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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Defect Localization Capabilities of a Global Detection Scheme: Spatial Pattern Recognition Using Full-field Vibration Test Data in Plates

Recently, a conceptually simple approach, based on the notion of defect energy in material space has been developed and extensively studied (from the theoretical and computational standpoints). The present study focuses on its evaluation from the viewpoint of damage localization capabilities in case of two-dimensional plates; i.e., spatial pattern recognition on surfaces. To this end, two different experimental modal test results are utilized; i.e., (1) conventional modal testing using (white noise) excitation and accelerometer-type sensors and (2) pattern recognition using Electronic speckle pattern interferometry (ESPI), a full field method capable of analyzing the mechanical vibration of complex structures. Unlike the conventional modal testing technique (using contacting accelerometers), these emerging ESPI technologies operate in a non-contacting mode, can be used even under hazardous conditions with minimal or no presence of noise and can simultaneously provide measurements for both translations and rotations. Results obtained have clearly demonstrated the robustness and versatility of the global NDE scheme developed. The vectorial character of the indices used, which enabled the extraction of distinct patterns for localizing damages proved very useful. In the context of the targeted pattern recognition paradigm, two algorithms were developed for the interrogation of test measurements; i.e., intensity contour maps for the damaged index, and the associated defect energy vector field plots.

Saleeb, A. F.↗
NASA NTRS1954

Theoretical performance characteristics of sharp-lip inlets at subsonic speeds

A method is presented for the estimation of the subsonic-flight-speed characteristics of sharp-lip inlets applicable to supersonic aircraft. The analysis, based on a simple momentum balance consideration, permits the computation of inlet-pressure-recovery mass-flow relations and additive-drag coefficients for forward velocities from zero to the speed of sound. The penalties for operation of a sharp-lip inlet at velocity ratios other than 1.0 may be severe; at lower velocity ratios an additive drag is incurred that is not cancelled by lip suction, while at higher velocity ratios, unavoidable losses in inlet total pressure will result. In particular, at the take-off condition, the total pressure and the mass flow for a choked inlet are only 79 percent of the values ideally attainable with a rounded lip. The test specimens were polished and unnotched. The manufacturer of the material, the Aluminum Company of America, has made axial-load tests on 24S-T4 and 75S-T6 rod material. The test techniques used at the three laboratories are described in detail; the test results are presented and are compared with each other and with results obtained on unpolished sheet by the National Bureau of Standards. Experimental data obtained at zero speed with a sharp-lip supersonic inlet model were in substantial agreement with the theoretical results. (author)

Fradenburgh, Evan A↗
DOE OSTI2022

Assessing models of force-dependent unbinding rates via infrequent metadynamics

Protein–ligand interactions are crucial for a wide range of physiological processes. Many cellular functions result in these non-covalent “bonds” being mechanically strained, and this can be integral to proper cellular function. Broadly, two classes of force dependence have been observed—slip bonds, where the unbinding rate increases, and catch bonds, where the unbinding rate decreases. Despite much theoretical work, we cannot predict for which protein–ligand pairs, pulling coordinates, and forces a particular rate dependence will appear. Here, we assess the ability of MD simulations combined with enhanced sampling techniques to probe the force dependence of unbinding rates. We show that the infrequent metadynamics technique correctly produces both catch and slip bonding kinetics for model potentials. We then apply it to the well-studied case of a buckyball in a hydrophobic cavity, which appears to exhibit an ideal slip bond. Finally, we compute the force-dependent unbinding rate of biotin–streptavidin. Here, the complex nature of the unbinding process causes the infrequent metadynamics method to begin to break down due to the presence of unbinding intermediates, despite the use of a previously optimized sampling coordinate. Allowing for this limitation, a combination of kinetic and free energy computations predicts an overall slip bond for larger forces consistent with prior experimental results although there are substantial deviations at small forces that require further investigation. Furthermore, this work demonstrates the promise of predicting force-dependent unbinding rates using enhanced sampling MD techniques while also revealing the methodological barriers that must be overcome to tackle more complex targets in the future.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Efficient emulation of relativistic heavy ion collisions with transfer learning

