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At least 253 records · Page 14

Improvements to a Response Surface Thermal Model for Orion Mated to the International Space Station

This study is an extension of previous work to evaluate the applicability of Design of Experiments (DOE)/Response Surface Methodology to on-orbit thermal analysis. The goal was to determine if the methodology could produce a Response Surface Equation (RSE) that predicted the thermal model temperature results within +/-10 F. An RSE is a polynomial expression that can then be used to predict temperatures for a defined range of factor combinations. Based on suggestions received from the previous work, this study used a model with simpler geometry, considered polynomials up to fifth order, and evaluated orbital temperature variations to establish a minimum and maximum temperature for each component. A simplified Outer Mold Line (OML) thermal model of the Orion spacecraft was used in this study. The factors chosen were the vehicle's Yaw, Pitch, and Roll (defining the on-orbit attitude), the Beta angle (restricted to positive beta angles from 0 to 75), and the environmental constants (varying from cold to hot). All factors were normalized from their native ranges to a non-dimensional range from -1.0 to 1.0. Twenty-three components from the OML were chosen and the minimum and maximum orbital temperatures were calculated for each to produce forty-six responses for the DOE model. A customized DOE case matrix of 145 analysis cases was developed which used analysis points at the factor corners, mid-points, and center. From this data set, RSE s were developed which consisted of cubic, quartic, and fifth order polynomials. The results presented are for the fifth order RSE. The RSE results were then evaluated for agreement with the analytical model predictions to produce a +/-3(sigma) error band. Forty of the 46 responses had a +/-3(sigma) value of 10 F or less. Encouraged by this initial success, two additional sets of verification cases were selected. One contained 20 cases, the other 50 cases. These cases were evaluated both with the fifth order RSE and with the analytical model. For the maximum temperature predictions, 12 of the 23 components had all predictions within +/-10 F and 17 were within +/-20 F. For the minimum temperature predictions, only 4 of the 23 components (the four radiator temperatures), were within the 10 F goal. The maximum temperature RSEs were then run through 59,049 screening cases. The RSE predictions were then filtered to find 55 cases that produced the hottest temperatures. These 55 cases were then analyzed using the thermal model and the results compared against the RSE predictions. As noted earlier, 12 of the 23 responses were within +/-10 F at 17 within +/-20 F. These results demonstrate that if properly formulated, an RSE can provide a reliable, fast temperature prediction. Despite this progress, additional work is needed to determine why the minimum temperatures responses and 6 of the hot temperature responses did not produce reliable RSEs. Recommend focus areas are the model itself (arithmetic vs. diffusion nodes) and seeking consultations with statistical application experts.

Miller, StephenW.↗

Numerical Modeling of Thermofluid Transients During Chilldown of Cryogenic Transfer Lines

The chilldown of fluid transfer lines is an important part of using cryogenic systems such as those found in both ground and space based applications. The chilldown process is a complex combination of both thermal and fluid transient phenomena. A cryogenic liquid flows through a transfer line that is initially at a much higher temperature than the cryogen. Transient heat transfer processes between the liquid and transfer line cause vaporization of the liquid, and this phase change can cause transient pressure and flow surges in the liquid. As the transfer line is cooled, these effects diminish until the liquid reaches a steady flow condition in the chilled transfer line. If these transient phenomena are not properly accounted for in the design process of a cryogenic system, it can lead to damage or failure of system components during operation. For such cases, analytical modeling is desirable for ensuring that a cryogenic system transfer line design is adequate for handling the effects of a chilldown process. The purpose of this paper is to present the results of a numerical model developed using Generalized Fluid System Simulation Program (GFSSP)'s new fluid transient capability in combination with its previously developed thermal transient capability to predict pressure and flow surge in cryogenic transfer lines during a chilldown process. An experiment performed by the National Bureau of Standards (NBS) in 1966 has been chosen as the baseline comparison case for this work. NBS s experimental set-up consisted of a 10.59 cubic foot supply dewar, an inlet valve, and a 200 foot long, in Outside Diameter (OD) vacuum jacketed copper transfer line that exhausted to atmosphere. Three different inlet valves, an in-port ball valve, a 1-in-port globe valve and a 1-in-port gate valve, were used in NBS's experiments. Experiments were performed using both liquid hydrogen and liquid nitrogen as the fluids. The proposed paper will include detailed comparisons of GFSSP's predictions with NBS's experimental results.

