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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Nodal Numerical Modeling of Submerged Helium Injection in a Cryogenic Propellant Tank

Subcooling of cryogenic propellant by helium injection is one of the most effective methods for suppressing bulk boiling and keeping subcooled propellant conditions for pre-launch, launch, and post-launch pressurization applications. For tank pressurization, submerged helium injection can substantially reduce helium consumption by infusing gaseous propellant into the tank ullage. This paper presents a mathematical model of the helium bubbling process in liquid oxygen to estimate the amount of oxygen vapor absorbed by the rising helium bubbles and the amount of subcooling of liquid oxygen due to evaporative heat and mass transfer. This mathematical model was incorporated in a simulation model of tank pressurization built with Generalized Fluid System Simulation Program (GFSSP), a general-purpose flow network code developed at NASA/Marshall Space Flight Center. The numerical predictions of subcooling have been compared with the experimental data of Cho et al. which investigated the propellant subcooling effect as a function of system pressure, helium injection temperature, and flowrate for a non-drained submerged injection system. The numerical predictions of helium consumption have been compared with the test data from a NASA Centaur test vehicle which included both direct and submerged injection with draining of propellants. The numerical model developed with GFSSP has been validated against two sets of experimental data and has been shown to predict both propellant subcooling and helium consumption to within 30% in most cases. The test data used for the model validation were taken in 1-g, but the mass diffusion model was developed to be applied in both 1-g and micro-g environments.

Cryogenics↗
NASA NTRSDate not supplied

Convolution-Based Numerical Solutions of Transient Temperature Fields during Powder Bed Fusion Additive Manufacturing: Theory, Accuracy, and Computational Cost

Powder bed fusion (PBF) additive manufacturing has found numerous applications in the aerospace domain. However, components fabricated via PBF have a complex time-temperature history that significantly impacts subsequent mechanical performance. This study examines convolution-based numerical solutions of transient temperature fields that support simulations involving arbitrary beam shapes and paths during PBF. The convolutional approach is verified through comparisons with analytical solutions of the temperature field. The computational speed and accuracy of the method are assessed through comparisons with other explicit and implicit numerical techniques. In addition, the straightforward translation of the approach from a CPU to a GPU implementation and the resultant performance improvement are presented. The role of the technique in predicting microstructure evolution during PBF (for a greater process-structure-property-performance framework) is also demonstrated. This work supports the development of computational materials methods for understanding and controlling the time-temperature history during PBF.

powder bed fusion↗
DOE OSTI2022

Assessment of Numerical Diffusion in NRELAP5 Code for Density Wave Oscillations Applications

Density wave oscillation (DWO) in a boiling channel can be a delicate phenomenon, and the precision of numerical tools can influence predictions. In this paper, relevant numerical diffusion was analyzed for the finite difference schemes used in the NRELAP5 code. The numerical diffusion in NRELAP5 was investigated under both single-phase and two-phase conditions. A unique perturbation technique called the “V” ramping approach was introduced, and the NRELAP5-predicted DWO results were then compared to test data.

Numerical diffusion, NRELAP5, RELAP5-3D, density w↗
DOE OSTI2022

Removing numerical pathologies in a turbulence parameterization through convergence testing

Discretized numerical models of the atmosphere are usually intended to faithfully represent an underlying set of continuous equations, but this necessary condition is violated sometimes by subtle pathologies that have crept into the discretized equations. Such pathologies can introduce undesirable artifacts, such as sawtooth noise, into the model solutions. The presence of these pathologies can be detected by numerical convergence testing. This study employs convergence testing to verify the discretization of the Cloud Layers Unified By Binormals (CLUBB) model of clouds and turbulence. That convergence testing identifies two aspects of CLUBB's equation set that contribute to undesirable noise in the solutions. First, numerical limiters (i.e. clipping) used by CLUBB introduce discontinuities or slope discontinuities in model fields. Second, this noise can be amplified by an advective term in CLUBB's background diffusion. Smoothing the limiters and removing the advective component of the background diffusion reduces the noise and restores the expected first-order convergence in CLUBB's solutions. These model reformulations improve the results at coarser, near-operational grid spacing and time step in cumulus cloud and dry turbulence tests. In addition, convergence testing is proved to be a valuable tool for detecting pathologies, including unintended discontinuities and grid dependence, in the model equation set.

