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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.

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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Effect of High Temperature Storage on AC Characteristics of Polymer Tantalum Capacitors

Replacement of MnO2 with conductive polymers as cathode materials in chip tantalum capacitors allows for a substantial reduction of the equivalent series resistance (ESR), improvement of frequency characteristics, and elimination of the possibility of ignition during failures. One of the drawbacks of chip polymer tantalum capacitors (CPTCs) is a relatively poor long-term stability at high temperatures. In this work, variations of capacitance, dissipation factor, and ESR in different types of capacitors including automotive grade parts from three manufacturers have been monitored during storage at temperatures from 100 ºC to 175 ºC for up to 18,000 hours. Results show that ESR is the most and capacitance the least sensitive to degradation parameter. Times to parametric failures have been simulated using a Weibull-Arrhenius model that allowed for assessments of activation energies of the degradation and prediction of times to failure at the use temperature. Degradation of CPTCs was explained by thermo-oxidative processes in conductive polymers that result in exponential increasing of the resistivity with time of ageing. This process starts after a certain incubation period that depends on packaging materials and design and corresponds to the time that is necessary to form delamination between the encapsulating molding compound and lead frame. The effectiveness of the existing qualification procedures to assure stable operation of CPTCs is discussed.

Aging↗
NASA NTRSDate not supplied

Effect of High Temperature Storage on AC Characteristics of Polymer Tantalum Capacitors

Replacement of MnO2 with conductive polymers as cathode materials in chip tantalum capacitors allows for a substantial reduction of the equivalent series resistance (ESR), improvement of frequency characteristics, and elimination of the possibility of ignition during failures. One of the drawbacks of chip polymer tantalum capacitors (CPTCs) is a relatively poor long-term stability at high temperatures. In this work, variations of capacitance, dissipation factor, and ESR in different types of capacitors including automotive grade parts from three manufacturers have been monitored during storage at temperatures from 100 ºC to 175 ºC for up to 18,000 hours. Results show that ESR is the most and capacitance the least sensitive to degradation parameter. Times to parametric failures have been simulated using a Weibull-Arrhenius model that allowed for assessments of activation energies of the degradation and prediction of times to failure at the use temperature. Degradation of CPTCs was explained by thermo-oxidative processes in conductive polymers that result in exponential increasing of the resistivity with time of ageing. This process starts after a certain incubation period that depends on packaging materials and design and corresponds to the time that is necessary to form delamination between the encapsulating molding compound and lead frame. The effectiveness of the existing qualification procedures to assure stable operation of CPTCs is discussed.

Aging↗
NASA NTRS2021

Effect of High Temperature Storage on AC Characteristics of Polymer Tantalum Capacitors

Replacement of MnO2 with conductive polymers as cathode materials in chip tantalum capacitors allows for a substantial reduction of the equivalent series resistance (ESR), improvement of frequency characteristics, and elimination of the possibility of ignition during failures. One of the drawbacks of chip polymer tantalum capacitors (CPTCs) is a relatively poor long-term stability at high temperatures. In this work, variations of capacitance, dissipation factor, and ESR in different types of capacitors including automotive grade parts from three manufacturers have been monitored during storage at temperatures from 100 ºC to 175 ºC for up to 18,000 hours. Results show that ESR is the most and capacitance the least sensitive parameter to degradation. Times to parametric failures have been simulated using a Weibull-Arrhenius model that allowed for assessments of activation energies of the degradation and prediction of times to failure at the use temperature. Degradation of CPTCs was explained by thermo-oxidative processes in conductive polymers that result in exponential increase of the resistivity with time of aging. This process starts after a certain incubation period that depends on packaging materials and design and corresponds to the time that is necessary to form delamination between the encapsulating molding compound and lead frame. The effectiveness of the existing qualification procedures to assure stable operation of CPTCs is discussed.

high temperature storage (HTS)↗
NASA NTRSDate not supplied

Reinforcement Learning for Spacecraft Navigation & Environment Characterization in the Planar-Restricted Two-Body Problem