Majumdar, Alok↗

Hybrid scaled structural dynamic models and their use in damping prediction

Analytical and experimental techniques for the prediction and ground verification of the damped structural dynamics of space structures are developed. The options available for similarity-scaled model testing, including replica and multiple scale approaches, are reviewed. For the case when the distortion of potentially dissipative or nonlinear joints, which would be required in multiple-scale modeling, is impractical, a new type of modeling is introduced, which uses a hybrid of joints at replica scale and connecting elements at a modified multiple scale. The model design requirements for replica, multiple-scale, and hybrid models are developed, and the expected scaling of nonlinear dissipation in joints is derived. A damping prediction scheme is developed that relies on a finite element model of the undamped structure and measurements of the individual joint properties to predict the modal damping of the truss attributable to the joints. A hybrid-scaled model of a segment of the Space Station was built and dynamically tested. The predicted and measured truss damping compared favorably.

Crawley, Edward F.↗

Phosphate binding protein as the biorecognition element in a biosensor for phosphate

This work explores the potential use of a member of the periplasmic family of binding proteins, the phosphate binding protein (PBP), as the biorecognition element in a sensing scheme for the detection of inorganic phosphate (Pi). The selectivity of this protein originates from its natural role which, in Escherichia coli, is to serve as the initial receptor for the highly specific translocation of Pi to the cytoplasm. The single polypeptide chain of PBP is folded into two similar domains connected by three short peptide linkages that serve as a hinge. The Pi binding site is located deep within the cleft between the two domains. In the presence of the ligand, the two globular domains engulf the former in a hinge-like manner. The resultant conformational change constitutes the basis of the sensor development. A mutant of PBP (MPBP), where an alanine was replaced by a cysteine residue, was prepared by site-directed mutagenesis using the polymerase chain reaction (PCR). The mutant was expressed, from plasmid pSD501, in the periplasmic space of E. coli and purified in a single chromatographic step on a perfusion anion-exchange column. Site-specific labeling was achieved by attaching the fluorophore, N-[2-(1-maleimidyl)ethyl]-7-(diethylamino)coumarin-3-carboxamide (MDCC), to the protein through the sulfhydryl group of the cysteine moiety. Steady-state fluorescence studies of the MPBP-MDCC conjugate showed a change in the intensity of the signal upon addition of Pi. Calibration curves for Pi were constructed by relating the intensity of the fluorescence signal with the amount of analyte present in the sample. The sensing system was first developed and optimized on a spectrofluorometer using ml volumes of sample. It was then adapted to be used on a microtiter plate arrangement with microliter sample volumes. The system's versatility was finally proven by developing a fiber optic fluorescence-based sensor for monitoring Pi. In all three cases the detection limits for the analyte were in the sub-microMolar range. It was also demonstrated that the sensing system was selective for phosphate over other structurally-similar anions, paving the way for the design and development of a new family of biosensors utilizing the specific binding properties of periplasmic proteins. c2003 Elsevier B.V. All rights reserved.

