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At least 973 records · Page 54

Hierarchic models for laminated plates

Structural plates and shells are three-dimensional bodies, one dimension of which happens to be much smaller than the other two. Thus, the quality of a plate or shell model must be judged on the basis of how well its exact solution approximates the corresponding three-dimensional problem. Of course, the exact solution depends not only on the choice of the model but also on the topology, material properties, loading and constraints. The desired degree of approximation depends on the analyst's goals in performing the analysis. For these reasons models have to be chosen adaptively. Hierarchic sequences of models make adaptive selection of the model which is best suited for the purposes of a particular analysis possible. The principles governing the formulation of hierarchic models for laminated plates are presented. The essential features of the hierarchic models described models are: (1) the exact solutions corresponding to the hierarchic sequence of models converge to the exact solution of the corresponding problem of elasticity for a fixed laminate thickness; and (2) the exact solution of each model converges to the same limit as the exact solution of the corresponding problem of elasticity with respect to the laminate thickness approaching zero. The formulation is based on one parameter (beta) which characterizes the hierarchic sequence of models, and a set of constants whose influence was assessed by a numerical sensitivity study. The recommended selection of these constants results in the number of fields increasing by three for each increment in the power of beta. Numerical examples analyzed with the proposed sequence of models are included and good correlation with the reference solutions was found. Results were obtained for laminated strips (plates in cylindrical bending) and for square and rectangular plates with uniform loading and with homogeneous boundary conditions. Cross-ply and angle-ply laminates were evaluated and the results compared with those of MSC/PROBE. Hierarchic models make the computation of any engineering data possible to an arbitrary level of precision within the framework of the theory of elasticity.

Actis, Ricardo Luis↗

Airfoil optimization by the one-shot method

An efficient numerical approach for the design of optimal aerodynamic shapes is presented in this paper. The objective of any optimization problem is to find the optimum of a cost function subject to a certain state equation (Governing equation of the flow field) and certain side constraints. As in classical optimal control methods, the present approach introduces a costate variable (Language multiplier) to evaluate the gradient of the cost function. High efficiency in reaching the optimum solution is achieved by using a multigrid technique and updating the shape in a hierarchical manner such that smooth (low-frequency) changes are done separately from high-frequency changes. Thus, the design variables are changed on a grid where their changes produce nonsmooth (high-frequency) perturbations that can be damped efficiently by the multigrid. The cost of solving the optimization problem is approximately two to three times the cost of the equivalent analysis problem.

Kuruvila, G.↗

Airfoil Design and Optimization by the One-Shot Method

An efficient numerical approach for the design of optimal aerodynamic shapes is presented in this paper. The objective of any optimization problem is to find the optimum of a cost function subject to a certain state equation (governing equation of the flow field) and certain side constraints. As in classical optimal control methods, the present approach introduces a costate variable (Lagrange multiplier) to evaluate the gradient of the cost function. High efficiency in reaching the optimum solution is achieved by using a multigrid technique and updating the shape in a hierarchical manner such that smooth (low-frequency) changes are done separately from high-frequency changes. Thus, the design variables are changed on a grid where their changes produce nonsmooth (high-frequency) perturbations that can be damped efficiently by the multigrid. The cost of solving the optimization problem is approximately two to three times the cost of the equivalent analysis problem.

Kuruvila, G.↗

Progress Toward Evaluating Roughness-Resolved Aerothermodynamic Simulations for the Mars Sample Return Earth Entry System

This work pursues the efficient Navier-Stokes simulation, using NASA’s standard LAURA and DPLR simulation tools, of the flowfield and convective heating resulting from the patterned-roughness surface of the Mars Sample Return (MSR) Earth Entry System (EES). This type of simulation has been infeasible for past NASA missions. However, for EES, the combination of a patterned roughness heatshield approximated with a sinusoidal pattern, the zero degrees angle of attack nominal flow, and the supersonic boundary layer edge Mach number, all combine to make these roughness resolved grid simulations feasible. The patterned roughness and zero degrees angle of attack nominal flow allow the simulation domain to be reduced to a thin axial flowfield slice that captures a minimum of single period of the roughness pattern. With a periodic boundary condition applied along the boundaries of this slice, simulation on the reduced domain is identical to the full domain but with significant cost saving. The supersonic boundary layer edge Mach number prevents the upstream influence, which allows the smooth stagnation region to be frozen. This freezing of the stagnation region flow is required because of the numerical instability resulting from the tight spacing of the grid in the axial direction as the stagnation point is approached. Applying the developed analysis approach to a peak heating EES case results in a roughness augmentation factor for the convective heating of 1.32, which agrees well with correlations that predict values between 1.30 and 1.37. Analysis approach developed in this work provides the framework for future studies of turbulence modeling impacts and the influence of an ablating surface.

