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At least 901 records · Page 50

Wing Shape Sensing from Measured Strain

A new two-step theory is investigated for predicting the deflection and slope of an entire structure using strain measurements at discrete locations. In the first step, a measured strain is fitted using a piecewise least-squares curve fitting method together with the cubic spline technique. These fitted strains are integrated twice to obtain deflection data along the fibers. In the second step, computed deflection along the fibers are combined with a finite element model of the structure in order to interpolate and extrapolate the deflection and slope of the entire structure through the use of the System Equivalent Reduction and Expansion Process. The theory is first validated on a computational model, a cantilevered rectangular plate wing. The theory is then applied to test data from a cantilevered swept-plate wing model. Computed results are compared with finite element results, results using another strain-based method, and photogrammetry data. For the computational model under an aeroelastic load, maximum deflection errors in the fore and aft, lateral, and vertical directions are -3.2 percent, 0.28 percent, and 0.09 percent, respectively; and maximum slope errors in roll and pitch directions are 0.28 percent and -3.2 percent, respectively. For the experimental model, deflection results at the tip are shown to be accurate to within 3.8 percent of the photogrammetry data and are accurate to within 2.2 percent in most cases. In general, excellent matching between target and computed values are accomplished in this study. Future refinement of this theory will allow it to monitor the deflection and health of an entire aircraft in real time, allowing for aerodynamic load computation, active flexible motion control, and active induced drag reduction..

system equivalent reduction and expansion process↗

Simulation of a Real-Time Local Data Integration System over East-Central Florida

The Applied Meteorology Unit (AMU) simulated a real-time configuration of a Local Data Integration System (LDIS) using data from 15-28 February 1999. The objectives were to assess the utility of a simulated real-time LDIS, evaluate and extrapolate system performance to identify the hardware necessary to run a real-time LDIS, and determine the sensitivities of LDIS. The ultimate goal for running LDIS is to generate analysis products that enhance short-range (less than 6 h) weather forecasts issued in support of the 45th Weather Squadron, Spaceflight Meteorology Group, and Melbourne National Weather Service operational requirements. The simulation used the Advanced Regional Prediction System (ARPS) Data Analysis System (ADAS) software on an IBM RS/6000 workstation with a 67-MHz processor. This configuration ran in real-time, but not sufficiently fast for operational requirements. Thus, the AMU recommends a workstation with a 200-MHz processor and 512 megabytes of memory to run the AMU's configuration of LDIS in real-time. This report presents results from two case studies and several data sensitivity experiments. ADAS demonstrates utility through its ability to depict high-resolution cloud and wind features in a variety of weather situations. The sensitivity experiments illustrate the influence of disparate data on the resulting ADAS analyses.

Case, Jonathan↗

Orr-Sherby-Dorn creep strengths of the refractory-metal alloys C-103, ASTAR-811C, W-5Re, and W-25Re

Available creep data for the refractory-metal alloys C-103 (Nb/10 percent Hf/1 percent Ti/0.7 percent Zr), ASTAR-811C (Ta/8 percent W/1 percent Re/0.7 percent Hf/0.025 percent C), W-5Re (W/5 percent Re), and W-25Re (W/25 percent Re) were correlated by the Orr-Sherby-Dorn method and extrapolated to 1 percent creep over 10 years. Useful life was specified to be 2 standard estimates of error below the mean surface through the data. Over the temperature range of 1200 to 1800 K, ASTAR-811C was found to be the strongest of these alloys. In particular, ASTAR-811C was found to have at 1800 K the same creep strength as W-25Re at 1420 K. The difference between these results and those of Horak and Booker likely devolves from the comparative lack of long-time data on tungsten alloys.