NASA Program Fundamental Space Biology↗

Tests of a Semi-Analytical Case 1 and Gelbstoff Case 2 SeaWiFS Algorithm with a Global Data Set

A semi-analytical algorithm was tested with a total of 733 points of either unpackaged or packaged-pigment data, with corresponding algorithm parameters for each data type. The 'unpackaged' type consisted of data sets that were generally consistent with the Case 1 CZCS algorithm and other well calibrated data sets. The 'packaged' type consisted of data sets apparently containing somewhat more packaged pigments, requiring modification of the absorption parameters of the model consistent with the CalCOFI study area. This resulted in two equally divided data sets. A more thorough scrutiny of these and other data sets using a semianalytical model requires improved knowledge of the phytoplankton and gelbstoff of the specific environment studied. Since the semi-analytical algorithm is dependent upon 4 spectral channels including the 412 nm channel, while most other algorithms are not, a means of testing data sets for consistency was sought. A numerical filter was developed to classify data sets into the above classes. The filter uses reflectance ratios, which can be determined from space. The sensitivity of such numerical filters to measurement resulting from atmospheric correction and sensor noise errors requires further study. The semi-analytical algorithm performed superbly on each of the data sets after classification, resulting in RMS1 errors of 0.107 and 0.121, respectively, for the unpackaged and packaged data-set classes, with little bias and slopes near 1.0. In combination, the RMS1 performance was 0.114. While these numbers appear rather sterling, one must bear in mind what mis-classification does to the results. Using an average or compromise parameterization on the modified global data set yielded an RMS1 error of 0.171, while using the unpackaged parameterization on the global evaluation data set yielded an RMS1 error of 0.284. So, without classification, the algorithm performs better globally using the average parameters than it does using the unpackaged parameters. Finally, the effects of even more extreme pigment packaging must be examined in order to improve algorithm performance at high latitudes. Note, however, that the North Sea and Mississippi River plume studies contributed data to the packaged and unpackaged classess, respectively, with little effect on algorithm performance. This suggests that gelbstoff-rich Case 2 waters do not seriously degrade performance of the semi-analytical algorithm.

Carder, Kendall L.↗

Progress in the Modeling of NiAl-Based Alloys Using the BFS Method

The BFS method has been applied to the study of NiAl-based materials to assess the effect of alloying additions on structure. Ternary, quaternary and even pent-alloys based on Ni-rich NiAl with additions of Ti, Cr and Cu were studied. Two approaches were used, Monte Carlo simulations to determine ground state structures and analytical calculations of high symmetry configurations which give physical insight into preferred bonding. Site occupancy energetics for ternary and the more complicated case of quaternary additions were determined, and solubility limits and precipitate formation with corresponding information concerning structure and lattice parameter were also 'observed' computationally. The method was also applied to determine the composition of alloy surfaces and interfaces. Overall, the results demonstrate that the BFS method for alloys is a powerful tool for alloy design and with its simplicity and obvious advantages can be used to complement any experimental alloy design program.

Bozzolo, Guillermo↗

The Quantum Approximation Optimization Algorithm for MaxCut: A Fermionic View

Farhi et al. recently proposed a class of quantum algorithms, the Quantum Approximate Optimization Algorithm (QAOA), for approximately solving combinatorial optimization problems. A level-p QAOA circuit consists of steps in which a classical Hamiltonian, derived from the cost function, is applied followed by a mixing Hamiltonian. The 2p times for which these two Hamiltonians are applied are the parameters of the algorithm. As p increases, however, the parameter search space grows quickly. The success of the QAOA approach will depend, in part, on finding effective parameter-setting strategies. Here, we analytically and numerically study parameter setting for QAOA applied to MAXCUT. For level-1 QAOA, we derive an analytical expression for a general graph. In principle, expressions for higher p could be derived, but the number of terms quickly becomes prohibitive. For a special case of MAXCUT, the Ring of Disagrees, or the 1D antiferromagnetic ring, we provide an analysis for arbitrarily high level. Using a Fermionic representation, the evolution of the system under QAOA translates into quantum optimal control of an ensemble of independent spins. This treatment enables us to obtain analytical expressions for the performance of QAOA for any p. It also greatly simplifies numerical search for the optimal values of the parameters. By exploring symmetries, we identify a lower-dimensional sub-manifold of interest; the search effort can be accordingly reduced. This analysis also explains an observed symmetry in the optimal parameter values. Further, we numerically investigate the parameter landscape and show that it is a simple one in the sense of having no local optima.