As science, exploration, and commercial space missions become increasingly complex, so does the need for efficient, autonomous, and integrated spacecraft navigation and operations techniques. Key operational functions, including data collection and transmission, environment characterization, systems constraints, human factors, and navigation, often are intertwined and conflicted. Deep Reinforcement Learning (DRL) offers a framework for addressing integrated spacecraft navigation and planning in an uncertain dynamical environment. The goal of this study is to evaluate the utility of DRL for integrated spacecraft navigation and planning. This is achieved by developing a simple environmental characterization training environment in the Planar-Restricted 2-Body Problem (PR2BP), establishing benchmarks and heuristic baselines, and designing a previously unstudied Markov Decision Process (MDP) formulation. This MDP formulation enables the spacecraft DRL agents to appropriately balance navigation and actuation capabilities. The resulting DRL-derived policy exceeds a random or untrained policy and meets or exceeds the level of performance of a heuristic without actuation. In the process, valuable intuition is gained about the problem with insight into how DRL methods could scale to increasingly more realistic scenarios, including net-work design and training architectures, efficient state space representations, and methods for encouraging exploration in a parametric action space, among others.

navigation↗
DOE OSTI2024

Parametric optimization of the liquid sampling-atmospheric pressure glow discharge ionization source coupled to an Orbitrap mass spectrometer for neodymium isotope ratio determinations

Isotope ratio determinations are a valuable tool in several application areas. In nuclear forensics, the isotope ratios of uranium and plutonium are commonly used as a signature for the nuclear material's provenance and processing history. However, signatures from other coexisting elements, such as neodymium and samarium, can offer additional insights. Here, the liquid sampling-atmospheric pressure glow discharge (LS-APGD) ionization source coupled to an Orbitrap mass spectrometer (MS) has demonstrated its utility for actinide measurements. This instrumental platform can leverage the high resolution offered by the Orbitrap MS to overcome potential isobaric interferences, such as 144 Nd- 144 Sm, 148 Nd- 148 Sm, and 150 Nd- 150 Sm pairs. The work presented herein demonstrates the rapid, accurate, and precise determination of the isotope ratios for neodymium using the LS-APGD/Orbitrap MS. Both the LS-APGD and Orbitrap MS parameters were optimized systematically, with NdO + found to be the most abundant, most reduced species after applying the optimal collision-induced dissociation modalities. A limit of detection of 3 pg of 142 Nd was achieved when data was acquired and processed using the FTMS Booster, an external data acquisition and processing system offered by Spectroswiss. Excellent accuracy of better than 99 % and precision of <1 % RSD were achieved when a solution of the well-characterized neodymium standard (JNdi-1 standard) was analyzed under the optimized condition, indicating the LS-APGD/Orbitrap's great potential for isotope ratio analysis of Nd and other REEs for diverse applications.

47 OTHER INSTRUMENTATION↗
NASA NTRS1988

On-orbit parametric identification methodology

On-orbit system identification (ID) of large space systems is essential for various reasons. For example, the complex composite structure of such systems cannot be ground-tested; their structural dynamic characteristics must be known accurately in order to accomplish active control. Furthermore, such capability can be used to characterize/identify various disturbances. The identification process is consisted of four principal elements: (1) modeling, (2) the estimation algorithm, (3) input system, and (4) measurement system. These elements are highly correlated and all togerher determine the success of the identification problem. Accurate modeling of large space systems is the most important element of the identification process. Large flexible structures are non-linear and infinite dimensional systems with highly coupled parameters and low frequency packed modes. In addition, these systems are subject to stochastic and time-varying disturbances, they have structural parameters which can vary due to on-orbit assembly deployment, and operations. These systems are generally; however, represented by constant coefficient, finite order differential equations. The non-linearities, coupling and noise effects are also often neglected. Moreover, identification experiment designs which lead to highly complex optimization problems usually require the simultaneous choice of ID algorithm, sensor, and actuator type and placement. On-orbit bandwidth and power restrictions on excitation, limited data window, and restrictions on sensor/actuator type, placement and number, has led to practical questions of implementations.