English, Robert E.↗

Scale effect and optimum relations for sea surface planning

From the general dimensional and mechanical similarity theory it follows that a condition of steady motion of a given shape\bottom with constant speed on the surface of water is determined by four nondimensional parameters. By considering the various systems of independent parameters which are applied in theory and practice and special tests, there is determined their mutual relations and their suitability as planning characteristics. In studying the scale effect on the basis of the Prnndtl formula for the friction coefficient for a turbulent condition the order of magnitude is given of the error in applying the model data to full scale in the case of a single-step bottom For a bottom of complicated shape it is shown how from the test data of the hydrodynamic characteristics for one speed with various loads, or one load with various speeds, there may be obtained by simple computation with good approximation the hydrodynamic characteristics for a different speed or for a different load. (These considerations may be of use in solving certain problems on the stability of planning.) This permits extrapolating the curve of resistance against speed for large speeds inaccessible in the tank tests or for other loads which were not tested. The data obtained by computation are in good agreement with the test results. Problems regarding the optimum trim angle or the optimum width in the case of planning of a flat plate are considered from the point of view of the minimum resistance for a given load on the water and planning speeds. Formulas and graphs are given for the optimum value of the planning coefficient and the corresponding values of the trim angle and width of the flat plate.

Sedov, L.↗

Elucidating the challenges in extracting ultra-slow flame speeds in a closed vessel - A CH 2 F 2 microgravity case study using optical and pressure-rise data

Refrigerants with a low global warming potential (GWP) possess mild flammability. Hence, a fundamental understanding of their combustion characteristics is required to assess their fire-hazardous potential. The laminar burning velocity is one fundamental property to describe these under safety evaluation aspects. However, measuring laminar burning velocities for slow-burning components, such as low-GWP alternatives, is challenging. This is due to influencing effects such as buoyant flame deformation, stretch, radiation, and confinement, especially at the flammability limits. Here, in the present study, we investigated near-limit flames of the representative refrigerant difluoromethane (CH 2 F 2 ) with nitrogen-enriched oxidizer mixtures to elucidate the potentials and limitations at ultra-slow flame speeds of two widely used flame speed measurement methods in the closed vessel configuration: the optical flame speed measurement in the early quasi-isobaric regime and the flame speed determination from the pressure-rise during the later phase of the isochoric combustion process. Experiments were performed under terrestrial- and microgravity, conducted in a specially designed setup suitable for drop tower applications, using both methods in parallel. Recommendations for the extraction of flame speed data are derived from the non-buoyant reference investigations under microgravity and transferred to ultra-slow flames at terrestrial gravity. Near-limit flames under microgravity were found to be significantly affected by stretch effects for the optical method so that flame speed extrapolations to unstretched conditions are prone to errors. Stretch also affects the pressure method’s lower evaluation limit, and errors can be estimated by combining flame speed data from the pressure method and Markstein lengths from optical experiments.

42 ENGINEERING↗

Estimating the Soil Temperature Profile from a Single Depth Observation: A Simple Empirical Heatflow Solution

Two data sets of experimental field observations with a range of meteorological conditions are used to investigate the possibility of modeling near-surface soil temperature profiles in a bare soil. It is shown that commonly used heat flow methods that assume a constant ground heat flux can not be used to model the extreme variations in temperature that occur near the surface. This paper proposes a simple approach for modeling the surface soil temperature profiles from a single depth observation. This approach consists of two parts: 1) modeling an instantaneous ground flux profile based on net radiation and the ground heat flux at 5cm depth; 2) using this ground heat flux profile to extrapolate a single temperature observation to a continuous near surface temperature profile. The new model is validated with an independent data set from a different soil and under a range of meteorological conditions.

