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At least 847 records · Page 47

Three-dimensional flow over a conical afterbody containing a centered propulsive jet - A numerical simulation

The supersonic flow field over a body of revolution incident to the free stream is simulated numerically on a large, array processor (the CDC Cyber 205). The configuration is composed of a cone-cylinder forebody followed by a conical afterbody from which emanates a centered, supersonic propulsive jet. The free-stream Mach number is 2, the jet-exit Mach number is 2.5, and the jet-to-free-stream static pressure ratio is 3. Both the external flow and the exhaust are ideal air at a common total temperature. The thin-layer approximation to the time-dependent, compressible, Reynolds-averaged Navier-Stokes equations are solved using an implicit finite-difference algorithm. The data base, of 5 million words, is structured in a 'pencil' format so that efficient use of the array processor can be realized. The computer code is completely vectorized to take advantage of the data structure. Turbulence closure is achieved using an empirical algebraic eddy-viscosity model. The configuration and flow conditions correspond to published experimental tests and the computed solutions are consistent with the experimental data.

Deiwert, G. S.↗

Free vibration analysis of coupled fluid-structure systems

An efficient numerical technique for the eigenvalue solution in the free vibration analysis of compressible fluid-structure coupled systems is presented. The fluid is assumed to be compressible in nature and the incompressible problem is only a special case of the present generalized algorithm. A natural frequency analysis of the structure in the absence of any fluid is achieved by a combined Sturm sequence and inverse iteration technique that computes only the required eigenvalues and vectors. A special inverse iteration scheme is then developed for the coupled system that uses the computed eigenvalues as starting iteration values for convergence. Numerical results obtained by solving a number of standard test cases indicate the pattern of root convergence corresponding to various simplifying assumptions.

Gupta, K. K.↗

Theoretical analysis of aircraft afterbody flow

The strongly interactive flow field about aircraft afterbodies is investigated using computational techniques by which the thin-shear-layer formulation of the compressible, Reynolds-averaged Navier-Stokes equations is solved. A time-dependent implicit numerical algorithm is used to obtain solutions for a variety of afterbody and nozzle geometries, within the class of bodies of revolution, for both subsonic and supersonic external flow, and for sonic and supersonic underexpanded jets. Only centered nozzles with either a sharp lip or a blunt base are considered. In all cases, computed results are compared with experimental data taken at flight Reynolds numbers for like-flow conditions. Turbulence closure is realized using algebraic eddy-viscosity concepts. A new and unique adaptive-grid technique is used to resolve flow regimes with large gradients and to improve the accuracy and efficiency of the computational scheme. Special singular point boundary conditions are used for similar purposes, and are especially effective for highly under-expanded jets. For all cases considered, except one with a very large base-to-nozzle-exit-diameter ratio, the agreement with experimental measurements is excellent. For geometries with large base regions, enhancements in the turbulence transport model are necessary to support improvements in the flow-field simulation.

Deiwert, G. S.↗

Parametric study of grid size, time step and turbulence modeling on Navier-Stokes computations over airfoils

An upwind-biased implicit approximate factorization algorithm is applied to several steady and unsteady turbulent flows. The thin layer form of the compressible Navier-Stokes equation is used. Both the flux vector splitting and flux difference splitting methods are used to determine fluxes, and the results are compared. Flux difference splitting predicts results more accurately than flux vector splitting on a given mesh size, but, in its present implementation, is more severely limited by the maximum CFL number for unsteady time accurate flows. Physical aspects of the computations are also examined. An equilibrium turbulent boundary layer model computes generally better steady and unsteady results than a nonequilibrium model when there is little to no boundary layer separation. Conversely, when a significant region of separation exists, the nonequilibrium model performs in better agreement with experiment.

Rumsey, Christopher L.↗

Numerical computation of shock wave-turbulent boundary layer interaction in transonic flow over an axisymmetric curved hill

A control-volume based finite difference computation of a turbulent transonic flow over an axisymmetric curved hill is presented. The numerical method is based on the SIMPLE algorithm, and hence the conservation of mass equation is replaced by a pressure correction equation for compressible flows. The turbulence is described by a k-epsilon turbulence model supplemented by a near-wall turbulence model. In the method, the dissipation rate in the region very close to the wall is obtained from an algebraic equation and that for the rest of the flow domain is obtained by solving a partial differential equation for the dissipation rate. The other flow equations are integrated up to the wall. It is shown that the present turbulence model yields the correct location of the compression shock. The other computational results are also in good agreement with experimental data.