Mathematics and Computing, Geosciences↗
DOE OSTI2015

Development of a discontinuous approach for modeling fluid flow in heterogeneous media using the numerical manifold method

Summary In the numerical modeling of fluid flow in heterogeneous geological media, large material contrasts associated with complexly intersected material interfaces are challenging, not only related to mesh discretization but also for the accurate realization of the corresponding boundary constraints. To address these challenges, we developed a discontinuous approach for modeling fluid flow in heterogeneous media using the numerical manifold method (NMM) and the Lagrange multiplier method (LMM) for modeling boundary constraints. The advantages of NMM include meshing efficiency with fixed mathematical grids (covers), the convenience of increasing the approximation precision, and the high integration precision provided by simplex integration. In this discontinuous approach, the elements intersected by material interfaces are divided into different elements and linked together using the LMM. We derive and compare different forms of LMMs and arrive at a new LMM that is efficient in terms of not requiring additional Lagrange multiplier topology, yet stringently derived by physical principles, and accurate in numerical performance. To demonstrate the accuracy and efficiency of the NMM with the developed LMM for boundary constraints, we simulate a number of verification and demonstration examples, involving a Dirichlet boundary condition and dense and intersected material interfaces. Last, we applied the developed model for modeling fluid flow in heterogeneous media with several material zones containing a fault and an opening. We show that the developed discontinuous approach is very suitable for modeling fluid flow in strongly heterogeneous media with good accuracy for large material contrasts, complex Dirichlet boundary conditions, or complexly intersected material interfaces. Copyright © 2015 John Wiley & Sons, Ltd.

Hu, Mengsu↗
DOE OSTI2017

A numerical and experimental study on weld lines formation and strength in extrusion

In this work, we present a study on numerical and experimental approaches aiming to improve our understanding about the relation between the flow conditions and the strength of weld lines in extruded profiles. For this purpose, a prototype extrusion die that comprises a movable spider leg is used to produce tapes under different flow conditions, by varying the location of the spider leg and the flow rate. The same case studies are numerically studied, considering a viscoelastic Giesekus constitutive model. The numerical results are then investigated to identify potential relationships between the flow conditions, in which the weld lines are formed, with the strength of the weld line experimentally characterized. The results obtained allow identifying a clear correlation between the flow conditions and the weld‐line strength. POLYM. ENG. SCI., 58:249–260, 2018. © 2017 Society of Plastics Engineers

Ferrás, Luís L.↗
DOE OSTI2018

Numerical Tools for Improved Convergence of Meshfree Peridynamic Discretizations

Peridynamic models have been employed to simulate a broad range of engineering applications concerning material failure and damage, with the majority of these simulations using a meshfree discretization. This chapter reviews that meshfree discretization, related issues present in peridynamic convergence studies, and possible remedies proposed in the literature. In particular, we discuss two numerical tools, partial-volume algorithms and influence functions, to improve the convergence behavior of numerical solutions in peridynamics. Numerical studies in this chapter involve static and dynamic simulations for linear elastic state-based peridynamic problems.

Seleson, Pablo D.↗
DOE OSTI2017

Numerical Simulation of Polynomial-Speed Convergence Phenomenon

We provide a hybrid method that captures the polynomial speed of convergence and polynomial speed of mixing for Markov processes. The hybrid method that we introduce is based on the coupling technique and renewal theory. We propose to replace some estimates in classical results about the ergodicity of Markov processes by numerical simulations when the corresponding analytical proof is difficult. After that, all remaining conclusions can be derived from rigorous analysis. Then we apply our results to seek numerical justification for the ergodicity of two 1D microscopic heat conduction models. The mixing rate of these two models are expected to be polynomial but very difficult to prove. In both examples, our numerical results match the expected polynomial mixing rate well.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Design and analysis of graphene–MoS{sub 2} hybrid layer based SPR biosensor with TiO{sub 2}–SiO{sub 2} nano film for formalin detection: numerical approach