Hadaegh, Fred Y.↗
DOE OSTI2024

Machine Learning Accelerated First-Principles Study of the Hydrodeoxygenation of Propanoic Acid

The complex reaction network of catalytic biomass conversions often involves hundreds of surface intermediates and thousands of reaction steps, greatly hindering the rational design of metal catalysts for these conversions. Here, we present a framework of machine learning (ML)-accelerated first-principles studies for the hydrodeoxygenation (HDO) of propanoic acid over transition metal surfaces. The microkinetic model (MKM) is initially parametrized by ML-predicted energies and iteratively improved by identifying the rate-determining species and steps (RDS), computing their energies by density functional theory (DFT), and reparameterizing the MKM until all the RDS are computed by DFT. The Gaussian process (GP) model performs significantly better than the linear ridge regression model for predicting both the adsorption free energies and transition state free energies. Parameterized with energies from the GP model, only 5–20% of the full reaction network has to be computed by DFT for the MKM to possess DFT-level accuracy for the TOF and dominant reaction pathway. While the linear ridge regression model performs worse than the GP model, its performance is greatly improved when only transition states are predicted by the regression model and adsorption energies are computed by DFT. Overall, we find that a high accuracy in adsorption free energies is more important for a reliable MKM than a high accuracy in TS free energies. Lastly, based on the GP model with GOH and GCHCHCO as catalyst descriptors, we build two-dimensional volcano plots in activity and selectivity that can help design promising alloy catalysts for HDO reactions of organic acids.

adsorption↗
DOE OSTI2022

Active learning of reactive Bayesian force fields applied to heterogeneous catalysis dynamics of H/Pt

Abstract Atomistic modeling of chemically reactive systems has so far relied on either expensive ab initio methods or bond-order force fields requiring arduous parametrization. Here, we describe a Bayesian active learning framework for autonomous “on-the-fly” training of fast and accurate reactive many-body force fields during molecular dynamics simulations. At each time-step, predictive uncertainties of a sparse Gaussian process are evaluated to automatically determine whether additional ab initio training data are needed. We introduce a general method for mapping trained kernel models onto equivalent polynomial models whose prediction cost is much lower and independent of the training set size. As a demonstration, we perform direct two-phase simulations of heterogeneous H 2 turnover on the Pt(111) catalyst surface at chemical accuracy. The model trains itself in three days and performs at twice the speed of a ReaxFF model, while maintaining much higher fidelity to DFT and excellent agreement with experiment.

42 ENGINEERING↗
DOE OSTI2021

Dispersion-engineered χ(2) nanophotonics: a flexible tool for nonclassical light

Abstract This article reviews recent progress in quasi-phasematched χ ( 2 ) nonlinear nanophotonics, with a particular focus on dispersion-engineered nonlinear interactions. Throughout this article, we establish design rules for the bandwidth and interaction lengths of various nonlinear processes, and provide examples for how these processes can be engineered in nanophotonic devices. In particular, we apply these rules towards the design of sources of non-classical light and show that dispersion-engineered devices can outperform their conventional counterparts. Examples include ultra-broadband optical parametric amplification as a resource for measurement-based quantum computation, dispersion-engineered spontaneous parametric downconversion as a source of separable biphotons, and synchronously pumped nonlinear resonators as a potential route towards single-photon nonlinearities.

Jankowski, Marc (ORCID:0000000318457415)↗
DOE OSTI2022

Development of Carbon Molecular Sieves Hollow Fiber Membranes based on Polybenzimidazole Doped with Polyprotic Acids with Superior H 2 /CO 2 Separation Properties (Final Report)