Kim, S.-W.↗

Enhancement of the no-vent fill process

This paper presents an analytical and experimental evaluation of an enhanced techniques for no-vent fill. The method entails injecting liquid through the top of the receiver vessel, thereby increasing surface area and agitation of the ullage/liquid interface. Both of these factors promote condensation induced ullage collapse, and reduce compressive impedance to the incoming liquid. The enhanced process was analyzed by modifying the surface area algorithm of an existing tank thermodynamic code to model a downward-pointing, conical jet impringing on a steadily rising liquid surface. Transient pressure and temperature measurements from several tests with Freon-114 were input into the revised model to calculate condensation rate as a function of fill level. By expressing these rates in dimensionless form (i.e., in terms of Stanton number and Prandtl number), an empirical correlation similar to the submerged jet model of Brown and Sonin (1989) was derived. This provided a basis for developing an expression which relates top fill to bottom fill performance.

Vaughan, David A.↗

Hypersonic flow past open cavities

The hypersonic flow over a cavity is investigated. The time-dependent compressible Navier-Stokes equations, in terms of mass averaged variables, are numerically solved. An implicit algorithm, with a subiteration procedure to recover time-accuracy, is used to perform the time-accurate computations. The objective of the study is to investigate the effects of Reynolds number and cavity dimensions. The comparison of the computations with available experimental data, in terms of time mean static pressure, heat transfer, and Mach number show good agreement. In the computations large vortex structures, which adversely affect the cavity flow characteristics, are observed at the rear of the cavity. A self-sustained oscillatory motion occurs within the cavity over a range of Reynolds number and cavity dimensions. The frequency spectra of the oscillations show good agreement with a modified semi-empirical relation.

Morgenstern, Alagacyr, Jr.↗

Studies Of Coherent Synchrotron Radiation And Longitudinal Space Charge In The Jefferson Lab FEL Driver

The Jefferson Laboratory IR FEL Driver provides an ideal test bed for studying a variety of beam dynamical effects. Recent studies focused on characterizing the impact of coherent synchrotron radiation (CSR) with the goal of benchmarking measurements with simulation. Following measurements to characterize the beam, we quantitatively characterized energy extraction via CSR by measuring beam position at a dispersed location as a function of bunch compression. In addition to operating with the beam on the rising part of the linac RF waveform, measurements were also made while accelerating on the falling part. For each, the full compression point was moved along the backleg of the machine and the response of the beam (distribution, extracted energy) measured. Initial results of start-to-end simulations using a 1D CSR algorithm show remarkably good agreement with measurements. A subsequent experiment established lasing with the beam accelerated on the falling side of the RF waveform in conjunction with positive momentum compaction (R56) to compress the bunch. The success of this experiment motivated the design of a modified CEBAF-style arc with control of CSR and microbunching effects.

Tennant, Christopher D.↗

Grid Sensitivity and Aerodynamic Optimization of Generic Airfoils

An algorithm is developed to obtain the grid sensitivity with respect to design parameters for aerodynamic optimization. The procedure is advocating a novel (geometrical) parameterization using spline functions such as NURBS (Non-Uniform Rational B- Splines) for defining the airfoil geometry. An interactive algebraic grid generation technique is employed to generate C-type grids around airfoils. The grid sensitivity of the domain with respect to geometric design parameters has been obtained by direct differentiation of the grid equations. A hybrid approach is proposed for more geometrically complex configurations such as a wing or fuselage. The aerodynamic sensitivity coefficients are obtained by direct differentiation of the compressible two-dimensional thin-layer Navier-Stokes equations. An optimization package has been introduced into the algorithm in order to optimize the airfoil surface. Results demonstrate a substantially improved design due to maximized lift/drag ratio of the airfoil.