In this paper, a Surface Plasmon Resonance (SPR) biosensor has been numerically developed that used Graphene–MoS{sub 2}–Au–TiO{sub 2}–SiO{sub 2} hybrid structure for the detection of formalin. This developed sensor has been sensed the presence the formalin based on attenuated total reflection (ATR) method by observing the change of “surface plasmon resonance angle-the change of minimum reflectance attributor” and “the resonance frequency characteristics (RFC)-maximum transmittance attributor”. Chitosan has been used as probe sensing medium to accelerate particular reaction with the formalin. Here, graphene is used as biomolecular recognition element because of its high adsorption ability and optical characteristics which helps to improve sensor sensitivity, MoS{sub 2} used for it has larger band gap, high fluroscence quenching ability, higher optical absorption efficiency, TiO{sub 2}–SiO{sub 2} bilayer as the improvement of sensitivity and Gold (Au) as the sharp SPR curve. Numerical results give the impression that the variation of RFC and SPR angle for improper sensing of formalin is quiet negligible that confirms no formalin is detected whereas for proper sensing these change are considerably countable that confirms the detection of formalin. From the sensor sensitivity analysis, owing to add TiO{sub 2}–SiO{sub 2} bilayer with Graphene–MoS{sub 2} Hybrid layer, maximum sensitivity of 85.375% has been numerically resulted. This high sensor performance is for taking advantages of Graphene surface high selectively which detect bio molecular compounds through pi-stacking force, larger work function (5.1 eV) of MoS{sub 2} which allows the high sensitive detection of bio targets and Rich plasmon happens at the TiO{sub 2}–SiO{sub 2} interface.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

Numerical Investigation of Novel Oxygen Blast Furnace Ironmaking Processes

Oxygen blast furnace (OBF) ironmaking process has the potential to realize “zero carbon footprint” production, but suffers from the “thermal shortage” problem. This paper presents three novel OBF processes, featured by belly injection of reformed coke oven gas, burden hot-charge operation, and their combination, respectively. These processes were studied by a multifluid process model. The applicability of the model was confirmed by comparing the numerical results against the measured key performance indicators of an experimental OBF operated with or without injection of reformed coke oven gas. Then, these different OBF processes together with a pure OBF were numerically examined in aspects of in-furnace states and global performance, assuming that the burden quality can be maintained during the hot-charge operation. The numerical results show that under the present conditions, belly injection and hot charge, as auxiliary measures, are useful for reducing the fuel rate and increasing the productivity for OBFs but in different manners. Hot charge should be more suitable for OBFs of different sizes because it improves the thermochemical states throughout the dry zone rather than within a narrow region in the case of belly injection. The simultaneous application of belly injection and hot charge leads to the best process performance, at the same time, lowering down hot-charge temperature to achieve the same carbon consumption and hot metal temperature as that achieved when applying the hot charge alone. This feature will be practically beneficial in the application of hot-charge operation. In addition, a systematic study of hot-charge temperature reveals that optimal hot-charge temperatures can be identified according to the utilization efficiency of the sensible heat of hot burden.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Propagation of Input Uncertainties in Numerical Simulations of Laser Powder Bed Fusion

Laser powder bed fusion has the potential of redefining state-of-the-art processing and production methods, but defect formation and inconsistent build quality have limited the implementation of this process. Numerical models are widely used to study this process and predict the formation of these defects. Presently, the uncertainties of model input parameters and thermophysical properties used by these numerical simulations have not been investigated. In the present study, the uncertainty in these input parameters and material properties are quantified for laser powder bed fusion, with and without a simulated powder bed, to determine their influence on the predictive accuracy of an experimentally validated numerical model. Accounting for all possible sources of uncertainty quickly becomes computationally expensive on account of the curse of dimensionality. Uncertainty in laser absorption, solid, and liquid specific heat of the metal were found to have the largest effect on model prediction reliability with or without the use of a powder bed. Results also illustrate that accounting for these three uncertain parameters still captures the majority of model prediction uncertainty. Furthermore, the methodology of this study may be used to understand the uncertainty in as-built microstructure through propagation to microstructure prediction models, or applied under processing conditions where high Péclet numbers are observed and the thermal convection and fluid flow within the molten pool are substantial.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Experimental Validation of Numerical Simulations of a New-Generation NiTi Endodontic File Under Bending