The goal of this project was to develop a highly efficient membrane-based process to capture CO 2 from coal-derived syngas with 95% CO 2 purity, achieving the cost of electricity (COE) 30% below the baseline capture approaches (i.e., Selexol process) when coupled with the advancement in other areas of the power generation facility. Our core approach is based on high-permeance hollow fiber membranes (HFMs) with superior H 2 /CO 2 separation properties at the syngas process conditions, which can then be further utilized to design membrane reactors for process intensification of H 2 production and purification and CO 2 capture. Three organizations with complementary skills collaborated to achieve the goal, including the University at Buffalo (UB), Los Alamos National Laboratory (LANL), and Trimeric Corporation (Trimeric). We formulated logical steps to bring the membrane technology from Technology Readiness Level (TRL) 3 (Experimental proof of concept) to TRL 4 (Laboratory scale validation in relevant environment). During the budget period (BP) 1, we screened various polymeric materials and identified polybenzimidazole doped with inorganic polyprotic acids as the desirable platform. The acid doping increases the H 2 /CO 2 selectivity, and the sequential carbonization increases H 2 permeability while retaining the high selectivity. By manipulating the acid type and doping level and the carbonization temperature, we demonstrated advanced carbon molecular sieving (CMS) materials with H 2 permeability of above 200 Barrer (1 Barrer = 10 -10 cm 3 (STP) cm cm -2 s -2 cmHg -1 ) and H 2 /CO 2 selectivity of above 40 at 200-300°C with simulated syngas containing CO and water vapor. For example, the PBI-(H 3 PO 4 ) 0.11 carbonized at 700 °C exhibits H 2 permeability of 200 Barrer and H 2 /CO 2 selectivity of 60 at 200 °C, and H 2 permeability of 240 Barrer and H 2 /CO 2 selectivity of 54 at 225 °C, which meets the targeted properties and surpasses Robeson’s upper bound. During the BP2, we focused on the conversion of the advanced CMS materials to stable HFMs. Membranes with H 2 permeance of 1,090 GPU (1 GPU = 10 -6 cm 3 (STP) cm -2 s -2 cmHg -1 ) and H 2 /CO 2 selectivity of 57 at 300 °C were successfully fabricated. The effects of temperature, gas compositions, pressure, and time on the separation properties were systematically investigated. Pencil modules were continuously evaluated for 219 h (dry pure gas) and 669 h (dry simulated syngas) and showed initial decline in permeance and increased H 2 /CO 2 selectivity over time, ultimately achieving a steady state stable value, indicating that the ageing phenomena in the nanoporous structures of the membranes during the test. Membrane reactors were fabricated based on the CMS membranes and evaluated for water-gas shift (WGS) reaction. The use of membranes slightly improves the conversion of the CO. However, parametric tests of the membrane reactors at various temperatures and flow rates need to be conducted, as well as the membranes with improved separation performance. We performed a sensitivity analysis on the impact of H 2 /CO 2 selectivity on the COE based on a hybrid process of a membrane unit and cryogenic unit developed by Membrane Technology and Research, Inc. (MTR). Three H 2 /CO 2 selectivity (40, 60, and 15) cases were developed and compared with the baseline capture process (Case B5B) provided by the DOE report. Increasing the membrane H 2 /CO 2 selectivity reduces COE, but the rate of the decrease of COE also diminishes. The COE values for H 2 /CO 2 selectivities of 40 and 60 were nearly the same. As the H 2 /CO 2 selectivity increases, the inert recycling decreases, leading to smaller equipment, less auxiliary power requirements, and less heating, cooling, and refrigeration duty. The refrigeration system used to liquefy the CO 2 is the most expensive piece of equipment and consumes the most electricity within the CO 2 capture process. Increasing the CO 2 concentration in the recycle stream would improve the economics of the process by reducing the refrigeration duty requirement of the unit and also allow for higher liquefaction temperatures. The high H 2 -selective membrane developed by our team may be applicable in other separation processes where lower pressure H 2 retains value. Typically, hydrogen retains its pressure when it is separated from syngas components. Residual components may be used as low-quality fuel and then vented to the atmosphere. Applications might include control of H 2 /CO ratios or mitigation of the water gas shift reaction by CO 2 recycling to the feed of a gasifier or steam methane reformer. To summarize, we have developed industrial HFMs with the best H 2 /CO 2 separation performance reported in the literature. The membranes demonstrate stability with simulated syngas and show great potential for membrane reactors for WGS reactions, lowering the cost of blue H 2 production.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2023

Toward Quantum Chemical Free Energy Simulations of Platinum Nanoparticles on Titania Support

