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At least 271 records · Page 15

A chemical kinetic analysis of knock propensity of methanol-to-gasoline fuel

Production of low carbon gasoline-like fuels such as methanol-to-gasoline (MTG) is a promising approach to achieve rapid greenhouse gas emission reduction of the transportation sector. Despite the fact that gasoline that meets the ASTM D4814 standard for automotive spark-ignition engine fuel can be readily produced from these processes, it is unclear how the composition of MTG may affect engine performance and emissions. Here, in this paper, a surrogate for an MTG is used to numerically study the effects of gasoline composition on knock propensity and on the sensitivity of knock to thermal and fuel stratification, to oxygen dilution and to nitric oxide from exhaust gas recirculation of residual gases. Simulations were performed in ANSYS CHEMKIN-PRO using a comprehensive chemical kinetic mechanism for gasoline surrogates, and results of the MTG surrogate were compared against those of a petroleum-based regular E10 gasoline, termed PACE-20. A premium-grade MTG fuel was also formulated by adding ethanol to the MTG surrogate, and results were compared against those of four premium-grade, gasoline-like fuels representative of future alternative gasoline formulations. Surrogates and mechanism were evaluated by comparison against experimental engine data, and the model showed high accuracy at stoichiometric conditions (mean absolute error of ignition timing equal to 1.46 crank angle degrees) but larger deviations at lean conditions (mean absolute error of ignition timing equal to 5.52 crank angle degrees). Despite the fact that the MTG surrogate has a RON 1.1 units higher than that of PACE-20, it may show higher knock propensity at medium temperature conditions due to a less intense NTC behavior. MTG autoignition was more temperature- and equivalence ratio-sensitive than that of PACE20, suggesting that MTG can benefit more from naturally-occurring thermal stratification or from induced fuel stratification of the end gas to mitigate knock intensity. The sensitivity of autoignition reactivity to oxygen dilution and to NO concentration was higher for MTG than for regular gasoline at medium loads, but the opposite trend was observed at high loads due to the effect of pressure on the low-temperature chemistry of regular gasoline. Approximately 14 % vol ethanol content was required to upgrade the octane rating of MTG from regular grade to premium grade. Adding 13.6 % vol ethanol made the fuel autoignition less sensitive to both oxygen dilution and NO content (ignition time varies approx. 17 % and 50 % less with oxygen dilution and NO addition, respectively, when adding ethanol at high engine loads).

02 PETROLEUM↗

Shedding light on the 239Pu fission source term with new high-precision experiments and advanced fission modeling

In the last decade, there has been a renaissance of fission research resulting in new high-precision experiments and advanced fission modeling. For instance, the Chi-Nu and CEA teams supplied, for the first time, the 239 Pu prompt fission neutron spectrum (PFNS) for broad ranges of incident and outgoing neutron energies. The CEA team also measured 239 Pu average prompt neutron multiplicities, ν ̄ p , with lower statistical uncertainties and a technique significantly different than the one used in the past. The NIFFTE collaboration provided 239 Pu( n ,f)/ 235 U( n ,f) cross section shape ratios with uncertainties below 1% utilizing a novel detector type. Advanced fission event generators were developed, among them CGMF, FIFRELIN, FREYA, and GEF, which calculate post-scission fission observables in a correlated manner. These new experimental data and more consistent fission models change the evaluated PFNS, ν ̄ p , and ( n ,f) cross sections, some only modestly, compared to ENDF/B-VIII.0. In turn, the individual new nuclear data distinctly change simulated effective neutron multiplication factors of fast critical assemblies, but their combined impact is small, while affecting the prediction of LLNL pulsed sphere neutron leakage spectra and reaction rates only within experimental uncertainties. Also, the parameters obtained from fitting to ν ̄ p reproduce various post-scission fission observables within the uncertainties of experimental data. This indicates that new differential experiments and consistent fission modeling reduce compensating errors present in ENDF/B-VIII.0.

fission cross section↗

Intumescent coating modeling

A thermal response mathematical model for an intumescent coating system is developed. The model predicts indepth temperature profiles of the solid as a function of the fundamental kinetic, mass, and heat-transfer properties of the original coating system. In the model, swelling is based on an empirical function of the paint's weight loss. The model is used to describe the effectiveness of the coating for thermal protection. Using the thermal response time at the backface of the material as a criterion, a sensitivity analysis is made with respect to variation in individual properties, such as total expansion, to provide a guide for designing improved intumescing agents. The sensitivity analysis shows that total expansion and rate of expansion, along with other material properties, are important parameters for providing thermal protection. Finally, backface temperature histories are predicted and compared to experimental data obtained from a representative fire environment. Predicted temperatures agree within a maximum error of plus or minus 20%.

