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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 109 records · Page 6

LYAPUNOV-Based Sensor Failure Detection and Recovery for the Reverse Water Gas Shift Process

Livingstone, a model-based AI software system, is planned for use in the autonomous fault diagnosis, reconfiguration, and control of the oxygen-producing reverse water gas shift (RWGS) process test-bed located in the Applied Chemistry Laboratory at KSC. In this report the RWGS process is first briefly described and an overview of Livingstone is given. Next, a Lyapunov-based approach for detecting and recovering from sensor failures, differing significantly from that used by Livingstone, is presented. In this new method, models used are in t e m of the defining differential equations of system components, thus differing from the qualitative, static models used by Livingstone. An easily computed scalar inequality constraint, expressed in terms of sensed system variables, is used to determine the existence of sensor failures. In the event of sensor failure, an observer/estimator is used for determining which sensors have failed. The theory underlying the new approach is developed. Finally, a recommendation is made to use the Lyapunov-based approach to complement the capability of Livingstone and to use this combination in the RWGS process.

Haralambous, Michael G.↗

Validation of Material Models For Automotive Carbon Fiber Composite Structures Via Physical And Crash Testing (VMM Composites Project)

As automotive fuel economy requirements increase, the push for reducing overall vehicle weight will likely include the consideration of materials that have not previously been part of mainstream vehicle design and manufacturing, including carbon fiber composites. Vehicle manufacturers currently rely on computer-aided engineering (CAE) methods as part of the design and development process, so going forward, the ability to accurately and predictably model carbon fiber composites will be necessary. If composites are to be used for structural components, this need applies to both, crash and quasi-static modeling. This final report covers the results of a five-year, $6.89M, 50% cost-shared research project between Department of Energy (DOE) and the US Advanced Materials Partnership (USAMP) under Cooperative Agreement DE-EE-0005661 known as “Validation of Material Models for Automotive Carbon Fiber Composite Structures Via Physical and Crash Testing (VMM).” The objective of the VMM Composites Project was to validate and assess the ability of physics-based material models to predict crash performance of automotive primary load-carrying carbon fiber composite structures. Simulation material models that were evaluated included micro-mechanics based meso-scale models developed by the University of Michigan (UM) and micro-plane models by Northwestern University (NWU) under previous collaborations with the DOE and Automotive Composites Consortium/USAMP, as well as five commercial crash codes: LS-DYNA, RADIOSS, VPS/PAM-CRASH, Abaqus, and GENOA-MCQ. CAE predictions obtained from seven organizations were compared with experimental results from quasi-static testing and dynamic crash testing of a thermoset carbon fiber composite front-bumper and crush-can (FBCC) system gathered under multiple loading conditions. This FBCC design was developed to demonstrate progressive crush, virtual simulation, tooling, fabrication, assembly, non-destructive evaluation and crash testing advances in order to assess the correlation of the predicted results to the physical tests. The FBCC was developed to meet a goal of 30-35% mass reduction while aiming for equivalent energy absorption as a steel component for which baseline experimental results were obtained from testing in the same crash modes. The project also evaluated crash performance of thermoplastic composite structures fabricated from commercial prepreg materials and low cost carbon fiber sourced from Oak Ridge National Laboratory. The VMM Project determined that no set of predictions from a CAE supplier were found to be universally accurate among all the six crash modes evaluated. In general, crash modes that were most dependent on the properties of the prepreg were more accurate than those that were dependent on the behavior of the joints. The project found that current CAE modeling methods or best practices for carbon fiber composites have not achieved standardization, and accuracy of CAE is highly reliant on the experience of its users. Coupon tests alone are not sufficient to develop an accurate material model, but it is necessary to bridge the gap between the coupon data and performance of the actual structure with a series of subcomponent level tests. Much of the unreliability of the predictions can be attributed to shortcomings in our ability to mathematically link the effects of manufacturing and material variability into the material models. This is a subject of ongoing research in the industry. The final report is organized by key technical tasks to describe how the validation project developed, modeled and compared crash data obtained on the composite FBCC to the multiple sets of CAE predictions. Highlights of the report include a discussion of the quantitative comparison between predictions and experimental data, as well as an in-depth discussion of remaining technological gaps that exist in the industry, which are intended to spur innovations and improvements in CAE technology.