quantum algorithm↗

Superexponential primordial black hole production via delayed vacuum decay

If a cosmological first-order phase transition occurs sufficiently slowly, delayed vacuum decay may lead to the formation of primordial black holes. Here we consider a simple model as a case study of how the abundance of the produced black holes depends on the model’s input parameters. We demonstrate, using both numerical and analytical arguments and methods, that the black hole abundance is controlled by a double, “super”-exponential dependence on the three-dimensional Euclidean action over temperature at its minimal value. We show that a modified expansion rate during the phase transition, such as one driven by an additional energy density component, leads to a weaker dependence on the underlying model parameters, but maintains the same superexponential structure. We argue that our findings generalize to any framework of black hole production via delayed vacuum decay. Published by the American Physical Society 2025

Wu, Yanda (ORCID:000000034487305X)↗

Some observations on the Houbolt-Rainey and peak-hold methods of flutter onset prediction

A subcritical response method for flutter onset prediction developed by Houbolt and Rainey in 1958 is compared with the Peak-Hold Method which was apparently first applied to flutter onset prediction by Sandford, Abel, and Gray in the early 1970's. The rational argument presented shows that the two methods are not different, but are actually the same. So, because there is an analytical foundation for the Houbolt-Rainey Method, then there is the same analytical foundation for the Peak-Hold Method. Further, it is suggested that, in applying Peak-Hold Method in cases where turbulence is used as the excitation force, the variation of the reciprocal of the response amplitude with the reciprocal of the dynamic pressure to be used to extrapolate to flutter onset rather than the variation with dynamic pressure which is the current practice because the linear trend which is predicted to occur for the former is easier to extrapolate to the flutter condition than the nonlinear trend predicted to occur for the latter.

Doggett, Robert V., Jr.↗

NCAR Johns Hopkins/CDC Climate and Health Summer Institute

The interactions between climate and health are rife with complexity and present many conceptual and methodological challenges. Possible effects of climate change on health are considered some of the most sensitive impacts of climate change and are a high priority for policy-makers and the public. As a first step toward improving tlit: quality of research, we developed a Climate and Health Workshop (Institute), geared toward teaching students various aspects of how to conduct integrated climate and health research. At the workshop scientists presented selected case studies of climate and health (e.g., heat mortality, vector-borne diseases), thus demonstrating a subset of key analytical tools and databases most useful to researchers in this field. Key research gaps in this research area were discussed. In this six-day Institute (21-28 July 2004, Boulder, Colorado), health scientists and students benefited from lectures and hands-on tools taught by top NCAR scientists. The attendees learned about health databases and epidemiologic methods from leading health scientists from CDC, Johns Hopkins, and other institutions from around the globe.

Mearns, Linda O.↗

Mathematical Modeling of Electrodynamics Near the Surface of Earth and Planetary Water Worlds

An interesting feature of planetary bodies with hydrospheres is the presence of an electrically conducting shell near the global surface. This conducting shell may typically lie between relatively insulating rock, ice, or atmosphere, creating a strong constraint on the flow of large-scale electric currents. All or parts of the shell may be in fluid motion relative to main components of the rotating planetary magnetic field (as well as the magnetic fields due to external bodies), creating motionally-induced electric currents that would not otherwise be present. As such, one may expect distinguishing features in the types of electrodynamic processes that occur, as well as an opportunity for imposing specialized mathematical methods that efficiently address this class of application. The purpose of this paper is to present and discuss such specialized methods. Specifically, thin-shell approximations for both the electrodynamics and fluid dynamics are combined to derive simplified mathematical formulations describing the behavior of these electric currents as well as their associated electric and magnetic fields. These simplified formulae allow analytical solutions featuring distinct aspects of the thin-shell electrodynamics in idealized cases. A highly efficient numerical method is also presented that is useful for calculations under inhomogeneous parameter distributions. Finally, the advantages as well as limitations in using this mathematical approach are evaluated. This evaluation is presented primarily for the generic case of bodies with water worlds or other thin spherical conducting shells. More specific discussion is given for the case of Earth, but also Europa and other satellites with suspected oceans.