Measurements from the Large Hadron Collider (LHC) and the Relativistic Heavy Ion Collider (RHIC) can be used to study the properties of quark-gluon plasma. Systematic constraints on these properties must combine measurements from different collision systems and methodically account for experimental and theoretical uncertainties. Such studies require a vast number of costly numerical simulations. While computationally inexpensive surrogate models (“emulators”) can be used to efficiently approximate the predictions of heavy ion simulations across a broad range of model parameters, training a reliable emulator remains a computationally expensive task. We use transfer learning to map the parameter dependencies of one model emulator onto another, leveraging similarities between different simulations of heavy ion collisions. By limiting the need for large numbers of simulations to only one of the emulators, this technique reduces the numerical cost of comprehensive uncertainty quantification when studying multiple collision systems and exploring different models.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1976

State trajectories used to observe and control dc-to-dc converters

State-plane analysis techniques are employed to study the voltage stepup energy-storage dc-to-dc converter. Within this framework, an example converter operating under the influence of a constant on-time and a constant frequency controller is examined. Qualitative insight gained through this approach is used to develop a conceptual free-running control law for the voltage stepup converter which can achieve steady-state operation in one on/off cycle of control. Digital computer simulation data are presented to illustrate and verify the theoretical discussions presented.

Burns, W. W., III↗
NASA NTRS1995

Spacecraft Cabin Air Quality Control and Its Application to Tight Buildings

Air quality is an important consideration not only for the external environment, but also for the indoor environment. Most people spend a majority of their lives indoors and the air that they breathe is important to their physical and emotional well being. Since most modern building designs have focused on energy efficiency, less fresh air is brought from the outside. As a result, pollutants from building materials, furniture, cleaning, and cooking have no place to go. To make matters worse, most ventilation systems do not include any means for removing pollutants from the recycled air. Unfortunately, pollution at even a small level can result in eye, throat, and lung irritation in addition to chronic headaches, nausea, and fatigue. A spacecraft cabin, which represents the worst case in tight building design, requires special consideration of air quality since any effects pollutants may have on a crewmember can potentially place a mission or other crewmembers at risk. A detailed approach has been developed by the National Aeronautics and Space Administration (NASA) to minimize cabin atmosphere pollution and provide the crew with an environment which is as free of pollutants as possible. This approach is a combination of passive and active contamination control concepts involving the evaluation and selection of materials to be used onboard the spacecraft, the establishment of air quality standards to ensure crew health, and the use of active control means onboard the spacecraft to further ensure an acceptable atmosphere. This approach has allowed NASA to prevent illness by providing crewmembers with a cabin atmosphere which contains pollutant concentrations up to 100 times lower than those specified for terrestrial indoor environments. Standard building construction, however, does not take into account the potentially harmful effects of materials used in the construction process on the health of future occupants and relies primarily on remedial rather than preventive techniques when addressing contamination. This approach results in a building that theoretically has low operating costs, but may actually have high costs associated with lost work days, increased medical claims, decreased productivity, and problem remediation. A similar approach to NASA's may be adopted by the building construction community which can tap the extensive database of material offgassing properties that has been collected to support the space program. Many materials used by NASA are commercially available and are frequently used in building construction. In addition, computer models which have been developed for assessing various methods of active contamination control can be applied to building ventilation system design and the analysis of their economics. Through using NASA' s experience, the expense associated with the current remedial approach can be avoided.

Perry, J. L.↗
NASA NTRS2003

Kalman Filtering with Inequality Constraints for Turbofan Engine Health Estimation

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops two analytic methods of incorporating state variable inequality constraints in the Kalman filter. The first method is a general technique of using hard constraints to enforce inequalities on the state variable estimates. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The second method uses soft constraints to estimate state variables that are known to vary slowly with time. (Soft constraints are constraints that are required to be approximately satisfied rather than exactly satisfied.) The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estimation accuracy. The improvement is proven theoretically and shown via simulation results. The use of the algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate health parameters. The turbofan engine model contains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.

Simon, Dan↗
NASA NTRS2015

Empirical State Error Covariance Matrix for Batch Estimation

State estimation techniques effectively provide mean state estimates. However, the theoretical state error covariance matrices provided as part of these techniques often suffer from a lack of confidence in their ability to describe the uncertainty in the estimated states. By a reinterpretation of the equations involved in the weighted batch least squares algorithm, it is possible to directly arrive at an empirical state error covariance matrix. The proposed empirical state error covariance matrix will contain the effect of all error sources, known or not. This empirical error covariance matrix may be calculated as a side computation for each unique batch solution. Results based on the proposed technique will be presented for a simple, two observer and measurement error only problem.