36 MATERIALS SCIENCE↗

Sensitivity of the boundary layer energy fluxes to forcing parameters in a simple climate model

Winter and summer surface temperatures and time-averaged boundary layer energy fluxes are calculated by utilizing the Saltzman-Ashe parameterization for boundary layer fluxes in a two-level static model. The results are found to agree with observed patterns. Within the framework of this simple model, sensitivity analyses of the time-averaged boundary layer energy fluxes are conducted. Based on these results some of the forcing parameters (such as the subsurface temperature, cloud cover, surface albedo, etc.) are arranged in a hierarchical order of importance. A generalized method of sensitivity analysis is also suggested.

Rao, M. S.↗

Asymmetric emission-line regions with out-flowing mass in QSOs and the z/ab/ at least equal to z/em/ systems

A heuristic asymmetrical model for a quasar emission-line region, with material streaming out, is described. The physical parameters are essentially the same as those of static models; the geometry turns out to be the dominant factor in determining the emission line profiles. Calculations are carried out for a variety of parameterized flow models and for the Blumenthal and Mathews (1975) theoretical model of a radiatively driven flow. The emission-line profiles are insensitive to the details of the acceleration, the filling factor, and the ionization profile. Absorption is assumed to take place in stationary matter in the QSO's galaxy or associated group or cluster, so that z(ab) is identified with the cosmological redshift. Due to the flow, the emission-lines are shifted with respect to the absorption-lines; in cases of a flow directed towards the observer systems with z(ab) at least equal to z(em) result. The distribution of absorption redshifts is symmetric about z(em).

Goldman, I.↗

Experimental investigation of passive infrared ice detection for helicopter applications

A technique is proposed to remotely detect rotor icing on helicopters. Using passive infrared (IR) thermometry it is possible to detect the warming caused by latent heat released as supercooled water freezes. During icing, the ice accretion region on the blade leading edge will be warmer than the uniced trailing edge resulting in a chordwise temperature profile characteristic of icing. Preliminary tests were conducted on a static model in the NASA Icing Research Tunnel for a variety of wet (glaze) and dry (rime) ice conditions. The characteristic chordwise temperature profiles were observed with an IR thermal video system and confirmed with thermocouple measurements. A prototype detector system was built consisting of a single point IR pyrometer, and experiments were run on a small scale rotor model. Again the characteristic chordwise temperature profiles were observed during icing, and the IR system was able to remotely detect icing. Based on the static and subscale rotor tests the passive IR technique is promising for rotor ice detection.

Dershowitz, Adam↗

Experimental investigation of passive infrared ice detection for helicopter applications

A technique is proposed to remotely detect rotor icing on helicopters. Using passive infrared (IR) thermometry, it is possible to detect the warming caused by latent heat released as supercooled water freezes. During icing, the ice accretion region on the blade leading edge will be warmer than the uniced trailing edge, resulting in a chordwise temperature profile characteristic of icing. Preliminary tests were conducted on a static model in the NASA Icing Research Tunnel for a variety of wet (glaze) and dry (rime) ice conditions. The characteristic chordwise temperature profiles were observed with an IR thermal video system and confirmed with thermocouple measurements. A prototype detector system was built consisting of a single point IR pyrometer. Experiments were run on a small scale rotor model. Again, the characteristic chordwise temperature profiles were observed during icing, and the IR system was able to remotely detect icing. Based on the static and subscale rotor tests, the passive IR technique is promising for rotor ice detection.

Dershowitz, Adam↗

Experimental Flow Models for SSME Flowfield Characterization

Full scale flow models with extensive instrumentation were designed and manufactured to provide data necessary for flow field characterization in rocket engines of the Space Shuttle Main Engine (SSME) type. These models include accurate flow path geometries from the pre-burner outlet through the throat of the main combustion chamber. The turbines are simulated with static models designed to provide the correct pressure drop and swirl for specific power levels. The correct turbopump-hot gas manifold interfaces were designed into the flow models to permit parametric/integration studies for new turbine designs. These experimental flow models provide a vehicle for understanding the fluid dynamics associated with specific engine issues and also fill the more general need for establishing a more detailed fluid dynamic base to support development and verification of advanced math models.