Platinum nanoparticles (Pt-NPs) supported on titania surfaces are costly but indispensable heterogeneous catalysts because of their highly effective and selective catalytic properties. Therefore, it is vital to understand their physicochemical processes during catalysis to optimize their use and to further develop better catalysts. However, simulating these dynamic processes is challenging due to the need for a reliable quantum chemical method to describe chemical bond breaking and bond formation during the processes but, at the same time, fast enough to sample a large number of configurations required to compute the corresponding free energy surfaces. Density functional theory (DFT) is often used to explore Pt-NPs; nonetheless, it is usually limited to some minimum-energy reaction pathways on static potential energy surfaces because of its high computational cost. In this work, we report a combination of the density functional tight binding (DFTB) method as a fast but reliable approximation to DFT, the steered molecular dynamics (SMD) technique, and the Jarzynski equality to construct free energy surfaces of the temperature-dependent diffusion and growth of platinum particles on a titania surface. In particular, we present the parametrization for Pt-X (X = Pt, Ti, or O) interactions in the framework of the second-order DFTB method, using a previous parametrization for titania as a basis. The optimized parameter set was used to simulate the surface diffusion of a single platinum atom (Pt 1 ) and the growth of Pt 6 from Pt 5 and Pt 1 on the rutile (110) surface at three different temperatures (T = 400, 600, 800 K). The free energy profile was constructed by using over a hundred SMD trajectories for each process. We found that increasing the temperature has a minimal effect on the formation free energy; nevertheless, it significantly reduces the free energy barrier of Pt atom migration on the TiO 2 surface and the transition state (TS) of its deposition. In a concluding remark, the methodology opens the pathway to quantum chemical free energy simulations of Pt-NPs’ temperature-dependent growth and other transformation processes on the titania support.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

DNA-assembled superconducting 3D nanoscale architectures

Studies of nanoscale superconducting structures have revealed various physical phenomena and led to the development of a wide range of applications. Most of these studies concentrated on one- and two-dimensional structures due to the lack of approaches for creation of fully engineered three-dimensional (3D) nanostructures. Here, we present a ‘bottom-up’ method to create 3D superconducting nanostructures with prescribed multiscale organization using DNA-based self-assembly methods. We assemble 3D DNA superlattices from octahedral DNA frames with incorporated nanoparticles, through connecting frames at their vertices, which result in cubic superlattices with a 48 nm unit cell. The superconductive superlattice is formed by converting a DNA superlattice first into highly-structured 3D silica scaffold, to turn it from a soft and liquid-environment dependent macromolecular construction into a solid structure, following by its coating with superconducting niobium (Nb). Through low-temperature electrical characterization we demonstrate that this process creates 3D arrays of Josephson junctions. This approach may be utilized in development of a variety of applications such as 3D Superconducting Quantum interference Devices (SQUIDs) for measurement of the magnetic field vector, highly sensitive Superconducting Quantum Interference Filters (SQIFs), and parametric amplifiers for quantum information systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2026

Theory of quasiparticle generation by microwave drives in superconducting qubits

Microwave drives play a central role in the control of superconducting quantum circuits, enabling qubit gates, readout, and parametric interactions. As the drive frequencies are typically an order of magnitude smaller than (twice) the superconducting gap, it is generally assumed that such drives do not disturb the BCS ground state. However, sufficiently strong drives can activate multiphoton pair-breaking processes that generate quasiparticles (QPs) and result in qubit errors. In this work, we present a theoretical framework for calculating the rates of multiphoton-assisted pair-breaking transitions induced by charge- or flux-coupled microwave drives. Through illustrative examples, we show that photon-assisted QP generation may affect novel high-frequency dispersive readout architectures, as well as Floquet-engineered superconducting circuits operating under strong driving.

circuit quantum electrodynamics↗
DOE OSTI2021

Validation and Demonstration of Control System Functional Capabilities within the IES Plug-and-Play Simulation Environment