Frisbee, Joe↗
DOE OSTI2021

Cryogenic Vibrationally Resolved Photoelectron Spectroscopy of OH–(H2O): Confirmation of Multidimensional Franck-Condon Simulation Results for the Transition State of the OH + H2O Reaction

We present a transition state spectroscopic study of the OH + H2O reaction using the experimental technique of cryogenic Negative Ion Photoelectron Spectroscopy (NIPES). The recorded NIPE spectrum at 193 nm exhibits multiple vibrational progressions that include excitations to the shared H atom antisymmetric stretching mode with an interval of 0.32 eV as well as other progressions, mainly involving the H bending and O…O symmetric stretching modes. The Vertical Detachment Energy (VDE) was measured at 3.53 eV, whereas an upper limit for the Adiabatic Detachment Energy (ADE) was estimated at 2.90 eV. These values are in excellent agreement with the theoretically computed values of 3.51 eV and 2.83 eV respectively, obtained at the CCSD(T)/aug-cc-pV5Z level of theory. The recorded NIPE spectrum is in very good agreement when compared to the one recently reported from four-dimensional Franck-Condon simulations, in which a similar spectral profile was predicted. Besides observing the ground state, a charge-transfer excited state in the form of [OH–(H2O)+] is identified with a relative energy of 1.39 eV, well matching the previous prediction of 1.36 eV. This work was supported by U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences, and performed using EMSL, a national scientific user facility sponsored by DOE’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory, which is operated by Battelle Memorial Institute for the DOE. The theoretical calculations were conducted on EMSL’s “Cascade” Supercomputer. This research also used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231.

Cao, Wenjin↗
NASA NTRS1978

Self streamlining wind tunnel: Further low speed testing and final design studies for the transonic facility

Work was continued with the low speed self streamlining wind tunnel (SSWT) using the NACA 0012-64 airfoil in an effort to explain the discrepancies between the NASA Langley low turbulence pressure tunnel (LTPT) and SSWT results obtained with the airfoil stalled. Conventional wind tunnel corrections were applied to straight wall SSWT airfoil data, to illustrate the inadequacy of standard correction techniques in circumstances of high blockage. Also one SSWT test was re-run at different air speeds to investigate the effects of such changes (perhaps through changes in Reynold's number and freestream turbulence levels) on airfoil data and wall contours. Mechanical design analyses for the transonic self-streamlining wind tunnel (TSWT) were completed by the application of theoretical airfoil flow field data to the elastic beam and streamline analysis. The control system for the transonic facility, which will eventually allow on-line computer operation of the wind tunnel, was outlined.

Wolf, S. W. D.↗
NASA NTRS2004

Neural network uncertainty assessment using Bayesian statistics: a remote sensing application

Neural network (NN) techniques have proved successful for many regression problems, in particular for remote sensing; however, uncertainty estimates are rarely provided. In this article, a Bayesian technique to evaluate uncertainties of the NN parameters (i.e., synaptic weights) is first presented. In contrast to more traditional approaches based on point estimation of the NN weights, we assess uncertainties on such estimates to monitor the robustness of the NN model. These theoretical developments are illustrated by applying them to the problem of retrieving surface skin temperature, microwave surface emissivities, and integrated water vapor content from a combined analysis of satellite microwave and infrared observations over land. The weight uncertainty estimates are then used to compute analytically the uncertainties in the network outputs (i.e., error bars and correlation structure of these errors). Such quantities are very important for evaluating any application of an NN model. The uncertainties on the NN Jacobians are then considered in the third part of this article. Used for regression fitting, NN models can be used effectively to represent highly nonlinear, multivariate functions. In this situation, most emphasis is put on estimating the output errors, but almost no attention has been given to errors associated with the internal structure of the regression model. The complex structure of dependency inside the NN is the essence of the model, and assessing its quality, coherency, and physical character makes all the difference between a blackbox model with small output errors and a reliable, robust, and physically coherent model. Such dependency structures are described to the first order by the NN Jacobians: they indicate the sensitivity of one output with respect to the inputs of the model for given input data. We use a Monte Carlo integration procedure to estimate the robustness of the NN Jacobians. A regularization strategy based on principal component analysis is proposed to suppress the multicollinearities in order to make these Jacobians robust and physically meaningful.