Abel, L. C.↗

A comparative study of dynamically expanding force-free, constant-alpha magnetic configurations with applications to magnetic clouds

We contrast two different solutions of the constant alpha, force-free MHD equation, both of which have been suggested as models for magnetic clouds: a solution in cylindrical coordinates and one in spherical coordinates. In line with the observation that magnetic clouds expand, we generalize these static models and construct their expanding counterparts. We find that expansion introduces in both cases a large asymmetry in the field strength signature which is in the same sense as that seen the the data, i.e. towards the leading edge of the cloud. We then do a least squares fit of the respective models to one-spacecraft data on a magnetic cloud. We find that the fitting routine converges in both cases. However, while purely formally we cannot distinguish between the two models using data from one spacecraft, the field components in the 'spherical' model have features not compatible with data on magnetic clouds.

Farrugia, C. J.↗

The dynamics of the nucleus of M31

Self-consistent dynamic models of the M31 nucleus were constructed which satisfy Stratoscope II and ground-based photometry, as well as ground-based velocity dispersion measurements. Two models designed to yield the highest and lowest mass-to-light ratios (M/L) consistent with observations are concentrated on. It is found that self-consistent static models of the M31 nucleus can be constructed with a nuclear mass-to-blue magnitude ratio between 0 and 50, and that it is very difficult to construct high M/L models with plausible evolutionary histories. The low values of M/L that were found suggest that the nucleus must be composed of stars on nearly radial orbits whose apocenters lie well outside the observable part of the nucleus. Such nuclei may be formed either during core collapse of a preexisting dense nucleus or by orbital decay of globular clusters in a triaxial bulge.

Tremaine, S.↗

Magnetopause modeling - Flux transfer events and magnetosheath quasi-trapped distributions

Three-dimensional distribution functions for energetic ions are studied numerically in the magnetosphere, through the magnetopause, and in the magnetosheath using a simple one-dimensional quasi-static model and ISEE 1 magnetopause crossing data for November 10, 1977. Quasi-trapped populations in the magnetosheath observed near flux transfer events (FTEs) are investigated, and it is shown that the population in the sheath appears to sandwich the FTE distributions. These quasi-trapped distributions are due to slow, large pitch angle, outward moving particles left behind by the outward rush of the ions more field-aligned at the time the flux was opened. It is found that sheath convective flows can map along the connected flux tube without drastically changing the distribution function, and results suggest that localized tangential fields above the upper limit may exist.

Speiser, T. W.↗

Development of lean, efficient, and fast physics-framed deep-learning-based proxy models for subsurface carbon storage

In this work, we present deep-learning-based surrogate models for CCUS developed with four different algorithms and a physics-framed two-phase flow problem involving displacement of water by CO 2 . The deep-learning models were trained using 3D datasets describing the pressure plume, CO 2 saturation plume, and water extraction rate generated by numerical simulation. The hyperparameters defining the architecture of the neural networks were optimized to determine the slimmest network size and training parameters that give the most efficient performance at the least training cost. To develop a robust model that closely mimics the governing physical laws, the discretized form of the two-phase fluid transport equation was used to formulate the supervised deep-learning task. The algorithms investigated in this study predicted the data to above 95% accuracy, with the multi-layer perceptron model demonstrating the best performance by balancing training speed, prediction time, and prediction accuracy with lean network capacity. Furthermore, the surrogate models simultaneously predict reservoir pressure and CO 2 saturation in every grid block, including the surface well extraction rate and bottomhole pressure, at all simulation times for a given static model realization in just a few seconds on a standard desktop computer. A key outcome of this study is that limits can be placed on network design parameters to avoid over designing neural networks, with associated efficiencies in training and prediction times. This is very useful because large volumes of data may be generated in CCUS projects and over-design of neural network architectures imposes penalties that are antithetical to the goal of near-real time forecasting.