The concept of an integrated energy system (IES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework is used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES. The new RAVEN plugin for grid and capacity optimization (HERON) only addresses the limits that affect the production variables and the corresponding rates of variation (explicit constraints). However, other variables are subject to constraints, and the associated limits should be accounted for (implicit constraints). In particular, for the power dispatch problem, the optimization algorithm takes into account the limits on the electrical power output and the corresponding hourly power variations but does not consider other constraints on process variables whose response affects the service life of the IES. This report describes a scheme that allows accounting for implicit constraints without increasing the size of the optimization problem. To obtain a more accurate approximation of the nonlinear dynamic behavior, a parametric version of the dynamic mode decomposition with control (DMDc) algorithm was developed to derive the state-space representation matrices of the IES components at different scheduling parameter. Thanks to this approach, a more accurate approximation of the system response can be obtained, the limits imposed by thermal mechanical implicit constraints can be translated into power dispatch limits, and the feedbacks to HERON power dispatcher can be provided. To assess the developed methodology, a power dispatching test case composed of three power generating and storage units (Balance of Plant, Secondary Energy Source, Thermal Energy Storage) was developed. The power output of each one of the three units was optimized to meet the imposed time-dependent load demand trajectory and to maximize the IES profitability by meeting both the explicit and implicit constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1993

Application of jet-shear-layer mixing and effervescent atomization to the development of a low-NO(x) combustor

An investigation was conducted to develop appropriate technologies for a low-NO(x), liquid-fueled combustor. The combustor incorporates an effervescent atomizer used to inject fuel into a premixing duct. Only a fraction of the combustion air is used in the premixing process to avoid autoignition and flashback problems. This fuel-rich mixture is introduced into the remaining combustion air by a rapid jet-shear-layer-mixing process involving radial fuel-air jets impinging on axial air jets in the primary combustion zone. Computational analysis was used to provide a better understanding of the fluid dynamics that occur in jet-shear-layer mixing and to facilitate a parametric analysis appropriate to the design of an optimum low-NO(x) combustor. A number of combustor configurations were studied to assess the key combustor technologies and to validate the modeling code. The results from the experimental testing and computational analysis indicate a low-NO(x) potential for the jet-shear-layer combustor. Key parameters found to affect NO(x) emissions are the primary combustion zone fuel-air ratio, the number of axial and radial jets, the aspect ratio and radial location of the axial air jets, and the radial jet inlet hole diameter. Each of these key parameters exhibits a low-NO(x) point from which an optimized combustor was developed. Using the parametric analysis, NO(x) emissions were reduced by a factor of 3 as compared with the emissions from conventional, liquid-fueled combustors operating at cruise conditions. Further development promises even lower NO(x) with high combustion efficiency.

Colantonio, Renato Olaf↗
NASA NTRS2002

Quasi-One-Dimensional Modeling of Pulse Detonation Rocket Engines

Pulsed detonation rocket engines (PDREs) have generated considerable research interest in recent years as a chemical propulsion system potentially offering improved performance and reduced complexity compared to conventional rocket engines. The detonative mode of combustion employed by these devices offers a thermodynamic advantage over the constant-pressure deflagrative combustion mode used in conventional rocket engines and gas turbines. However, while this theoretical advantage has spurred a great deal of interest in building PDRE devices, the unsteady blowdown process intrinsic to the PDRE has made realistic estimates of the actual propulsive performance problematic. The recent review article by Kailasanath highlights some of the difficulties in comparing the available experimental measurements with numerical models. In a previous paper by the author, parametric studies of the performance of a single, straight-tube PDRE were reported. A 1-D, unsteady method of characteristics code, employing a constant-gamma assumption behind the detonation front, was developed for that study. Models of this type are computationally inexpensive, and are particularly useful for parametric performance comparisons. For example, a plot showing the specific impulse of various PDRE and steady-state rocket engine (SSRE) configurations as a function of blowdown pressure ratio. The performance curves clearly indicate that a straight-tube PDRE is superior in specific impulse to a SSRE with a sonic nozzle over the entire range of pressure ratios. Note, however, that a straight-tube PDRE in general does not compare favorably to a SSRE fitted with an optimized de Laval supersonic nozzle, particularly at the high pressure ratios typical for boost or in-space rocket applications. However, the calculations also show that if a dynamically optimized, supersonic de Laval nozzle could be could be fitted to a PDRE, then the specific impulse of the device would exceed that of a comparable SSRE. While such a nozzle is a considerable idealization, it is clear that nozzle design and optimization will play a critical role in whether the performance potential of PDREs can be effectively realized in practice. In order to study PDRE nozzle issues with greater accuracy, a quasi-one-dimensional, finite-rate chemistry CFD code has been developed by the author. Comparisons of the code with both the previous MOC model and experimental data from Stanford University are reported. The effect of constant-gamma and finite-rate chemistry assumptions on the flowfield and performance is examined. Parametric studies of the effect of nozzle throat size and expansion ratio, at various blowdown pressure ratios, are reported.