Cagliostro, D. E.↗

Comparison of forward fuselage to Space Shuttle Orbiter flight pressure data to wind tunnel and analytical results in the hypersonic Mach number range

The Space Transportation System (STS) test program is unique in that it combines flight testing with operational flights using the first operational orbital vehicle (OV-102). The Space Shuttle Orbiter was instrumented to obtain various types of flight data. The instrumentation, designated Development Flight Instrumentation (DFI) includes pressure transducers, thermocouples, calorimeters, and accelerometers. A comparison is conducted between orbiter DFI forward fuselage flight pressure data obtained from OV-102 during the STS-1 reentry, and ground facility data obtained utilizing a 0.04 scale Orbiter forebody model. The comparisons are used to validate the existing experimental data base, optimize the pressure modeling technique, and make possible the refinement of error analysis relative to both. The obtained results indicate, in general, good agreement between flight and ground-based data.

Bradley, P. F.↗

Remote sensing of earth terrain

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow covered fields is developed using the optimum polarimetric classifier. The covariance matrices for the various terrain cover are computed from theoretical models of random medium by evaluating the full polarimetric scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Theoretical probability of classification error using the full polarimetric matrix are compared with classification based on single features including the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements.

Kong, J. A.↗

Remote sensing of earth terrain

A systematic approach for the identification of terrain media such as vegetation canopy, forest, and snow covered fields is developed using the optimum polarimetric classifier. The covariance matrices for the various terrain covers are computed from the theoretical models of random medium by evaluating the full polarimetric scattering matrix elements. The optimal classification scheme makes use of a quadratic distance measure and is applied to classify a vegetation canopy consisting of both trees and grass. Experimentally measured data are used to validate the classification scheme. Theoretical probability of classification error using the full polarimetric matrix are compared with classification based on single features including the phase difference between the VV and HH polarization returns. It is shown that the full polarimetric results are optimal and provide better classification performance than single feature measurements. A systematic approach is presented for obtaining the optimal polarimetric matched filter which produces maximum contrast between two scattering classes, each represented by its respective covariance matrix.

Kong, J. A.↗

Experimental analysis of thread movement in bolted connections due to vibrations

The objective of this study was to identify the main design parameters contributing to loosening of bolts due to vibration and to identify their relative importance and degree of contribution to bolt loosening. Vibration testing was conducted on a shaketable with a controlled-random input in the dynamic testing laboratory of the Structural Test Division of MSFC. Test specimens which contained one test bolt were vibrated for a fixed amount of time and percentage of pre-load loss was measured. Each specimen tested implemented some combination of eleven design parameters as dictated by the design of experiment methodology employed. The eleven design parameters were: bolt size (diameter), lubrication on bolt, hole tolerance, initial pre-load, nut locking device, grip length, thread pitch, lubrication between mating materials, class of fit, joint configuration and mass of configuration. These parameters were chosen for this experiment because they are believed to be the design parameters having the greatest impact on bolt loosening. Two values of each design parameter were used and each combination of parameters tested was subjected to two different directions of vibration and two different g-levels of vibration. One replication was made for each test to gain some indication of experimental error and repeatability and to give some degree of statistical credibility to the data, resulting in a total of 96 tests being performed. The results of the investigation indicated that nut locking devices, joint configuration, fastener size, and mass of configuration were significant in bolt loosening due to vibration. The results of this test can be utilized to further research the complex problem of bolt loosening due to vibration.