58 GEOSCIENCES↗

An integrated analytical and experimental study of contact acoustic nonlinearity at rough interfaces of fatigue cracks

This paper presents an analytical model that describes the relationship between interface stiffness and separation of rough interfaces such as fatigue cracks. The contact acoustic nonlinearity at the interface is simulated by a quasi-static model based on Hertzian contact theory. The model is validated using the results of dynamic acoustoelastic testing (DAET) with a Rayleigh wave probe on fatigue cracks in two aluminum alloy samples. One novel aspect of this work is that all the required geometrical parameters for the model are acquired directly from the aperture profile of real cracks extracted from their scanning electron microscopy (SEM) images. Also, the separation of the crack faces during dynamic perturbation is independently measured using a 3D laser Doppler vibrometer (LDV). In addition, using DAET allows for an unprecedented direct comparison between experimental and analytical results. Overall, this is because unlike conventional nonlinear ultrasonic tests that are based on measuring the amplitude of higher harmonics, DAET outputs directly the strain-dependency of transmission and time delay of ultrasonic waves propagating across the interface. The model is found in good qualitative agreement with the experimental results, although the predictions tend to underestimate the variation of transmission coefficient and time delay. We conduct a sensitivity analysis to investigate the influence of different assumptions and simplifications on model predictions.

36 MATERIALS SCIENCE↗

Machine-Learned Force Field for Molecular Dynamics Simulations of Nonequilibrium Ammonia Synthesis on Iron Catalysts

Ammonia (NH 3 ) is one of the most important industrial chemicals. The conventional NH 3 synthesis method-the Haber–Bosch process-converts atmospheric nitrogen (N 2 ) into NH 3 using H 2 with an iron (Fe) catalyst. However, this process requires high pressures (100–200 atm) and temperatures (700–800 K) near thermal equilibrium. Recently, Fe-based nanocatalysts have been reported to produce promising NH 3 yields under atmospheric pressures and temperature-modulated nonequilibrium conditions. Understanding the mechanism of nonequilibrium catalysis with programmed temperature variation could help to optimize this fully electrified and less energy-intensive process. Although reactive molecular dynamics (RMD) simulations can be a useful tool to model nonequilibrium catalytic processes, they require the development of accurate force fields (i.e., interatomic potentials). Here, we present a machine-learned (ML) force field within the Deep Potential MD (DPMD) framework, trained using periodic density functional theory (DFT) calculations, to model NH 3 synthesis on Fe catalysts with various surface adsorbates such as *N, *H, *N 2 , *H 2 , *NH, *NH 2 , and *NH 3 . Here, we generated the DFT data from static models of elementary reactions on the most stable (110) surface of body-centered cubic Fe, which then were augmented by data from constant number of particles–volume–temperature (NVT) DFT-MD trajectories at various temperatures. Finally, we utilized the fully optimized ML force field to investigate reaction dynamics at an Fe(110) surface at linearly increasing temperatures using NVT-DPMD simulations. Our simulations indicate that pulsed temperature ramping could prove favorable for NH3 synthesis. For example, we conducted ramping under multiple sets of conditions: (i) from 900 to 1200 K over periods of 0.1–0.3 ns for Fe surfaces precovered with N or NH along with H; and (ii) from 300 to 600 K over 0.1–0.3 ns for Fe surfaces precovered with NH 3 . While our simulations so far are limited to short time scales (very rapid heating), these observations shed light on the mechanism of the high NH 3 synthesis rate achieved in a novel temperature-modulated nonequilibrium catalytic reactor using pulsed heating and cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Models for extracting vertical crustal movements from leveling data

Various adjustment strategies are being used in North America to obtain vertical crustal movements from repeated leveling. The more successful models utilize polynomials or multiquadric analysis to describe elevation change with a velocity surface. Other features permit determination of nonlinear motions, motions associated with earthquakes or episodes, and vertical motions of blocks where boundaries are prespecified. The preferred models for estimating crustal motions permit the use of detached segments of releveling to govern the shape of a velocity surface and allow for input from nonleveling sources such as tide gages and paired lake gages. Some models for extracting vertical crustal movements from releveling data are also excellent for adjusting leveling networks, and permit mixing old and new data in areas exhibiting vertical motion. The new adjustment techniques are more general than older static models and will undoubtedly be used routinely in the future as the constitution of level networks becomes mainly relevelings.