Earth Entry System↗

Analysis of fast-ion losses measured in MAST-U via infrared thermography and a Fast Ion Loss Detector

Fast-ion losses need to be monitored to avoid damage to plasma facing components. In existing experimental devices, the scintillator-based fast-ion loss detector (FILD) is the most advanced diagnostic for measuring fast-ion losses. However, FILDs provide only local information about the losses. Infrared (IR) thermography can be used as a complementary tool for more global monitoring of the deposition of fast-ion losses on the wall, at the expense of no velocity-space resolution. IR cameras measure the temperature of the plasma facing components. This measurement, determined by a combined effect of the thermal plasma, radiation, neutrons and fast-ion losses, can be decomposed to infer the fast-ion load on the tokamak wall. In this manuscript, a workflow to estimate fast-ion losses via IR thermography is applied to the MAST-U spherical tokamak, using a 1D approximation to extract the experimental heat flux on the FILD front face from IR data. To numerically estimate the different contributions to this total heat flux, the field-line tracing environment SMITER is used to calculate the thermal plasma contribution, the orbit-following Monte-Carlo code ASCOT to estimate the fast-ion losses, and bolometry measurements for the radiation. To validate the workflow, two discharges, L-mode plasmas with low MHD activity, were executed using on and off-axis beams, respectively. The experimentally and numerically estimated heat flux are of the same order of magnitude for the on-axis heated scenario, with a strong dependence of the estimated fast-ion losses contribution on the fit to the kinetic profiles used as input. This is also true for the off-axis heated scenario, where the total numerically estimated heat flux is 2.1 or 1.3 times higher than the maximum experimentally estimated heat flux, depending on the ASCOT input used.

FILD↗

Development of a neural network model for peeling–ballooning stability analysis in the KSTAR tokamak pedestals

The neural network model, MISHKA-NN is developed to mitigate the computational burden associated with the linear ideal magnetohydrodynamic (MHD) stability analysis of the pedestal based on the peeling–ballooning (P–B) model. By utilizing both 1D plasma profiles (current density, pressure gradient, and safety factor) and 0D parameters (plasma geometry, total current, and toroidal mode number), the model predicts linear growth rate of edge-localized ideal MHD instability in a given equilibrium state. By enabling the prediction of each instability within a second, the model reduces the time required for plotting a pedestal P–B stability diagram (j - α diagram) from approximately 100 CPU hours to a few CPU minutes. Notably, even with the utilization of parametric pressure and current profiles and plasma boundary shapes for the training dataset, the model shows a satisfactory level of performance in benchmarking the j - α diagram for the reconstructed equilibrium from a KSTAR tokamak experiment. We anticipate the model to serve as a versatile alternative to 2D linear MHD stability codes, alleviating numerical costs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

On the Departure from Monin–Obukhov Surface Similarity and Transition to the Convective Mixed Layer

Large-eddy simulations are used to evaluate mean profile similarity in the convective boundary layer (CBL). Particular care is taken regarding the grid sensitivity of the profiles and the mitigation of inertial oscillations in the simulation spin-up. The nondimensional gradients Φ for wind speed and air temperature generally align with Monin–Obukhov similarity across cases but have a steeper slope than predicted within each profile. The same trend has been noted in several other recent studies. The Businger-Dyer relations are modified here with an exponential cutoff term to account for the decay in Φ to first-order approximation, yielding improved similarity from approximately 0.05z i to above 0.3z i , where z i is the CBL depth. The necessity for the exponential correction is attributed to an extended transition from surface scaling to zero gradient in the mixed layer, where the departure from Monin–Obukhov similarity may be negligible at the surface but becomes substantial well below the conventional surface layer height of 0.1 z i .

