SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Gains of lasers with regular polygon cross sections of tubes are considered. Results obtained demonstrate the consistency of the model.
Matrix factorization is widely used in recommendation systems, text mining, face recognition and computer vision. As one of the most popular methods, nonnegative matrix factorization and its incremental variants have attracted much attention. The existing incremental algorithms are established based on the assumption of samples are independent and only update the new latent variable of weighting coefficient matrix when the new sample comes, which may lead to inferior solutions. To address this issue, we investigate a novel incremental nonnegative matrix factorization algorithm based on correlation and graph regularizer (ICGNMF). The correlation is mainly used for finding out those correlated rows to be updated, that is, we assume that samples are dependent on each other. We derive the updating rules for ICGNMF by considering the correlation. We also present tests on widely used image datasets, and show ICGNMF reduces the error by comparing other methods.
In this paper, we design a compact finite difference scheme which preserves the original conservative properties to solve the generalized symmetric regularized long-wave equations. The existence of the difference solution is proved by the Brouwer fixed-point theorem. Applying the discrete energy method, the convergence and stability of the difference scheme is obtained, and its numerical convergence order is O(τ{sup 2}+h{sup 4}) in the L{sup ∞}-norm for u and ρ. For computing the nonlinear algebraic system generated by the compact scheme, a decoupled iterative algorithm is constructed and proved to be convergent. Numerical experiment results show that the theory is accurate and the method is efficient and reliable.
In this paper, we propose a numerical method to approach the solution of a Fredholm integral equation with a weakly singular kernel by applying the convolution product as a regularization operator and the Fourier series as a projection. Preliminary numerical results show that the order of convergence of the method is better than the one of conventional projection methods.
The article “An elliptic regularity theorem for fractional partial differential operators”, written by Arran Fernandez, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on May 02, 2018 without open access.
Here we investigate the irregular eutectic growth dynamics of the Al-Al 3 Ni alloy, in which one of the solid phases (Al 3 Ni) grows faceted from the liquid. Leveraging in situ optical microscopy and synchrotron transmission x-ray microscopy, we address the question of the degree of coupling between Al and Al 3 Ni at the growth front and that of the shape of the microstructures left behind in the bulk solid during directional solidification. Real-time optical observations bring evidence for a morphological transition from a eutectic-grain dependent, irregular eutectic growth at low solidification velocity V (typically 1 μm s -1 ), to a weakly anisotropic, regular growth at higher V ( reaching 10 μm s -1 ). Unprecedented x-ray nano-imaging of the solid–liquid interface, and 3D characterization of the growth patterns, were made possible by a new DS setup at Brookhaven National Laboratory’s NSLS-II. At low V, the leading tips of partly faceted Al 3 Ni crystals are observed to grow not far ahead of the Al growth front. Correlating in situ images and postmortem 3D tomographic reconstructions reveals that the presence of faceted and non-faceted regions of Al 3 Ni crystals in the solid is a direct consequence of coupling and decoupling during DS, respectively. Upon increasing V, the lead distance of Al 3 Ni vanishes, and the shape of Al 3 Ni ceases to be governed by faceted growth. These observations cast light onto the basic mechanisms (faceted growth, diffusive coupling, and the dynamics of trijunctions) governing a faceted to rod-like transition upon increasing V in the Al 3 Ni system, with broad implications to a large class of irregular eutectics.
Replacing vector type of interaction of the Thirring–Wess model by the chiral type a new model is presented which is termed here as chiral Thirring–Wess model. Ambiguity parameters of regularization are so chosen that the model falls into the Faddeevian class. The resulting Faddeevian class of model in general does not possess Lorentz invariance. However we can exploit the arbitrariness admissible in the ambiguity parameters to relate the quantum mechanically generated ambiguity parameters with the classical parameter involved in the masslike term of the gauge field which helps to maintain physical Lorentz invariance instead of the absence of manifestly Lorentz covariance of the model. The phase space structure and the theoretical spectrum of this class of model have been determined through Dirac’s method of quantization of constraint system.