Tyler, Robert H.↗

Assessing Carbon Properties in Coastal Waters with a New Observing System Testbed

Large rainfall events over land can lead to a substantial flux of carbon and nutrients to estuaries and the coastal ocean. In the mid-Atlantic on the east coast of North America (35° - 42° N), these events often happen due to tropical storm activity as well as less predictable anomalously large midlatitude storms or abrupt spring snow melt runoff. Storms can directly impact the coastal carbon cycle via export of carbon from land to sea, while also stimulating phytoplankton production due to the influx of nutrients to the coastal ocean. To assess the impact of high precipitation and river flow events on the coastal carbon cycle, we have integrated multiple observing platforms in an analytical framework to dynamically observe carbon-related properties. The new observing system testbed (NOS-T) allows for an estimate of phytoplankton and organic carbon stocks in the surface ocean, with a goal of providing near real time analytical capability. A case study of high river discharge in the mid-Atlantic in the summer and fall of 2018 and 2021 were used to examine how riverine carbon manifests along the land-estuary-ocean continuum particularly in Chesapeake Bay. Chesapeake Bay was chosen as the study site because of long term monitoring by the Chesapeake Bay Program and a robust and well-developed regional biogeochemical modeling system, the Chesapeake Bay Environmental Forecast System (CBEFS), that is publicly available. There is also new capability in Chesapeake Bay to combine hyperspectral radiometric data from the Aerosol Robotic Network site that is online in 2022 with in-water observations of optical properties. Precipitation data from the Global Precipitation Measurement IMERG data set was used to establish triggering criteria for storm carbon flux observation. USGS and in-water carbon data were used to establish statistical models to estimate the mass flux of organic carbon into Chesapeake Bay using measured river discharge. The year 2018 was examined as there was record rainfall and near record river flow in the late summer. The CBEFS modeling was compared with in-water estimates of dissolved organic carbon (DOC) to assess the model’s ability to capture storm fluxes of carbon to the ecosystem. Multiple satellite platforms were also used to assess how remote sensing using passive Earth orbiting sensors can be used to observe carbon in this complex coastal region. A set of recommendations have been established to improve sensing capability to measure aquatic carbon during storm events. A unique challenge in these dynamic inland waters is how rapidly carbon fluxes can evolve in space and time, with many sources contributing to the water leaving reflectance that satellites can observe. To improve our ability to quantify carbon stocks and fluxes in near real time, a suite of satellite sensors and high-resolution modeling capability is needed, all supplemented by in situ monitoring. Future inclusion of in-water observations that would be deployed when the system reaches triggering criteria, as well as taskable orbital instruments, will improve estimates of ocean carbon properties and provide the ability to calculate major carbon stocks and fluxes in near real time following episodic storm events.