The superelasticity of NiTi shape memory alloy has been used in endodontics since the 1990s. To study the mechanical behavior of endodontic instruments, a traditional approach consists in experimental investigations. However, finite element analysis constitutes another way to assess their mechanical behavior and to facilitate their design. The main aim of this study is to compare experimental and numerical bending results on different structures (NiTi wire, spreader, and instruments) to estimate the reliability of the finite element simulations. These investigations were carried out as follows. Firstly, experimental material parameters identification was performed using NiTi wires. These parameters were implemented in an appropriate NiTi model. Bending was numerically applied to the meshed structures generated by the finite element method. Experimental tests were performed on real structures under bending, with exactly the same loading, in order to compare experimental and numerical results. These results were in good agreement for each of the considered structures. This enabled the validation of the simulation results and the use of simulations to design new endodontic instruments.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Crashworthiness of a Composite Wing Section: Numerical Investigation of the Bird Strike Phenomenon by Using a Coupled Eulerian–Lagrangian Approach

Crashworthiness is defined as the capability of a structure to guarantee its occupants safety during a crash event. In the present work, the crashworthiness of a composite wing section, subjected to a bird strike event, has been investigated. Indeed, the mechanical behavior of the impacted wing section has been inspected by means of the FE code Abaqus/Explicit. The impact phenomenon has been numerically simulated with a coupled Eulerian–Lagrangian (CEL) approach. The impacted structure has been modeled considering a Lagrangian formulation, while a Eulerian one has been used to model the bird. Moreover, Eulerian–Lagrangian contacts are used for transfer the loads arising from the impact event to the Lagrangian structure. The proposed numerical model, capable to take into account the matrix and fiber traction and compression damages, uses a 3D finite element approach to better predict the deformations and the damages onset and propagation during the impact event. The numerical results, in terms of structural deformation and damage onset and propagation, have been obtained by considering different impact locations and different impact angles.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Experimental and Numerical Investigation of PZT Response in Composite Structures with Variable Degradation Levels

Commercial aerospace vehicles have been increasingly demanding to withstand harsh conditions with low-weight material, i.e., composites. Unfortunately, low-velocity impacts strongly affect their performance. Structural health monitoring with permanently attached sensors allows achieving cost-effective maintenance and tearing down knockdown factors. However, the degradation of transducers adopted for online detection of damage negatively affects the diagnosis. That deterioration is addressed in this work with the electromechanical impedance approach employed at relatively low ultrasonic frequencies. Several degradation conditions are investigated with experimental and numerical simulations. The results demonstrate how the self-diagnosis approach detects pure sensor failures without any structural dependence. However, self-detection of the mixed mode of failures is challenging due to the opposite effect that different types of failure return. Numerical simulations provide a spectral response in compliance with measurements. On top of that, numerical results demonstrate that the combination of different types of damage may induce missed detection. That is where a multi-parameter self-diagnosis approach may further improve the overall monitoring system.

36 MATERIALS SCIENCE↗
DOE OSTI2019

An Integrated Numerical Method to Predict the Strain Sensing Behavior of Flexible Conductive Fibers under Electric–Thermal Conditions

Flexible conductive textiles have attracted an increasing amount of attention due to being flexible and stretchable with multi-functions, in addition to the strain sensing function. In this paper, an integrated numerical method is established to predict the strain sensing behavior of PPy-coated flexible conductive fibers. Based on our previous investigation on the strain sensing behavior of the PPy-coated elastic conductive fibers, it has been known that the main strain sensing mechanisms of the conductive fibers are micro-cracks opening under stretching and closing under unloading. Therefore, in the numerical approach, extended finite element method is used to simulate the multi-crack initiation and propagation. Then, by establishing a representative element model including a single crack, the resistance variation with the increase in crack width/depth can be obtained using the electric–thermal package in ABAQUS software. Combining the relationship between crack width and strain, the relationship between fractional increment in resistance (ΔR/R{sub 0}) and the strain can be obtained. The prediction of the fractional increment in resistance (ΔR/R{sub 0}) versus strain is consistent with the experimental results of PPy-coated Lycra fibers. The new integrated method is further verified by experimental results of PPy-coated XLA fibers, showing that the integrated numerical approach can capture the complicated strain sensing mechanisms of PPy-coated elastic fibers and predict the strain sensing behavior of flexible conductive fibers. This approach will make it possible to shorten the period, and reduce the cost in R&D of the PPy-coated electrically conductive fibers, comparing with the corresponding experimental work.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Numerical similarity solution for a variable coefficient K(m, n) equation