Quantum simulations would be highly desirable in order to investigate the finite density physics of QCD. (1+1)-d CP(N−1) quantum field theories are toy models that share many important features of QCD: they are asymptotically free, have a non-perturbatively generated massgap, as well as θ-vacua. SU(N) quantum spin ladders provide an unconventional regularization of CP(N−1) models that is well-suited for quantum simulation with ultracold alkaline-earth atoms in an optical lattice. In order to validate future quantum simulation experiments of CP(2) models at finite density, here we use quantum Monte Carlo simulations on classical computers to investigate SU(3) quantum spin ladders at non-zero chemical potential. This reveals a rich phase structure, with single- or double-species Bose–Einstein “condensates”, with or without ferromagnetic order.
Black hole perturbation theory is a useful approach to study interactions between black holes and fundamental fields. A particular class of black hole solutions arising out of modification of Einstein’s general theory of relativity are regular black holes (RBHs) which can be constructed using a nonlinear electrodynamic Lagrangian. Because of their importance, we are interested in studying the behavior of three kinds of such RBHs under perturbations generated by an external field. Indeed, we investigate the quasinormal modes (QNMs) of a massive scalar field propagating near the RBHs which is non-minimally coupled to the Ricci scalar-tensor of background geometry. We will attempt to find the low-lying quasinormal frequencies of the perturbations by using WKB approximation. We shall also study the relationship between the QNMs and some characteristic properties of black holes such as grey-body factors, area quantization, and shadow radius.
In the setting of continuum elasticity martensitic phase transformations are characterized by a non-convex free energy density function that possesses multiple wells in strain space and includes higher-order gradient terms for regularization. Metastable martensitic microstructures, defined as solutions that are local minimizers of the total free energy, are of interest and are obtained as steady state solutions to the resulting transient formulation of Toupin’s gradient elasticity at finite strain. This type of problem poses several numerical challenges including stiffness, the need for fine discretization to resolve microstructures, and following solution branches. Accurate time-integration schemes are essential to obtain meaningful solutions at reasonable computational cost. Here in this work we introduce two classes of unconditionally stable second-order time-integration schemes for gradient elasticity, each having relative advantages over the other. Numerical examples are shown highlighting these features.
Turbulence closure models that are based on a regularized deconvolution method (RDM) are proposed for application to implicitly filtered Large-Eddy Simulation (LES). This method reconstructs sub-grid scale contributions by approximately recovering filtered quantities through an optimization approach. Physical principles on the boundedness and conservation of reconstructed quantities are preserved by constraining the optimization problem. Further, to account for effects of scales that are not resolved in implicitly filtered LES, a reconstruction method is proposed that combines sub-grid projection and energy-similarity to enrich unresolved scales. With this method, closure models are developed for turbulent scalar fluxes and turbulence–chemistry interaction that are intrinsically consistent with the LES formulation. These closure models are evaluated in application to a piloted turbulent jet flame with inhomogeneous inlet composition, in which combustion is represented by a two-scalar manifold model. The RDM-formulation is benchmarked against simulations obtained using a presumed PDF method and eddy diffusivity closure model. In partially-premixed flame regions, it is observed that RDM improves the prediction of turbulent mixing, and faster grid convergence is observed for results with RDM compared to simulations employing a presumed PDF method.