Ramey, G. ED↗

Experimental analysis of thread movement in bolted connections due to vibrations

This is the final report of research project NAS8-39131 #33 sponsored by NASA's George C. Marshall Space Flight Center (MSFC) and carried out by the Civil Engineering Department of Auburn University (Auburn, Alabama) and personnel of MSFC. The objective of this study was to identify the main design parameters contributing to the loosening of bolts due to vibration and to identify their relative importance and degree of contribution to bolt loosening. Vibration testing was conducted on a shaketable with a controlled-random input in the dynamic testing laboratory of the Structural Test Division of MSFC. Test specimens which contained one test bolt were vibrated for a fixed amount of time and a percentage of pre-load loss was measured. Each specimen tested implemented some combination of eleven design parameters as dictated by the design of experiment methodology employed. The eleven design parameters were: bolt size (diameter), lubrication on bolt, hole tolerance, initial pre-load, nut locking device, grip length, thread pitch, lubrication between mating materials, class of fit, joint configuration, and mass of configuration. These parameters were chosen for this experiment because they are believed to be the design parameters having the greatest impact on bolt loosening. Two values of each design parameter were used and each combination of parameters tested was subjected to two different directions of vibration and two different g-levels of vibration. One replication was made for each test to gain some indication of experimental error and repeatability and to give some degree of statistical credibility to the data, resulting in a total of 96 tests being performed. The results of the investigation indicated that nut locking devices, joint configuration, fastener size, and mass of configuration were significant in bolt loosening due to vibration. The results of this test can be utilized to further research the complex problem of bolt loosening due to vibration.

Ramsey, G. ED↗

Modelling and Simulation of a Thermoelectric Heat Pump with Micro-Channel Heat Transfer

Thermoelectric heat pumps (TEHPs) have advantages of modularity and simple design for heating and cooling in some applications. Models of thermoelectric (TE) heat pumps are widely studied. Nevertheless, most existing modeling work focuses on the TE material or air-sourced TE modules. TEHP modeling, especially the relationship between modules and heat exchangers, has not been comprehensively conducted. This work presents a water-to-water TEHP modeling framework that combines Goldsmid’s approach for TE material performance, Gnielinski’s correlation for convective heat transfer, and thermal balance theory for heat exchange networks. This combined framework provides an accurate theoretical analysis of the water-to-water TEHP system. Subsequently, the framework was used to empirically determine TE material properties (electric resistivity, thermal conductivity, and Seebeck coefficient) that minimize modeling errors versus experimentally observed values from the literature. Finally, an additional set of experimental TEHP data was used to validate the model, all with relative absolute deviations of approximately 10% when predicting heating capacity and 10%–20% when forecasting cooling capacity at a 30 K temperature lift. For future work, people can further develop models of TEHPs with an air-based heat sink on one side and water channels on the other side.

Wan, Hanlong↗

Phase-shift speckle-shearing interferometry

We have numerically simulated the process of measuring stress – strain states by the method of speckle-shearing interferometry using the phase-shift technique. A computer model with the possibility of setting its strain and roughness is developed, which includes a model of a diffusely reflecting test object corresponding to the characteristics of a real membrane, as well as a speckle interferometer model that allows speckle interferograms to be obtained for different speckle sizes and angles between interfering beams. The process of reconstructing the object surface topogram from model speckle interferograms by the phase-shift technique is implemented. Using the developed models, a two-dimensional shearogram are obtained, which is a derivative of the strain field of a circular membrane. Comparison of the results of numerical simulation with experimental data shows that the differences (rms deviations) do not exceed 0.02 μm. It is also shown that the error of interferogram reconstruction by the phase-shift technique increases significantly when the test object strains exceed 12 μm. (paper)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Experiments using least square lattice filters for the identification of structural dynamics

An approach for identifying the dynamics of large space structures is applied to a free-free beam. In this approach the system's order is determined on-line, along with mode shapes, using recursive lattice filters which provide a least square estimate of the measurement data. The mode shapes determined are orthonormal in the space of the measurements and, hence, are not the natural modes of the structure. To determine the natural modes of the structure, a method based on the fast Fourier transform is used on the outputs of the lattice filter. These natural modes are used to obtain the modal amplitude time series which provides the input data for an output error parameter identification scheme that identifies the ARMA parameters of the difference equation model of the modes. the approach is applied to both simulated and experimental data.