A technique for finding numerical similarity solutions to an initial boundary value problem (IBVP) for generalized K(m, n) equations is described. The equation under consideration is nonlinear and has variable coefficients. The original problem is transformed with the aid of Lie symmetries to an initial value problem (IVP) for a nonlinear third-order ordinary differential equation. The existence and uniqueness of the solution are examined, and the problem is consequently solved with the aid of a finite-difference scheme for various values of the governing parameters. In lieu of an exact symbolic solution, the scheme is validated by comparing the numerical solutions with the approximate analytic solutions obtained with the aid of the method of successive approximations in their region of validity. The accuracy, efficiency, and consistency of the scheme are demonstrated. Numerical solutions to the original initial boundary value problem are constructed for selected parameter values with the aid of the transforms. The qualitative behavior of the solutions as a function of the governing parameters is analyzed, and it is found that the examined IBVPs for generalized K(m, n) equations with variable coefficients that are functions of time, do not admit solitary wave or compacton solutions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Computationally efficient and error aware surrogate construction for numerical solutions of subsurface flow through porous media

Limiting the injection rate to restrict the pressure below a threshold at a critical location can be an important goal of simulations that model the subsurface pressure between injection and extraction wells. The pressure is approximated by the solution of Darcy’s partial differential equation for a given permeability field. The subsurface permeability is modeled as a random field since it is known only up to statistical properties. This induces uncertainty in the computed pressure. Solving the partial differential equation for an ensemble of random permeability simulations enables estimating a probability distribution for the pressure at the critical location. These simulations are computationally expensive, and practitioners often need rapid online guidance for real-time pressure management. An ensemble of numerical partial differential equation solutions is used to construct a Gaussian process regression model that can quickly predict the pressure at the critical location as a function of the extraction rate and permeability realization. The Gaussian process surrogate analyzes the ensemble of numerical pressure solutions at the critical location as noisy observations of the true pressure solution, enabling robust inference using the conditional Gaussian process distribution. Our first novel contribution is to identify a sampling methodology for the random environment and matching kernel technology for which fitting the Gaussian process regression model scales as O ( n log n ) instead of the typical O ( n 3 ) rate in the number of samples n used to fit the surrogate. The surrogate model allows almost instantaneous predictions for the pressure at the critical location as a function of the extraction rate and permeability realization. Our second contribution is a novel algorithm to calibrate the uncertainty in the surrogate model to the discrepancy between the true pressure solution of Darcy’s equation and the numerical solution. Finally, although our method is derived for building a surrogate for the solution of Darcy’s equation with a random permeability field, the framework broadly applies to solutions of other partial differential equations with random coefficients.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Revisiting numerical real-space renormalization group for quantum lattice systems

Highlights: •A regularized scheme of the NRG algorithm is proposed. •The method overcomes the boundary obstacle in applying the NRG to quantum lattices. •Extension of the scheme to 2D lattices is illustrated. •Benchmark test on the Heisenberg antiferromagnet demonstrates its numerical validity. -- Abstract: Although substantial progress has been achieved in solving quantum impurity problems, the numerical renormalization group (NRG) method generally performs poorly when applied to quantum lattice systems in a real-space blocking form. The approach was thought to be unpromising for most lattice systems owing to its flaw in dealing with the boundaries of the block. Here the discovery of intrinsic prescriptions to cure interblock interactions is proposed which is able to clear up the boundary obstacle in applying the NRG to quantum lattice systems. While the resulting RG transformation turns out to be strict in the thermodynamic limit, benchmark tests of the algorithm on a one-dimensional Heisenberg antiferromagnet and a two-dimensional tight-binding model demonstrate its numerical efficiency in resolving low-energy spectra for finite lattice systems.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