Holmes, Thomas↗

Computational investigation of water glasses using machine-learning potentials

The molecular origins of water’s anomalous properties have long been a subject of scientific inquiry. The liquid–liquid phase transition hypothesis, which posits the existence of distinct low-density and high-density liquid states separated by a first-order phase transition terminating at a critical point, has gained increasing experimental and computational support and offers a thermodynamically consistent framework for many of water’s anomalies. However, experimental challenges in avoiding crystallization near the postulated liquid–liquid critical point have focused attention to water’s canonical glassy states: low-density and high-density amorphous ice. Here, we use two Deep Potential machine-learning models, trained on the Strongly Constrained and Appropriately Normed density functional and the highly accurate Many-Body Polarizable potential, to conduct an investigation of water’s glassy phenomenology based on quantum mechanical calculations. Despite not being explicitly trained on amorphous ices, both models accurately capture the structure and transformation of the water glasses, including their interconversion along different thermodynamic paths. Isobaric quenching of liquid water at various pressures generates a continuum of intermediate amorphous ices and density fluctuations increase near the liquid–liquid critical pressure. The glass transition temperatures of the amorphous ices produced at different pressures exhibit two distinct branches, corresponding to low-density and high-density amorphous ice behaviors, consistent with experiment and the liquid–liquid transition hypothesis. Extrapolating transformation pressures from isothermal compressions to experimental compression rates brings our simulations into excellent agreement with data. Our findings demonstrate that machine-learning potentials trained on equilibrium phases can effectively model nonequilibrium glassy behavior and pave the way for studying long-timescale, out-of-equilibrium processes with quantum mechanical accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Benchmarking machine learning strategies for phase-field problems

Abstract We present a comprehensive benchmarking framework for evaluating machine-learning approaches applied to phase-field problems. This framework focuses on four key analysis areas crucial for assessing the performance of such approaches in a systematic and structured way. Firstly, interpolation tasks are examined to identify trends in prediction accuracy and accumulation of error over simulation time. Secondly, extrapolation tasks are also evaluated according to the same metrics. Thirdly, the relationship between model performance and data requirements is investigated to understand the impact on predictions and robustness of these approaches. Finally, systematic errors are analyzed to identify specific events or inadvertent rare events triggering high errors. Quantitative metrics evaluating the local and global description of the microstructure evolution, along with other scalar metrics representative of phase-field problems, are used across these four analysis areas. This benchmarking framework provides a path to evaluate the effectiveness and limitations of machine-learning strategies applied to phase-field problems, ultimately facilitating their practical application.

36 MATERIALS SCIENCE↗

Testing in Support of the Development of EPP Plus SMT Design Method at ORNL (FY2021)

Experiments in support of the development of the integrated Elastic–Perfectly Plastic (EPP) plus Simplified Model Test (SMT) design methodology, referred to as the EPP+SMT method, continued in FY21. This report focuses on the methodology for developing the EPP+SMT creep-fatigue (CF) design curves at low strain ranges. The creep damage-based method and dissipated work-based method were used to evaluate the available CF data at the low strain range region. A set of failure criteria were determined, and a simple extrapolation method was developed to predict the CF life cycles at low strain ranges that are not accessible by experiments due to the extraordinarily long failure times at the low strain region (thousands to hundreds of thousands of years) and the inability of the test machine to control these small strain ranges due to the signal to noise issues. An experimental method with the concept of block-strain range CF testing was proposed to generate the information needed to extrapolate the CF design curves to low strain ranges. Based on this new testing approach, a preliminary EPP+SMT CF design curve was developed for Alloy 617 at 950°C with tension hold time of 100 s. The analysis in this report shows the potential of generating a set of EPP+SMT CF design curves with different hold times within a reasonable amount of time and testing effort. Based on such a progress, a hold time extrapolation procedure for low strain ranges will be developed in FY22 and critical testing will be carried out to complete the development of the EPP+SMT CF design curves for Alloy 617.

36 MATERIALS SCIENCE↗

An out-of-distribution-aware autoencoder model for reduced chemical kinetics

While detailed chemical kinetic models have been successful in representing rates of chemical reactions in continuum scale computational fluid dynamics (CFD) simulations, applying the models in simulations for engineering device conditions is computationally prohibitive. To reduce the cost, data-driven methods, e.g., autoencoders, have been used to construct reduced chemical kinetic models for CFD simulations. Despite their success, data-driven methods rely heavily on training data sets and can be unreliable when used in out-of-distribution (OOD) regions (i.e., when extrapolating outside of the training set). In this paper, we present an enhanced autoencoder model for combustion chemical kinetics with uncertainty quantification to enable the detection of model usage in OOD regions, and thereby creating an OOD-aware autoencoder model that contributes to more robust CFD simulations of reacting flows.Here, we first demonstrate the effectiveness of the method in OOD detection in two well-known datasets, MNIST and Fashion-MNIST, in comparison with the deep ensemble method, and then present the OOD-aware autoencoder for reduced chemistry model in syngas combustion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Flight flutter testing using pulse techniques