Bayesian parameter inference is useful to improve Li-ion battery diagnostics and can help formulate battery aging models. However, it is computationally intensive and cannot be easily repeated for multiple cycles, multiple operating conditions, or multiple replicate cells. To reduce the computational cost of Bayesian calibration, numerical solvers for physics-based models can be replaced with faster surrogates. A physics-informed neural network (PINN) is developed as a surrogate for the pseudo-2D (P2D) battery model calibration. For the P2D surrogate, additional training regularization was needed as compared to the PINN single-particle model (SPM) developed in Part I. Both the PINN SPM and P2D surrogate models are exercised for parameter inference and compared to data obtained from a direct numerical solution of the governing equations. A parameter inference study highlights the ability to use these PINNs to calibrate scaling parameters for the cathode Li diffusion and the anode exchange current density. By realizing computational speed-ups of ~2250x for the P2D model, as compared to using standard integrating methods, the PINN surrogates enable rapid state-of-health diagnostics. Finally, in the low-data availability scenario, the testing error was estimated to ~2 mV for the SPM surrogate and ~10 mV for the P2D surrogate which could be mitigated with additional data.
One primary challenge for prediction of gas flow in the unconventional gas reservoir at the pore-scale such as shale and tight gas reservoirs is the geometric complexity of the micro-porous media. In this paper, a regularized multiple-relaxation-time (MRT) lattice Boltzmann (LB) model is applied to analyze gas flow in 2-dimensional micro-porous medium reconstructed by quartet structure generation set (QSGS) on pore-scale. In this paper, the velocity distribution inside the porous structure is presented and analyzed, and the effects of the porosity and specific surface area on the rarefied gas flow and apparent permeability are examined and investigated. The simulation results indicate that the gas exhibits different flow behaviours at various pressure conditions and the gas permeability is strongly related to the pressure. Finally, the increased porosity or the decreased specific surface area leads to the increase of the gas apparent permeability, and the gas flow is more sensitive to the pore morphological properties at low-pressure conditions.
The injection of multi-species fluids into high-pressure and high-temperature environments beyond the species' critical points is commonly found in engineering applications. At these conditions, for immiscible species, both subcritical interfacial dynamics and supercritical mixing can coexist due to variations in temperature around the mixture critical point. The modeling of these complex transcritical phenomena for large-scale configurations is so far not possible. To address this issue, we propose the Regularized-Interface Method (RIM) as a unified formulation that can describe both sub- and supercritical processes as well as the transition between them. The proposed method is derived via filtering of the nanoscale interface-resolving formulation based on van der Waals' linear gradient theory. Thus, this approach allows for the consistent modeling of interfacial dynamics that vanishes at supercritical conditions, while significantly reducing the temporal and spatial resolution constraints of the original nanoscale formulation. The resulting RIM formulation is examined in interface-capturing simulations of sub-, trans-, and supercritical fuel injection processes, involving droplets and jets. Furthermore, these results highlight the importance of resolving spatio-temporal transitions from subcritical interfacial dynamics to supercritical mixing in high-pressure multiphase simulations, in contrast to commonly employed diffused-interface methods, where interfacial dynamics are often neglected.
This paper presents experimental and numerical studies on the hydrodynamics of a two-body floating-point absorber (FPA) wave energy converter (WEC) under both extreme and operational wave conditions. In this study, the responses of the WEC in heave, surge, and pitch were evaluated for various regular wave conditions. For extreme condition analysis, we assume the FPA system has a survival mode that locks the power-take-off (PTO) mechanism in extreme waves, and the WEC moves as a single body in this scenario. A series of Reynolds-averaged Navier-Stokes (RANS) simulations was performed for the survival condition analysis, and the results were validated with the measurements from experimental wave tank tests. For the FPA system in operational conditions, both a boundary element method (BEM) and the RANS simulations were used to analyze the motion response and power absorption performance. Additional viscous damping, primarily induced by flow separation and vortex shedding, is included in the BEM simulation as a quadratic drag force proportional to the square of body velocity. The inclusion of viscous drag improves the accuracy of BEM's prediction of the heave response and the power absorption performance of the FPA system, which agrees well with experimental data and the RANS simulation results over a broad range of incident wave periods, except near resonance in large wave height scenarios. Overall, the experimental and numerical results suggest that nonlinear effects, caused by viscous damping and interaction between waves and the FPA, significantly influence the system response and power absorption performance. Nonlinear effects were found to be particularly significant when the wave height was large and the period was near or shorter than the resonant period of the FPA system. The study is expected to be helpful for understanding the nonlinear interaction between waves and the FPA system so that the structure of the FPA can be adequately designed.