54 ENVIRONMENTAL SCIENCES↗

Evaluating large scale aqueous organic redox flow battery performance with a hybrid numerical and machine learning framework

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low-capacity degradation in 10 cm$^2$ cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier to commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm$^2$ DHP-based AORFB by combining a physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. Such combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

Adjoint Algorithm for CAD-Based Shape Optimization Using a Cartesian Method

Adjoint solutions of the governing flow equations are becoming increasingly important for the development of efficient analysis and optimization algorithms. A well-known use of the adjoint method is gradient-based shape optimization. Given an objective function that defines some measure of performance, such as the lift and drag functionals, its gradient is computed at a cost that is essentially independent of the number of design variables (geometric parameters that control the shape). More recently, emerging adjoint applications focus on the analysis problem, where the adjoint solution is used to drive mesh adaptation, as well as to provide estimates of functional error bounds and corrections. The attractive feature of this approach is that the mesh-adaptation procedure targets a specific functional, thereby localizing the mesh refinement and reducing computational cost. Our focus is on the development of adjoint-based optimization techniques for a Cartesian method with embedded boundaries.12 In contrast t o implementations on structured and unstructured grids, Cartesian methods decouple the surface discretization from the volume mesh. This feature makes Cartesian methods well suited for the automated analysis of complex geometry problems, and consequently a promising approach to aerodynamic optimization. Melvin et developed an adjoint formulation for the TRANAIR code, which is based on the full-potential equation with viscous corrections. More recently, Dadone and Grossman presented an adjoint formulation for the Euler equations. In both approaches, a boundary condition is introduced to approximate the effects of the evolving surface shape that results in accurate gradient computation. Central to automated shape optimization algorithms is the issue of geometry modeling and control. The need to optimize complex, "real-life" geometry provides a strong incentive for the use of parametric-CAD systems within the optimization procedure. In previous work, we presented an effective optimization framework that incorporates a direct-CAD interface. In this work, we enhance the capabilities of this framework with efficient gradient computations using the discrete adjoint method. We present details of the adjoint numerical implementation, which reuses the domain decomposition, multigrid, and time-marching schemes of the flow solver. Furthermore, we explain and demonstrate the use of CAD in conjunction with the Cartesian adjoint approach. The final paper will contain a number of complex geometry, industrially relevant examples with many design variables to demonstrate the effectiveness of the adjoint method on Cartesian meshes.

Nemec, Marian↗

An inviscid three-dimensional analysis of the Space Shuttle main engine hot-gas manifold

A numerical study using an inviscid three-dimensional Lagrangian fluid dynamics code has been conducted as a part of an overall effort to understand the flow behavior in the SSME fuel side hot-gas manifold. The model simulates flow from the high-pressure fuel turbine exit through the transfer ducts, including the effects of swirl, inlet flow symmetry, and presence of straightening vanes and struts; a separate, more-detailed effort is in progress that includes viscosity and turbulence effects. The simplified model presented is divided into two parts, the first includes the 180-degree turnaround duct downstream of the turbine exit and the spherical fuel bowl section, while the second models the three transfer ducts. The two parts of the model are coupled together with the interface conditions being updated through iteration. Results indicate that a transverse pressure differential of 165 psi would be imposed on the turbine exit and that unstable flow separation occurs around the vanes, struts, and within the transfer ducts. The three transfer ducts show a mass flux split of approximately 41, 21, and 38 percent. Results to date are encouraging that certain flow characteristics can be usefuly represented using a relatively coarse grid inviscid code.

Liang, P. Y.↗

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

Galaxy bispectrum in the spherical Fourier-Bessel basis

The bispectrum, the three-point correlation in Fourier space, is a crucial statistic for studying many effects targeted by the next-generation galaxy surveys, such as primordial non-Gaussianity (PNG) and general relativistic (GR) effects on large scales. In this work we develop a formalism for the bispectrum in the spherical Fourier-Bessel (SFB) basis—a natural basis for computing correlation functions on the curved sky, as it diagonalizes the Laplacian operator in spherical coordinates. Working in the SFB basis allows for line-of-sight effects such as redshift space distortions and GR to be accounted for exactly, i.e., without having to resort to perturbative expansions to go beyond the plane-parallel approximation. Only analytic results for the SFB bispectrum exist in the literature given the intensive computations needed. We numerically calculate the SFB bispectrum for the first time, enabled by a few techniques: We implement a template decomposition of the redshift-space kernel Z 2 into Legendre polynomials, and separately treat the PNG and velocity-divergence terms. We derive an identity to integrate a product of three spherical harmonics connected by a Dirac delta function as a simple sum and use it to investigate the limit of a homogeneous and isotropic Universe. Furthermore, we present a formalism for convolving the signal with separable window functions and use a toy spherically symmetric window to demonstrate the computation and give insights into the properties of the observed bispectrum signal. While our implementation remains computationally challenging, it is a step toward a feasible full extraction of information on large scales via a SFB bispectrum analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