Neural Networks (Computer)↗
DOE OSTI2020

Coarse-grain cluster analysis of tensors with application to climate biome identification

A tensor provides a concise way to codify the interdependence of complex data. Treating a tensor as a d-way array, each entry records the interaction between the different indices. Clustering provides a way to parse the complexity of the data into more readily understandable information. Clustering methods are heavily dependent on the algorithm of choice, as well as the chosen hyperparameters of the algorithm. However, their sensitivity to data scales is largely unknown. In this work, we apply the discrete wavelet transform to analyze the effects of coarse-graining on clustering tensor data. We are particularly interested in understanding how scale affects clustering of the Earth's climate system. The discrete wavelet transform allows classification of the Earth's climate across a multitude of spatial-temporal scales. The discrete wavelet transform is used to produce an ensemble of classification estimates, as opposed to a single classification. Each element of the ensemble is a clustering at a different spatial-temporal scale. Information theoretic approaches are used to identify important scale lengths in clustering the L15 Climate Datset. We also discover a sub-collection of the ensemble that spans the majority of the variance observed, allowing for efficient consensus clustering techniques that can be used to identify climate biomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Dynamic mode decomposition with core sketch

With the increase in collected data volumes, either from experimental measurements or high fidelity simulations, there is an ever-growing need to develop computationally efficient tools to process, analyze, and interpret these datasets. Modal analysis techniques have gained great interest due to their ability to identify patterns in the data and extract valuable information about the system being considered. Dynamic mode decomposition (DMD) relies on elements of the Koopman approximation theory to compute a set of modes, each associated with a fixed oscillation frequency and a decay/growth rate. Extracting these details from large datasets can be computationally expensive due to the need to implement singular value decomposition of the input data matrix. Sketching algorithms have become popular in numerical linear algebra where statistical theoretic approaches are utilized to reduce the cost of major operations. A sketch of a matrix is another matrix, which is significantly smaller, but still sufficiently approximates the original system. We put forth an efficient DMD framework, SketchyDMD, based on a core sketching algorithm that captures information about the range and corange (their mutual relationship) of input data. The proposed sketching-based framework can accelerate various portions of the DMD routines, compared to classical methods that operate directly on the raw input data. We conduct numerical experiments using the spherical shallow water equations as a prototypical model in the context of geophysical flows. In conclusion, we show that the proposed SketchyDMD is superior to existing randomized DMD methods that are based on capturing only the range of the input data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

An adjoint-based optimization method for jointly inverting heterogeneous material properties and fault slip from earthquake surface deformation data

SUMMARY Analysis of tectonic and earthquake-cycle associated deformation of the crust can provide valuable insights into the underlying deformation processes including fault slip. How those processes are expressed at the surface depends on the lateral and depth variations of rock properties. The effect of such variations is often tested by forward models based on a priori geological or geophysical information. Here, we first develop a novel technique based on an open-source finite-element computational framework to invert geodetic constraints directly for heterogeneous media properties. We focus on the elastic, coseismic problem and seek to constrain variations in shear modulus and Poisson’s ratio, proxies for the effects of lithology and/or temperature and porous flow, respectively. The corresponding nonlinear inversion is implemented using adjoint-based optimization that efficiently reduces the cost function that includes the misfit between the calculated and observed displacements and a penalty term. We then extend our theoretical and numerical framework to simultaneously infer both heterogeneous Earth’s structure and fault slip from surface deformation. Based on a range of 2-D synthetic cases, we find that both model parameters can be satisfactorily estimated for the megathrust setting-inspired test problems considered. Within limits, this is the case even in the presence of noise and if the fault geometry is not perfectly known. Our method lays the foundation for a future reassessment of the information contained in increasingly data-rich settings, for example, geodetic GNSS constraints for large earthquakes such as the 2011 Tohoku-oki M9 event, or distributed deformation along plate boundaries as constrained from InSAR.