Sadrehaghighi, Ideen↗

Total variation vs L1 regularization: a comparison of compressive sensing optimization methods for chemical detection

One of the fundamental assumptions of compressive sensing (CS) is that a signal can be reconstructed from a small number of samples by solving an optimization problem with the appropriate regularization term. Two standard regularization terms are the L1 norm and the total variation (TV) norm. We present a comparison of CS reconstruction results based on these two approaches in the context of chemical detection, and we demonstrate that optimization based on the L1 norm outperforms optimization based on the TV norm. Our comparison is driven by CS sampling, reconstruction, and chemical detection in two real-world datasets: the Physical Sciences Inc. Fabry-Perot interferometer sensor multispectral dataset and the Johns Hopkins Applied Physics Lab FTIR-based longwave infrared sensor hyperspectral dataset. Both datasets contain the release of a chemical simulant such as glacial acetic acid, triethyl phosphate, and sulfur hexafluoride. For chemical detection we use the adaptive coherence estimator (ACE) and bulk coherence, and we propose algorithmic ACE thresholds to define the presence or absence of a chemical of interest in both un-compressed data cubes and reconstructed data cubes. The un-compressed data cubes provide an approximate ground truth. We demonstrate that optimization based on either the L1 norm or TV norm results in successful chemical detection at a compression rate of 90%, but we show that L1 optimization is preferable. We present quantitative comparisons of chemical detection on reconstructions from the two methods, with an emphasis on the number of pixels with an ACE value above the threshold.

Hyperspectral imagery, L1-norm, total variation, A↗

Grid and aerodynamic sensitivity analyses of airplane components

An algorithm is developed to obtain the grid sensitivity with respect to design parameters for aerodynamic optimization. The procedure is advocating a novel (geometrical) parameterization using spline functions such as NURBS (Non-Uniform Rational B-Splines) for defining the wing-section geometry. An interactive algebraic grid generation technique, known as Two-Boundary Grid Generation (TBGG) is employed to generate C-type grids around wing-sections. The grid sensitivity of the domain with respect to geometric design parameters has been obtained by direct differentiation of the grid equations. A hybrid approach is proposed for more geometrically complex configurations such as a wing or fuselage. The aerodynamic sensitivity coefficients are obtained by direct differentiation of the compressible two-dimensional thin-layer Navier-Stokes equations. An optimization package has been introduced into the algorithm in order to optimize the wing-section surface. Results demonstrate a substantially improved design due to maximized lift/drag ratio of the wing-section.

Sadrehaghighi, Ideen↗

A continuous analogue of the tensor-train decomposition

We develop new approximation algorithms and data structures for representing and computing with multivariate functions using the functional tensor-train (FT), a continuous extension of the tensor-train (TT) decomposition. The FT represents functions using a tensor-train ansatz by replacing the three-dimensional TT cores with univariate matrix-valued functions. The main contribution of this paper is a framework to compute the FT that employs adaptive approximations of univariate fibers, and that is not connected to any tensorized discretization. The algorithm can be coupled with any univariate linear or nonlinear approximation procedure. We demonstrate that this approach can generate multivariate function approximations that are several orders of magnitude more accurate, for the same cost, than those based on the conventional approach of compressing the coefficient tensor of a tensor-product basis. Our approach is in the spirit of other continuous computation packages such as Chebfun, and yields an algorithm which requires the computation of “continuous” matrix factorizations such as the LU and QR decompositions of vector-valued functions. To support these developments, we describe continuous versions of an approximate maximum-volume cross approximation algorithm and of a rounding algorithm that re-approximates an FT by one of lower ranks. We demonstrate that our technique improves accuracy and robustness, compared to TT and quantics-TT approaches with fixed parameterizations, of high-dimensional integration, differentiation, and approximation of functions with local features such as discontinuities and other nonlinearities.

42 ENGINEERING↗

Optimal Orbital Selection for Full Configuration Interaction (OptOrbFCI): Pursuing the Basis Set Limit under a Budget

Full configuration interaction (FCI) solvers are limited to small basis sets due to their expensive computational costs. An optimal orbital selection for FCI (OptOrbFCI) is proposed to boost the power of existing FCI solvers to pursue the basis set limit under a computational budget. The optimization problem coincides with that of the complete active space SCF method (CASSCF), while OptOrbFCI is algorithmically quite different. OptOrbFCI effectively finds an optimal rotation matrix via solving a constrained optimization problem directly to compress the orbitals of large basis sets to one with a manageable size, conducts FCI calculations only on rotated orbital sets, and produces a variational ground-state energy and its wave function. Coupled with coordinate descent full configuration interaction (CDFCI), we demonstrate the efficiency and accuracy of the method on the carbon dimer and nitrogen dimer under basis sets up to cc-pV5Z. We also benchmark the binding curve of the nitrogen dimer under the cc-pVQZ basis set with 28 selected orbitals, which provide consistently lower ground-state energies than the FCI results under the cc-pVDZ basis set. Furthermore, the dissociation energy in this case is found to be of higher accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Sparse optimization of two-dimensional terahertz spectroscopy