A case of flutter developed at a speed lower than had been flown previously. This incident precipitated the routine procedure of pulsing control surfaces as well as the firing of explosive charges during speed build-ups. In the interest of rapid evaluation of results, simple methods of data reduction were used. A case history is presented where in the pulse technique predicted flutter by extrapolating decay rates obtained at subcritical speeds; in addition, a case is presented where no valid extrapolation could be made.

Stringham, R. H., Jr.↗

The non-metallic materials sample array

The Non-Metallic Materials Sample Array (MSA) was flown as verification flight instrumentation (VFI) on both Spacelab 1 (SL-1) and Spacelab 2 (SL-2). The basis for materials selection was either previous flight history or probable flight suitability based upon analysis. The observed changes in the optical properties of the exposed materials are, in general, quite minimal; however, this data represents the short exposure of two Space Shuttle missions, and no attempt should be made to extrapolate the long-term exposure. The MSA was in orbit for 10 days at approximately 240 km on SL-1 and for 7 days at approximately 315 km on SL-2. The array was exposed to the solar flux for only a portion of the time in orbit.

King, H. M.↗

Geostationary satellite position determination for common-view two-way time transfer measurements

In common-view two-way time transfer, each earth station receives an unwanted return signal from its own transmission as well as the desired signal from the other earth station. National Institute of Standards and Technology (NIST), the National Research Council (NRC), and the U.S. Naval Observatory (USNO) have been cooperating in a three-corner common-view two-way time transfer experiment. Some systematic effects are known to depend on the position of the satellite (Sagnac effect and the cross-correlation pulling of the pseudo-random codes). A method is presented for deriving accurate satellite ranges from each of three stations doing common-view two-way satellite time transfer measurements, when one (and only one) station also takes ranging measurements on its 'unwanted return signal' for a brief period. The method is applied to determine the variations in position of the satellite used over the course of the NIST/NRC/USNO SBS-3 experiment, with ranging data taken at NRC, where no additional hardware was required to automate the process. The fit and extrapolation which are employed in this method have an estimated precision of 2 m. If the delays of SBS-3 satellite KU band transponder and earth station equipment were measured accurately as well as the tropospheric refractions were well modeled and corrected, we would expect a ranging accuracy of 2.5 m and satellite positioning accuracy would be 200 m (latitude) 50 m (longitude) and 20 m (height above ellipsoid).

Zhuang, Qixiang↗

Contributions from geomagnetic inverse theory to the study of hydromagnetic conditions near the core-mantle boundary

The Final Report on contributions from geomagnetic inverse theory to the study of hydromagnetic conditions near the core-mantle boundary (CMB) is presented. The original proposal was to study five questions concerning what the surface and satellite magnetic data imply about hydromagnetic and electromagnetic conditions near the CMB. The five questions are: (1) what do the surface and satellite data imply about the geomagnetic field B near the surface of the earth; (2) how does one extrapolate B down through the conducting mantle to the CMB; (3) if B on the CMB is visible, how accurately does it satisfy the frozen-flux approximation; (4) if frozen flux is a good approximation on the CMB, what can be inferred about the fluid velocity v in the upper core; and (5) if v at the CMB is visible, does it suggest any dynamical properties of the core, such as vertical advection, Alfven-inertial waves, link instabilities, or mantle effects. A summary of the research is provided.