Geochemistry & Geophysics↗
DOE OSTI2024

Problem-tailored Simulation of Energy Transport on Noisy Quantum Computers

The transport of conserved quantities like spin and charge is fundamental to characterizing the behavior of quantum many-body systems. Numerically simulating such dynamics is generically challenging, which motivates the consideration of quantum computing strategies. However, the relatively high gate errors and limited coherence times of today's quantum computers pose their own challenge, highlighting the need to be frugal with quantum resources. In this work we report simulations on quantum hardware of infinite-temperature energy transport in the mixed-field Ising chain, a paradigmatic many-body system that can exhibit a range of transport behaviors at intermediate times. We consider a chain with L = 12 sites and find results broadly consistent with those from ideal circuit simulators over 90 Trotter steps, containing up to 990 entangling gates. To obtain these results, we use two key problem-tailored insights. First, we identify a convenient basis – the Pauli Y basis – in which to sample the infinite-temperature trace and provide theoretical and numerical justifications for its efficiency relative to, e.g., the computational basis. Second, in addition to a variety of problem-agnostic error mitigation strategies, we employ a renormalization strategy that compensates for global nonconservation of energy due to device noise. We discuss the applicability of the proposed sampling approach beyond the mixed-field Ising chain and formulate a variational method to search for a sampling basis with small sample-to-sample fluctuations for an arbitrary Hamiltonian. This opens the door to applying these techniques in more general models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Dependence of alpha-particle-driven Alfven eigenmode linear stability on device magnetic field strength and consequences for next-generation tokamaks

Recently-proposed tokamak concepts use magnetic fields up to 12 T, far higher than in conven- tional devices, to reduce size and cost. Theoretical and computational study of trends in plasma behavior with increasing field strength is critical to such proposed devices. This paper considers trends in Alfven eigenmode (AE) stability. Energetic particles, including alphas from D-T fusion, can destabilize AEs, possibly causing loss of alpha heat and damage to the device. AEs are sensitive to device magnetic field via the field dependence of resonances, alpha particle beta, and alpha orbit width. We describe the origin and effect of these dependences analytically and by using recently- developed numerical techniques (Rodrigues et al. 2015 Nucl. Fusion 55 083003). The work suggests high-field machines where fusion-born alphas are sub-Alfvenic or nearly sub-Alfvenic may partially cut off AE resonances, reducing growth rates of AEs and the energy of alphas interacting with them. High-field burning plasma regimes have non-negligible alpha particle beta and AE drive, but faster slowing down time, provided by high electron density, and higher field strength reduces this drive relative to low-field machines with similar power densities. The toroidal mode number of the most unstable modes will tend to be higher in high magnetic field devices. The work suggests that high magnetic field devices have unique, and potentially advantageous, AE instability properties at both low and high densities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1974

Evaluation of importance of lateral acceleration derivatives in extraction of lateral-directional derivatives at high angles of attack

A theoretical investigation was conducted to determine the importance of the lateral acceleration (beta) derivatives in the extraction of lateral-directional stability derivatives for swept wing airplanes at high angles of attack. Representative values of lateral acceleration derivatives in yaw and roll (Cn beta and Cl beta) were used in a computer program to generate representative flight motions at several angles of attack and altitudes. The computer-generated motions were then subjected to a parameter identification process based on a modified Newton-Raphson method. Two identification techniques were evaluated, one which included the beta derivatives and one which neglected them. The results of the study indicate that omission of the beta derivatives from mathematical models used in the derivative-extraction techniques can produce erroneous values for the lateral-directional stability derivatives particularly at high angles of attack, where the beta derivatives are large. The largest errors occur in the dynamic derivatives, but large errors may also occur in the static derivatives for cases in which the beta derivatives have large effects on the flight motions of the airplane. In addition, the resulting identified mathematical models provide poor motion prediction as well as erroneous predictions of dynamic modal characteristics. These results strongly indicate that the effects of beta derivatives should be considered in any attempt to extract lateral-directional aerodynamic parameters at high angles of attack.

Nguyen, L. T.↗
NASA NTRS1974

A theory of wave scatter from an inhomogeneous medium with a slightly rough boundary and its application to sea ice

An analytical theory of electromagnetic wave scattering from an inhomogeneous medium with a slightly rough boundary surface is formulated. The inhomogeneity in the medium is assumed to vary continuously in the vertical direction and to have a small random variation in the horizontal direction. The medium is assumed to consist of two layers. Maxwell's equations are solved by using the small perturbation method together with Fourier transform technique. The resulting differential equations are solved by using WKB and variation of parameter methods. Field amplitudes in each medium are determined by taking boundary conditions into account. The expressions for first order polarized radar backscatter cross-section are obtained. An attempt is made to apply the developed theory to compute sea ice scatter. Numerical calculations are performed for polarized radar backscatter cross-section at two frequencies, 13.3 GHz and 400 MHz. It is shown that WKB method is applicable at both of these frequencies. Theoretical results are compared with the experimental results obtained from NASA Earth Resources Program mission 126. Theoretical results and experimental results are in good agreement.

Parashar, S. K.↗