With tuning the ligands from bte, btp, btb to bth, four new decavanadate-based metal–organic hybrid compounds, [Zn(bte)(H{sub 2}O){sub 4}][Zn{sub 2}(bte)(H{sub 2}O){sub 10}](V{sub 10}O{sub 28})·8H{sub 2}O, [Zn{sub 2}(btp){sub 4}(H{sub 2}O){sub 6}](H{sub 2}V{sub 10}O{sub 28})·4H{sub 2}O, [Zn(H{sub 2}O){sub 6}][Zn{sub 2}(btb){sub 2}V{sub 10}O{sub 28}(H{sub 2}O){sub 6}]·4H{sub 2}O, and [Zn{sub 2}(bth)(H{sub 2}O){sub 10}](H{sub 2}V{sub 10}O{sub 28})·6H{sub 2}O (bte=1,2-bis(1,2,4-triazol-1-yl)ethane, btp=1,3-bis(1,2,4-triazol-1-y1)propane, btb=1,4-bis(1,2,4-triazol-1-y1)butane, bth=1,6-bis(1,2,4-triazol-1-y1)hexane), have been synthesized under conventional conditions. The four compounds represent the first examples of decavanadate-based metal–organic hybrids constructed by Zn–bis(triazole) complexes. Their structural analyses show that the four compounds possess different Zn–bis(triazole) structural motifs and various finally structures, which verifies that regular changing the spacers of ligands is an effective strategy to tuning the structures of polyoxometalate-based hybrids. Also, the electrochemical studies show that the compounds have good electrocatalytic activities towards oxidation of nitrite molecules ascribed to V-centers. - Graphical abstract: Four compounds representing the first examples of V{sub 10}O{sub 28}-based hybrids constructed by Zn–bis(triazole) complexes have been synthesized by changing the spacers of the ligands and their electrocatalytic properties have been investigated. - Highlights: • The first examples of V{sub 10}O{sub 28}-based hybrids constructed by Zn-bis(triazole) complexes. • Verifying that changing the spacers of ligands is a strategy to tuning structures. • Showing good electrocatalytic activities toward oxidation of nitrite molecules.
The floating oscillating surge wave energy converter (FOSWEC) is a wave energy converter that was designed, built, and tested to develop an open-access data set for the purpose of numerical model validation. Here, this paper details the experimental testing of the 1:33-scale FOSWEC in a directional wave basin, and compares experimental data to numerical simulations using the wave energy converter simulator (WEC-Sim) open-source code. The FOSWEC consists of a floating platform moving in heave, pitch, and surge, and two pitching flaps. Power is extracted through relative motion between each of the flaps and the platform. The device was designed to constrain different degrees of freedom so that it could be configured into a variety of operating conditions with varying dynamics. The FOSWEC was tested in a range of different conditions including: static offset, free decay, forced oscillation, wave excitation, and dynamic response to regular waves. In this paper, results from the range of experimental tests are presented and compared to numerical simulations using the WEC-Sim code.
Kohn–Sham regularizer (KSR) is a differentiable machine learning approach to finding the exchange-correlation functional in Kohn–Sham density functional theory that works for strongly correlated systems. Here we test KSR for a weak correlation. We propose spin-adapted KSR (sKSR) with trainable local, semilocal, and nonlocal approximations found by minimizing density and total energy loss. We assess the atoms-to-molecules generalizability by training on one-dimensional (1D) H, He, Li, Be, and Be 2+ and testing on 1D hydrogen chains, LiH, BeH 2 , and helium hydride complexes. The generalization error from our semilocal approximation is comparable to other differentiable approaches, but our nonlocal functional outperforms any existing machine learning functionals, predicting ground-state energies of test systems with a mean absolute error of 2.7 mH.