Sundararajan, N.↗

Calculated X-ray Intensities Using Monte Carlo Algorithms: A Comparison to Experimental EPMA Data

Monte Carlo (MC) modeling has been used extensively to simulate electron scattering and x-ray emission from complex geometries. Here are presented comparisons between MC results and experimental electron-probe microanalysis (EPMA) measurements as well as phi(rhoz) correction algorithms. Experimental EPMA measurements made on NIST SRM 481 (AgAu) and 482 (CuAu) alloys, at a range of accelerating potential and instrument take-off angles, represent a formal microanalysis data set that has been widely used to develop phi(rhoz) correction algorithms. X-ray intensity data produced by MC simulations represents an independent test of both experimental and phi(rhoz) correction algorithms. The alpha-factor method has previously been used to evaluate systematic errors in the analysis of semiconductor and silicate minerals, and is used here to compare the accuracy of experimental and MC-calculated x-ray data. X-ray intensities calculated by MC are used to generate a-factors using the certificated compositions in the CuAu binary relative to pure Cu and Au standards. MC simulations are obtained using the NIST, WinCasino, and WinXray algorithms; derived x-ray intensities have a built-in atomic number correction, and are further corrected for absorption and characteristic fluorescence using the PAP phi(rhoz) correction algorithm. The Penelope code additionally simulates both characteristic and continuum x-ray fluorescence and thus requires no further correction for use in calculating alpha-factors.

Carpenter, P. K.↗

A Practical Methodology for Quantifying Random and Systematic Components of Unexplained Variance in a Wind Tunnel

This paper documents a check standard wind tunnel test conducted in the Langley 0.3-Meter Transonic Cryogenic Tunnel (0.3M TCT) that was designed and analyzed using the Modern Design of Experiments (MDOE). The test designed to partition the unexplained variance of typical wind tunnel data samples into two constituent components, one attributable to ordinary random error, and one attributable to systematic error induced by covariate effects. Covariate effects in wind tunnel testing are discussed, with examples. The impact of systematic (non-random) unexplained variance on the statistical independence of sequential measurements is reviewed. The corresponding correlation among experimental errors is discussed, as is the impact of such correlation on experimental results generally. The specific experiment documented herein was organized as a formal test for the presence of unexplained variance in representative samples of wind tunnel data, in order to quantify the frequency with which such systematic error was detected, and its magnitude relative to ordinary random error. Levels of systematic and random error reported here are representative of those quantified in other facilities, as cited in the references.

Deloach, Richard↗

A study of pilot modeling in multi-controller tasks

A modeling approach, which utilizes a matrix of transfer functions to describe the human pilot in multiple input, multiple output control situations, is studied. The approach used was to extend a well established scalar Wiener-Hopf minimization technique to the matrix case and then study, via a series of experiments, the data requirements when only finite record lengths are available. One of these experiments was a two-controller roll tracking experiment designed to force the pilot to use rudder in order to coordinate and reduce the effects of aileron yaw. One model was computed for the case where the signals used to generate the spectral matrix are error and bank angle while another model was computed for the case where error and yaw angle are the inputs. Several anomalies were observed to be present in the experimental data. These are defined by the descriptive terms roll up, break up, and roll down. Due to these algorithm induced anomalies, the frequency band over which reliable estimates of power spectra can be achieved is considerably less than predicted by the sampling theorem.

Whitbeck, R. F.↗

Computationally Guided and Experimentally Validated Design of Custom Chelators for Critical Mineral Recovery