Two-dimensional terahertz spectroscopy (2DTS) is a low-frequency analog of two-dimensional optical spectroscopy that is rapidly maturing as a probe of a wide variety of condensed matter systems. However, a persistent problem with 2DTS is the long experimental acquisition times, which prevent its broader adoption. A potential solution, requiring no increase in experimental complexity, is signal reconstruction via compressive sensing. In this work, we apply the sparse exponential mode analysis (SEMA) technique to 2DTS of a cuprate superconductor. We benchmark the performance of the algorithm in reconstructing terahertz nonlinearities and find that SEMA reproduces the asymmetric photon echo line shapes at sampling rates as low as 10%, reaching the reconstruction noise floor at sampling rates beyond 20%–30%. The success of SEMA in reproducing such subtle, asymmetric line shapes confirms compressive sensing as a general method to accelerate 2DTS and multidimensional spectroscopies more broadly.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Algorithms for the Euler and Navier-Stokes equations for supercomputers

The steady state Euler and Navier-Stokes equations are considered for both compressible and incompressible flow. Methods are found for accelerating the convergence to a steady state. This acceleration is based on preconditioning the system so that it is no longer time consistent. In order that the acceleration technique be scheme-independent, this preconditioning is done at the differential equation level. Applications are presented for very slow flows and also for the incompressible equations.

Turkel, E.↗

Algorithms for the Euler and Navier-Stokes equations for supercomputers

The steady state Euler and Navier-Stokes equations are considered for both compressible and incompressible flow. Methods are found for accelerating the convergence to a steady state. This acceleration is based on preconditioning the system so that it is no longer time consistent. In order that the acceleration technique be scheme-independent, this preconditioning is done at the differential equation level. Applications are presented for very slow flows and also for the incompressible equations.

Turkel, E.↗

Genome-wide functional screens enable the prediction of high activity CRISPR-Cas9 and -Cas12a guides in Yarrowia lipolytica

Abstract Genome-wide functional genetic screens have been successful in discovering genotype-phenotype relationships and in engineering new phenotypes. While broadly applied in mammalian cell lines and in E. coli , use in non-conventional microorganisms has been limited, in part, due to the inability to accurately design high activity CRISPR guides in such species. Here, we develop an experimental-computational approach to sgRNA design that is specific to an organism of choice, in this case the oleaginous yeast Yarrowia lipolytica . A negative selection screen in the absence of non-homologous end-joining, the dominant DNA repair mechanism, was used to generate single guide RNA (sgRNA) activity profiles for both SpCas9 and LbCas12a. This genome-wide data served as input to a deep learning algorithm, DeepGuide, that is able to accurately predict guide activity. DeepGuide uses unsupervised learning to obtain a compressed representation of the genome, followed by supervised learning to map sgRNA sequence, genomic context, and epigenetic features with guide activity. Experimental validation, both genome-wide and with a subset of selected genes, confirms DeepGuide’s ability to accurately predict high activity sgRNAs. DeepGuide provides an organism specific predictor of CRISPR guide activity that with retraining could be applied to other fungal species, prokaryotes, and other non-conventional organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Visualization Quality Assessment

Understanding how inaccuracies in visualizations affect users’ perception and understanding of scientific data is hard. Inaccuracies in visualizations are quite common and could arise from a range of sources such as errors in the original dataset arising from compression artifacts, errors in the capturing device, noise during transmission of the data, effects due to the algorithm being used to convert data to visualization images, images generated from neural networks, and sources we have yet to discover. Many image quality assessment metrics have been developed to quantify image errors. However, these are usually focused on “natural images” rather than visualizations of scientific data. Common image quality assessment metrics (IQAs) include MSE, PSNR, perceptual metrics such SSIM, FSIM as well as perceptual metrics using deep learning approaches. However, a critical part of understanding how errors are perceived by humans, and subsequently developing more accurate quality assessment metrics, is through user evaluation studies. The goal of this software is to develop a visualization quality assessment (VQA) process that will enable the generation of VQAs that can be used to quantify errors in scientific data visualizations. The VQA development process will include software to support user evaluation experimental design, analysis of visualization differences against standard quality metrics, and the ability to develop additional VQA metrics specific to scientific visualization images.

Grosset, Andre↗