High Fidelity Simulations of a Methane-Oxygen Rotating Detonation Rocket Engine

The rotating detonation combustor (RDC) is an important realization of pressure gain combustion for practical applications. The RDC system is characterized by a highly unsteady flow field, with multiple reflected pressure waves following the strong detonations and the existence of partially-burnt gases entrained within the detonation annulus during the injector recovery process. While experimental efforts have provided macroscopic properties of an RDC with a given fuel-oxidizer mixture and geometry, limited optical access and reduced lifespan of flow-field diagnostic equipment constrain understanding of the mechanisms that lend to wave stability, controllability, and sustainability. To this end, high-fidelity numerical simulations of the Air Force Research Laboratory (AFRL) methane-oxygen rotating detonation rocket engine (RDRE) are performed to provide detailed insight into the detonation physics and anomalous behavior within the combustor. The results highlight the merit of high-fidelity numerical studies in analyzing the combustion processes and injector dynamics of a complex combustion system. The simulations capture the general wave behavior observed within the experimental studies. Three different operating conditions, with varying global equivalence ratio and system mass flow rate, are considered: (1) baseline configuration, (2) high equivalence ratio, and (3) high mass flow rate. The high mass flow rate case results in increased detonation wave strength whereas the high equivalence ratio results in increased deflagrative heat release. The high equivalence ratio case results in chaotic behavior with two pairs of counter-rotating detonation waves, whereas a single pair of co-rotating waves is observed in the baseline and high mass flow rate cases. Further, parasitic combustion of the reactant mixture ahead of the detonation wave diminishes its strength and reduces propagation speed to approximately 50-60\% of the Chapman-Jouguet (CJ) condition. In this work, a detailed analysis of the detonation wave behavior, injector dynamics, and the statistics of combustion parameters are presented.

Prakash, Supraj↗

Volumetric pattern analysis of fuselage-mounted airborne antennas

A volumetric pattern analysis of fuselage-mounted airborne antennas at high frequencies was investigated. The primary goal of the investigation was to develop a numerical solution for predicting radiation patterns of airborne antennas in an accurate and efficient manner. An analytical study of airborne antenna pattern problems is presented in which the antenna is mounted on the fuselage near the top or bottom. Since this is a study of general-type commercial aircraft, the aircraft was modeled in its most basic form. The fuselage was assumed to be an infinitely long perfectly conducting elliptic cylinder in its cross-section and a composite elliptic cylinder in its elevation profile. The wing, cockpit, stabilizers (horizontal and vertical) and landing gear are modeled by "N" sided bent or flat plates which can be arbitrarily attached to the fuselage. The volumetric solution developed utilizes two elliptic cylinders, namely, the roll plane and elevation plane models to approximate the principal surface profile (longitudinal and transverse) at the antenna location. With the belt concept and the aid of appropriate coordinate system transformations the solution can be used to predict the volumetric patterns of airborne antennas in an accurate and efficient manner. Applications of this solution to various airborne antenna problems show good agreement with scale model measurements. Extensive data are presented for a microwave landing antenna system.

Yu, C. L.↗

Analytic Thermal Model of an Optical Fiber Based Gamma Thermometer and its Application in a University Research Reactor

This paper describes and validates, by comparison with numerical modeling results, an analytical model of thermal transport in an optical fiber based gamma thermometer (OFBGT) that is appropriate for use in university research reactors. The maximum temperature difference between the thermal mass and the outer sheath ( &#x0394;<!-- Δ --> T ) for the OFBGT design that we have considered is approximately 50 &#x2218;<!-- ° --> C , for the OFBGT in the Central Irradiation Facility of the Ohio State University Research Reactor (OSURR) with the reactor operating at full power (450 kW). The maximum value of &#x0394;<!-- Δ --> T that is predicted by the analytic model for the OFBGT design is smaller by approximately 1.1 °C than the value of &#x0394;<!-- Δ --> T which is predicted by the numerical model, for the same OFBGT design, but including all the details of the design. We have used the analytical model of thermal transport in an OFBGT to determine a normalized Modulation Transfer Function M T F &#x2032; ( k ) ) for the OFBGT. We conclude that MTF &#x2032;<!-- ' --> ( k OSU ) > 0.99 , where k OSU is the spatial frequency for the axial dependence of the reactor power distribution in the