Selective, high throughput separation of target critical metals from complex environments such as fly ash leachates and mining process streams presents a significant challenge for economical production. Custom chelators and sorbents are an attractive technology for selective metal extraction, however it can be difficult to predict their performance, and significant experimental efforts are often required to develop chelating technologies. Here, we present a computational strategy focused on modelling chelator-metal binding interactions and benchmark these results versus experimental data. A computational pipeline combining forcefield, semiempirical, and meta-GGA methods with a thermodynamic framework optimized for error cancellation has been developed to predict binding energies of chelator complexes towards critical mineral recovery applications. This approach, originally validated on [2.2.2] cryptates binding mono- and divalent cations, demonstrated robust predictive capabilities with an R2 of 0.850 against experimental aqueous binding energies. The workflow includes metadynamics for exploring high-dimensional potential energy surfaces and a cluster-continuum model for accurate yet computationally efficient solvation modeling. Error cancellation between solvation energies of free and chelator-coordinated ions enables faster convergence, even with finite cluster sizes. Initial studies on the cryptates revealed consistent metal-ligand coordination patterns, with systematic variations influenced by ion size and charge, highlighting key structural features linked to binding selectivity. Further studies of a proprietary chelator have resulted in identification of previously unreported selectivity towards economically significant metals, which in-house experiments have confirmed, demonstrating the feasibility of this approach. By applying this methodology to new chelators targeting critical minerals such as lithium, cobalt, nickel and other strategic metals, we aim to accelerate the discovery of next-generation chelators for efficient recovery, recycling, and separation processes. This computational framework serves as the backbone of a high-throughput design pipeline tailored for sustainable resource utilization and may be applied to a wide range of systems to meet experimental needs.

computational materials↗

Model wall and recovery temperature effects on experimental heat transfer data analysis

Basic analytical procedures are used to illustrate, both qualitatively and quantitatively, the relative impact upon heat transfer data analysis of certain factors which may affect the accuracy of experimental heat transfer data. Inaccurate knowledge of adiabatic wall conditions results in a corresponding inaccuracy in the measured heat transfer coefficient. The magnitude of the resulting error is extreme for data obtained at wall temperatures approaching the adiabatic condition. High model wall temperatures and wall temperature gradients affect the level and distribution of heat transfer to an experimental model. The significance of each of these factors is examined and its impact upon heat transfer data analysis is assessed.

Throckmorton, D. A.↗

GT2024-128885: Flow Reconstruction in a Transonic Turbine Cascade using Physics-Informed Neural Networks (PINNs)

This presentation investigates the application of Physics-Informed Neural Networks (PINNs) for the analysis of turbine blades in a transonic cascade. PINNs are a machine learning method trained on losses calculated from reconstructed governing equations, assigned boundary/initial conditions, and measured data. We reconstruct the 2-D flow field in a transonic turbine cascade in two ways: the traditional forward approach (without training/experimental data) and by training the PINN using experimental data. We then compare the PINN solutions to measured data. This is repeated for three different turbine blades with distinct loading characteristics. The experimental data used for training is the static pressure measurements along the suction and pressure sides of each blade. The PINN is trained utilizing all available data, half the available data, data from only the leading edge region, and data from only the trailing edge region. It's shown that the PINN can reconstruct the flow field in all cases with acceptable errors. Cases where the PINN is trained on all the data, and even half the data, resulted in the lowest errors. The exit Mach number is inferred for each case and compared to the experimentally calculated value.

Machine Learning↗

A New Method for Predicting Turbulent Flow Reattachment Location: Application of Stratford Criterion for Reattaching Flows

A new method for predicting turbulent flow reattachment location has been developed. The method predicts the reattachment location using the surface static pressure distribution and requires only a single empirical parameter. The method is based on the well-known Stratford’s flow separation criterion, which results from an approximate solution to the equations of motion within the boundary layer. Because of the large pressure rise, the original Stratford separation criterion is not valid for reattaching flows. In order to apply the Stratford criterion for reattaching flows, the reference location was moved to the pressure drop conditions instead of pressure rise conditions. In addition, the pressure distribution was scaled using a technique that was originally introduced for supersonic base flows. A new empirical parameter was also obtained for the modified Stratford criterion. The method has been tested for 30 different separated flow configurations from the literature. The variety of test cases include subsonic flows, transonic flows, 2D flows, and axisymmetric flows, with experimental as well as high resolution numerical simulation results. The flow reattachment predictions with the new method agree very well with the reported data. The error is less than 5% and typically about 2%. The new method is an extremely simple and a quick way of finding the reattachment location. Given the complexities of the existing experimental techniques for finding the reattachment location, the method easily and quickly provides the flow reattachment location, which could be used to estimate the physical extent of separation bubbles, as a performance index for flow control methods, or to assess the predictive capability of turbulence models.

Flow reattachment location↗