land-ocean continuum↗

CFD Simulation of Liquid Rocket Engine Injectors

Detailed design issues associated with liquid rocket engine injectors and combustion chamber operation require CFD methodology which simulates highly three-dimensional, turbulent, vaporizing, and combusting flows. The primary utility of such simulations involves predicting multi-dimensional effects caused by specific injector configurations. SECA, Inc. and Engineering Sciences, Inc. have been developing appropriate computational methodology for NASA/MSFC for the past decade. CFD tools and computers have improved dramatically during this time period; however, the physical submodels used in these analyses must still remain relatively simple in order to produce useful results. Simulations of clustered coaxial and impinger injector elements for hydrogen and hydrocarbon fuels, which account for real fluid properties, is the immediate goal of this research. The spray combustion codes are based on the FDNS CFD code' and are structured to represent homogeneous and heterogeneous spray combustion. The homogeneous spray model treats the flow as a continuum of multi-phase, multicomponent fluids which move without thermal or velocity lags between the phases. Two heterogeneous models were developed: (1) a volume-of-fluid (VOF) model which represents the liquid core of coaxial or impinger jets and their atomization and vaporization, and (2) a Blob model which represents the injected streams as a cloud of droplets the size of the injector orifice which subsequently exhibit particle interaction, vaporization, and combustion. All of these spray models are computationally intensive, but this is unavoidable to accurately account for the complex physics and combustion which is to be predicted, Work is currently in progress to parallelize these codes to improve their computational efficiency. These spray combustion codes were used to simulate the three test cases which are the subject of the 2nd International Workshop on-Rocket Combustion Modeling. Such test cases are considered by these investigators to be very valuable for code validation because combustion kinetics, turbulence models and atomization models based on low pressure experiments of hydrogen air combustion do not adequately verify analytical or CFD submodels which are necessary to simulate rocket engine combustion. We wish to emphasize that the simulations which we prepared for this meeting are meant to test the accuracy of the approximations used in our general purpose spray combustion models, rather than represent a definitive analysis of each of the experiments which were conducted. Our goal is to accurately predict local temperatures and mixture ratios in rocket engines; hence predicting individual experiments is used only for code validation. To replace the conventional JANNAF standard axisymmetric finite-rate (TDK) computer code 2 for performance prediction with CFD cases, such codes must posses two features. Firstly, they must be as easy to use and of comparable run times for conventional performance predictions. Secondly, they must provide more detailed predictions of the flowfields near the injector face. Specifically, they must accurately predict the convective mixing of injected liquid propellants in terms of the injector element configurations.

Farmer, Richard↗

Analytic Shielding Optimization to Reduce Crew Exposure to Ionizing Radiation Inside Space Vehicles

A sustainable lunar architecture provides capabilities for leveraging out-of-service components for alternate uses. Discarded architecture elements may be used to provide ionizing radiation shielding to the crew habitat in case of a Solar Particle Event. The specific location relative to the vehicle where the additional shielding mass is placed, as corroborated with particularities of the vehicle design, has a large influence on protection gain. This effect is caused by the exponential- like decrease of radiation exposure with shielding mass thickness, which in turn determines that the most benefit from a given amount of shielding mass is obtained by placing it so that it preferentially augments protection in under-shielded areas of the vehicle exposed to the radiation environment. A novel analytic technique to derive an optimal shielding configuration was developed by Lockheed Martin during Design Analysis Cycle 3 (DAC-3) of the Orion Crew Exploration Vehicle (CEV). [1] Based on a detailed Computer Aided Design (CAD) model of the vehicle including a specific crew positioning scenario, a set of under-shielded vehicle regions can be identified as candidates for placement of additional shielding. Analytic tools are available to allow capturing an idealized supplemental shielding distribution in the CAD environment, which in turn is used as a reference for deriving a realistic shielding configuration from available vehicle components. While the analysis referenced in this communication applies particularly to the Orion vehicle, the general method can be applied to a large range of space exploration vehicles, including but not limited to lunar and Mars architecture components. In addition, the method can be immediately applied for optimization of radiation shielding provided to sensitive electronic components.

Gaza, Razvan↗

Calculation of sensitivity derivatives in thermal problems by finite differences

The optimum design of a structure subject to temperature constraints is considered. When mathematical optimization techniques are used, derivatives of the temperature constraints with respect to the design variables are usually required. In the case of large aerospace structures, such as the Space Shuttle, the computation of these derivatives can become prohibitively expensive. Analytical methods and a finite difference approach have been considered in studies conducted to improve the efficiency of the calculation of the derivatives. The present investigation explores two possibilities for enhancing the effectiveness of the finite difference approach. One procedure involves the simultaneous solution of temperatures and derivatives. The second procedure makes use of the optimum selection of the magnitude of the perturbations of the design variables to achieve maximum accuracy.