47 OTHER INSTRUMENTATION↗

Analysis of X-ray observations of the 15 June 1973 flare in active region NOAA 131

Observations and analyses of the 1B/M3 flare of 15 June, 1973 in active region NOAA 131 (McMath 12379) are presented. The X-ray observations, consisting of broadband photographs and proportional counter data from the Skylab/ATM NASA-MSFC/Aerospace S-056 experiment, are used to infer temperatures, emission measures, and densities for the flaring plasma. The peak temperature from the spatially resolved photographs is 25,000,000 K, while the temperature from the full-disk proportional counter data is approximately 15,000,000 K. The density is 3 times 10 to the 10th/cu cm. The X-ray flare emission appears to come primarily from two low-lying curvilinear features lying perpendicular to and centered on the line where the photospheric longitudinal magnetic field is zero. Similarities in the preflare and postflare X-ray emission patterns indicate that no large-scale relaxation of the coronal magnetic configuration was observed. Also discussed are H-alpha and magnetic field observations of the flare and the active region. Finally, results of numerical calculations, including thermal conduction, radiative loss, and chromospheric evaporation, are in qualitative agreement with the decay phase observations.

Krall, K. R.↗

CFD analysis of jet mixing in low NOx flametube combustors

The Rich-burn/Quick-mix/Lean-burn (RQL) combustor was identified as a potential gas turbine combustor concept to reduce NO(x) emissions in High Speed Civil Transport (HSCT) aircraft. To demonstrate reduced NO(x) levels, cylindrical flametube versions of RQL combustors are being tested at NASA Lewis Research Center. A critical technology needed for the RQL combustor is a method of quickly mixing by-pass combustion air with rich-burn gases. Jet mixing in a cylindrical quick-mix section was numerically analyzed. The quick-mix configuration was five inches in diameter and employed twelve radial-inflow slots. The numerical analyses were performed with an advanced, validated 3-D Computational Fluid Dynamics (CFD) code named REFLEQS. Parametric variation of jet-to-mainstream momentum flux ratio (J) and slot aspect ratio was investigated. Both non-reacting and reacting analyses were performed. Results showed mixing and NO(x) emissions to be highly sensitive to J and slot aspect ratio. Lowest NO(x) emissions occurred when the dilution jet penetrated to approximately mid-radius. The viability of using 3-D CFD analyses for optimizing jet mixing was demonstrated.

Talpallikar, M. V.↗

A Piloted Simulator Evaluation of Transport Aircraft Rudder Pedal Force/Feel Characteristics

A piloted simulation study has been conducted in a fixed-base research simulator to assess the directional handling qualities for various rudder pedal feel characteristics for commercial transport airplanes. That is, the effects of static pedal force at maximum pedal travel, breakout force, and maximum pedal travel on handling qualities were studied. An artificial maneuver with a severe lateral wind shear and requiring runway tracking at an altitude of 50 feet in a crosswind was used to fully exercise the rudder pedals. Twelve active airline pilots voluntarily participated in the study and flew approximately 500 maneuvers. The pilots rated the maneuver performance with various rudder pedal feel characteristics using the Cooper- Harper rating scale. The test matrix had 15 unique combinations of the 3 static pedal feel characteristics. A 10-term, second-order equation for the Cooper-Harper pilot rating as a function of the 3 independent pedal feel parameters was fit to the data. The test matrix utilized a Central Composite Design that is very efficient for fitting an equation of this form. The equation was used to produce contour plots of constant pilot ratings as a function of two of the parameters with the third parameter held constant. These contour plots showed regions of good handling qualities as well as regions of degraded handling qualities. In addition, a numerical equation solver was used to predict the optimum parameter values (those with the lowest pilot rating). Quantitative pilot performance data were also analyzed. This analysis found that the peak values of the cross power spectra of the pedal force and heading angle could be used to quantify the tendency toward directional pilot induced oscillations (PIO). Larger peak values of the cross power spectra were correlated with larger (degraded) Cooper-Harper pilot ratings. Thus, the subjective data (Cooper-Harper pilot ratings) were consistent with the objective data (peak values of the cross power spectra).

Stewart, Eric C.↗