Holdahl, S. H.↗

The He II lines in the spectrum of zeta Puppis

The observed He II line spectrum in zeta Pup is compared with that predicted from model atmospheres in an attempt to establish the parameters (effective temperature, log g) which characterize the model that best represents this star's atmosphere. The study is conducted by compiling equivalent widths of the He II lines in the series (n = 2,3,4,5) and comparing them with predictions from plane-parallel static model atmospheres using a non-LTE theory of line formation. Good agreement between observation and prediction for a model atmosphere with an effective temperature of 50,000 K and log of 4.0 is found for the upper members of the n = 3 and n = 5 series, but discrepancies are found for the two lines of the n = 2 series and the upper members of the n = 4 series. It is shown that the n = 4 level appears to be more overpopulated at moderate atmospheric depths than the non-LTE calculations with plane-parallel layers indicate. It is suggested that this may be due to an overlap of the H and He II lines in the even-even series caused by macroturbulent velocities of the hydrogen and helium atoms.

Snijders, M. A. J.↗

Life Modeling and Design Analysis for Ceramic Matrix Composite Materials

The primary research efforts focused on characterizing and modeling static failure, environmental durability, and creep-rupture behavior of two classes of ceramic matrix composites (CMC), silicon carbide fibers in a silicon carbide matrix (SiC/SiC) and carbon fibers in a silicon carbide matrix (C/SiC). An engineering life prediction model (Probabilistic Residual Strength model) has been developed specifically for CMCs. The model uses residual strength as the damage metric for evaluating remaining life and is posed probabilistically in order to account for the stochastic nature of the material s response. In support of the modeling effort, extensive testing of C/SiC in partial pressures of oxygen has been performed. This includes creep testing, tensile testing, half life and residual tensile strength testing. C/SiC is proposed for airframe and propulsion applications in advanced reusable launch vehicles. Figures 1 and 2 illustrate the models predictive capabilities as well as the manner in which experimental tests are being selected in such a manner as to ensure sufficient data is available to aid in model validation.

Source record↗

Smart material based multilayered microbeam structures for spatial self-deployment and reconfiguration: A residual stress approach

Alleviation of the potentially damaging effects induced by residual stresses was comprehensively investigated in previous research. Here, this paper, however, presents a spatially self-deployable and reconfigurable multilayered microbeam which takes advantage of residual stresses and shape memory effects. Reconfigurable mechanism of a typical four-layered microbeam composed of Pt\Ni 50 Ti 50 \Ni 50 Ti 50 \Pt is introduced, followed by analytical modeling of the maximum distance of the self-deployed gap as functions of variable structural and material parameters, including compressive residual stress in Pt layers and tensile residual stress in Ni 50 Ti 50 layers. Analytical solutions given by the static model agree well with the results obtained via finite element models (FEMs). Fabrication, characterization, and in-situ experiments were carried out to validate the feasibility of deployment of the as-released four-layered microbeam. The maximum distance of the gap was measured to be 41.39 μm at 20 °C, which could be increased to 51.73 μm thanks to controllable reconfiguration driven by shape memory effects. Theoretical analysis of such self-deployment and reconfiguration suggested a tensile residual stress increase by 52 MPa in Ni 50 Ti 50 layers. The multilayered microbeam structure with capabilities of self-deployment and reconfiguration offers great potential for various emerging applications, such as micro robotics, medical drug delivery devices, and intelligent chip scale spacecraft.

36 MATERIALS SCIENCE↗

A passive infrared ice detection technique for helicopter applications

A technique has been developed, and successfully tested, to detect icing remotely on helicopter rotor blades. Using passive infrared (IR) thermometry it is possible to detect the warming caused by latent heat released as supercooled water freezes. During icing, the ice accretion region on the leading edge of the blade is found to be warmer than the uniced trailing edge resulting in a chordwise temperature profile characteristic of icing. Preliminary tests, using an IR Thermal video system, were conducted on a static model in the NASA Icing Research Tunnel (IRT) for a variety of wet (glaze) and dry (rime) ice conditions. A prototype detector system was built consisting of a single point IR pyrometer, and experiments were run on a small scale rotor model. Using this prototype detector, the characteristic chordwise temperature profiles were again observed for a range of icing conditions. Several signal processing methods were investigated, to allow automatic recognition of the icing signature. Additionally, several implementation issues were considered. Based on both the static and subscale rotor tests, where ice was successfully detected, the passive IR technique appears to be promising for rotor ice detection.

Dershowitz, Adam L.↗