Haftka, R. T.↗

Analytical and Numerical Results for an Adhesively Bonded Joint Subjected to Pure Bending

A one-dimensional, semi-analytical methodology that was previously developed for evaluating adhesively bonded joints composed of anisotropic adherends and adhesives that exhibit inelastic material behavior is further verified in the present paper. A summary of the first-order differential equations and applied joint loading used to determine the adhesive response from the methodology are also presented. The method was previously verified against a variety of single-lap joint configurations from the literature that subjected the joints to cases of axial tension and pure bending. Using the same joint configuration and applied bending load presented in a study by Yang, the finite element analysis software ABAQUS was used to further verify the semi-analytical method. Linear static ABAQUS results are presented for two models, one with a coarse and one with a fine element meshing, that were used to verify convergence of the finite element analyses. Close agreement between the finite element results and the semi-analytical methodology were determined for both the shear and normal stress responses of the adhesive bondline. Thus, the semi-analytical methodology was successfully verified using the ABAQUS finite element software and a single-lap joint configuration subjected to pure bending.

Smeltzer, Stanley S., III↗

A Finite Element Method for Compressible and Turbulent Multiphase Flow Instabilities with Heat Transfer

We present a new finite element framework for modeling compressible, turbulent multiphase flows with heat transfer. For two-fluid systems with a free surface, the Volume of Fluid (VOF) method is implemented without the need for interface reconstruction, while turbulence is resolved using a dynamic Vreman large eddy simulation (LES) model. Unlike most two-phase VOF studies, which neglect heat transfer, the present approach incorporates energy transport equations within the VOF formulation to account for heat exchange, an effect particularly important in turbulent flows. Conjugate heat transfer is often challenging in finite volume methods, which require explicit specification of heat fluxes at the solid–fluid interface, limiting accuracy and predictive capability. By contrast, the finite element formulation does not require heat flux inputs, allowing more accurate and robust simulation of heat transfer between solids and fluids. The method is demonstrated through three representative cases. First, a two-fluid instability with a single-mode perturbation is simulated and validated against analytical growth rates. Second, conjugate heat transfer is examined in a high-temperature flow over a cold metal cylinder, with validation performed both quantitatively—via pressure coefficient comparisons with experimental data—and qualitatively using vector field topology. Finally, compressible spray injection and breakup are modeled, demonstrating the ability of the framework to capture interfacial dynamics and atomization under turbulent, high-speed conditions. In the compressible spray injection and breakup case, the results indicate that the finite element formulation achieved higher predictive accuracy and robustness than the finite-volume method. With the same mesh resolution, the FEM reduced the root mean square error (RMSE) and mean absolute percentage error (MAPE) from 6.96 mm and 26.0% (for the FVM) to 4.85 mm and 12.7%, respectively, demonstrating improved accuracy and robustness in capturing interfacial dynamics and heat transfer. The study also introduced vector field topology to visualize and interpret coherent flow structures and instabilities, offering insights beyond conventional scalar-field analyses.

97 MATHEMATICS AND COMPUTING↗

Blade loss transient dynamics analysis, volume 1. Task 1: Survey and perspective

An analytical technique was developed to predict the behavior of a rotor system subjected to sudden unbalance. The technique is implemented in the Turbine Engine Transient Rotor Analysis (TETRA) computer program using the component element method. The analysis was particularly aimed toward blade-loss phenomena in gas turbine engines. A dual-rotor, casing, and pylon structure can be modeled by the computer program. Blade tip rubs, Coriolis forces, and mechanical clearances are included. The analytical system was verified by modeling and simulating actual test conditions for a rig test as well as a full-engine, blade-release demonstration.

Gallardo, V. C.↗