Morris, Christopher I.↗
NASA NTRS2007

Drag Prediction for the DLR-F6 Wing/Body and DPW Wing using CFL3D and OVERFLOW Overset Mesh

A series of overset grids was generated in response to the 3rd AIAA CFD Drag Prediction Workshop (DPW-III) which preceded the 25th Applied Aerodynamics Conference in June 2006. DPW-III focused on accurate drag prediction for wing/body and wing-alone configurations. The grid series built for each configuration consists of a coarse, medium, fine, and extra-fine mesh. The medium mesh is first constructed using the current state of best practices for overset grid generation. The medium mesh is then coarsened and enhanced by applying a factor of 1.5 to each (I,J,K) dimension. The resulting set of parametrically equivalent grids increase in size by a factor of roughly 3.5 from one level to the next denser level. CFD simulations were performed on the overset grids using two different RANS flow solvers: CFL3D and OVERFLOW. The results were post-processed using Richardson extrapolation to approximate grid converged values of lift, drag, pitching moment, and angle-of-attack at the design condition. This technique appears to work well if the solution does not contain large regions of separated flow (similar to that seen n the DLR-F6 results) and appropriate grid densities are selected. The extra-fine grid data helped to establish asymptotic grid convergence for both the OVERFLOW FX2B wing/body results and the OVERFLOW DPW-W1/W2 wing-alone results. More CFL3D data is needed to establish grid convergence trends. The medium grid was utilized beyond the grid convergence study by running each configuration at several angles-of-attack so drag polars and lift/pitching moment curves could be evaluated. The alpha sweep results are used to compare data across configurations as well as across flow solvers. With the exception of the wing/body drag polar, the two codes compare well qualitatively showing consistent incremental trends and similar wing pressure comparisons.

Sclanfani, Anthony J.↗
NASA NTRS2007

Integrated Aerodynamic/Structural/Dynamic Analyses of Aircraft with Large Shape Changes

The conceptual and preliminary design processes for aircraft with large shape changes are generally difficult and time-consuming, and the processes are often customized for a specific shape change concept to streamline the vehicle design effort. Accordingly, several existing reports show excellent results of assessing a particular shape change concept or perturbations of a concept. The goal of the current effort was to develop a multidisciplinary analysis tool and process that would enable an aircraft designer to assess several very different morphing concepts early in the design phase and yet obtain second-order performance results so that design decisions can be made with better confidence. The approach uses an efficient parametric model formulation that allows automatic model generation for systems undergoing radical shape changes as a function of aerodynamic parameters, geometry parameters, and shape change parameters. In contrast to other more self-contained approaches, the approach utilizes off-the-shelf analysis modules to reduce development time and to make it accessible to many users. Because the analysis is loosely coupled, discipline modules like a multibody code can be easily swapped for other modules with similar capabilities. One of the advantages of this loosely coupled system is the ability to use the medium-to high-fidelity tools early in the design stages when the information can significantly influence and improve overall vehicle design. Data transfer among the analysis modules are based on an accurate and automated general purpose data transfer tool. In general, setup time for the integrated system presented in this paper is 2-4 days for simple shape change concepts and 1-2 weeks for more mechanically complicated concepts. Some of the key elements briefly described in the paper include parametric model development, aerodynamic database generation, multibody analysis, and the required software modules as well as examples for a telescoping wing, a folding wing, and a bat-like wing.

Samareh, Jamshid A.↗