Backus, George E.↗

The role of airborne eddy correlation measurements in global change studies

We have obtained measurements of the mean and turbulent quantities of heat, moisture, momentum, O3, CO, and CH4 from an airborne platform. Species flux measurements obtained from these data provide unique regional-scale information which can be used to evaluate 'scaled-up' flux estimates based on smaller scale observations. Airborne flux data also provide a basis for assessing the uncertainties associated with large-scale ground level flux extrapolations. Airborne constituent budget analyses are possible with this suite of measurements. The local change in the mean value of a parameter can be explained in terms of horizontal advection, vertical turbulent transport, and, in the case of chemically reactive species (i.e., O3), in situ production or destruction. This technique is used to indicate a direct relationship between O3 precursors and the measured in situ production rate.

Ritter, J. A.↗

The Origin of the X-Ray and Ultraviolet Emission in NGC 7469

We present a spectral analysis of a approx 30 day, near-continuous observation of the Seyfert 1 galaxy NGC 7469 with RXTE. Daily integrations show strong spectral changes during the observation. Our main result is that we find the X-ray spectral index to be correlated with the UV flux. Furthermore, the broadband X-ray photon flux is also correlated with the UV continuum. These correlations point toward a model in which the X-rays originate via thermal Comptonization of UV seed photons. Furthermore, the UV is also correlated with the extrapolation of the X-ray power law into the soft X-ray/EUV region. Our data analysis therefore reopens the possibility that the UV photons and their variability arise from reprocessing, as long as the primary source of heating is photoelectric absorption in the re-processor, rather than Compton down-scattering. A coherent picture of the X-ray/UV variability can therefore be constructed whereby absorption and reprocessing of EUV/soft X-rays in a standard accretion disk produce a variable seed photon distribution, which is in turn up-scattered into the X-ray band. We also find a significant correlation between the 2-10 keV flux and the 6.4 keV iron K-alpha line, suggesting that at least some portion of the line originates within approx. 1 light day of the X-ray continuum source. Neither the power-law photon index nor the Compton reflection component are correlated with the 2-10 keV flux. The latter is not correlated with the iron K-alpha line flux either. We do find an apparent correlation between the X-ray spectral index and the strength of the Compton reflection component. In an Appendix we show, however, that this can be produced by a combination of statistical and systematic errors. We conclude that the apparent variations in the Compton reflection component may be an artifact of these effects.

Nandra, K.↗

A Decision-Support Model for Selecting Additive Manufacturing Versus Subtractive Manufacturing Based on Energy Consumption

This paper presents a simple computational model for determining whether additive manufacturing or subtractive manufacturing is more energy efficient for production of a given metallic part. The key discriminating variable is the fraction of the bounding envelope that contains material – i.e. the volume fraction of solid material. For both the additive process and the subtractive process, the total energy associated with the production of a part is defined in terms of the volume fraction of that part. The critical volume fraction is that for which the energy consumed by subtractive manufacturing equals the energy consumed by additive manufacturing. For volume fractions less than the critical value, additive manufacturing is more energy efficient. For volume fractions greater than the critical value, subtractive manufacturing is more efficient. The model considers the entire manufacturing lifecycle – from production and transport of feedstock material through processing to return of post-production scrap for recycling. Energy consumed by processing equipment while idle is also accounted for in the model. Although the individual energy components in the model are identified and accounted for in the expressions for additive and subtractive manufacturing, values for many of these components may not be currently available. Energy values for some materials’ production and subtractive and additive manufacturing processes can be found in the literature. However, since many of these data are reported for a very specific application, it may be difficult, if not impossible, to reliably apply these data to new process-material manufacturing scenarios since, very often, insufficient information is provided to enable extrapolation to broader use. Consequently, this paper also highlights the need to develop improved knowledge of the energy embodied in each phase of the manufacturing process. To be most valuable, users of the model should determine the energy consumed by their manufacturing process equipment on the basis of energy-per-unit-volume of production for each material of interest – considering both alloy composition and form. Energy consumed during machine idle per unit time should also be determined by the user then scaled to specific processing scenarios. Energy required to generate feedstock material (billet, plate, bar, wire, powder) must be obtained from suppliers.

J K Watson↗