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NASA NTRSDate not supplied

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↗

NASA NTRS2021

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↗

NASA NTRS1988

An experiment in software reliability: Additional analyses using data from automated replications

A study undertaken to collect software error data of laboratory quality for use in the development of credible methods for predicting the reliability of software used in life-critical applications is summarized. The software error data reported were acquired through automated repetitive run testing of three independent implementations of a launch interceptor condition module of a radar tracking problem. The results are based on 100 test applications to accumulate a sufficient sample size for error rate estimation. The data collected is used to confirm the results of two Boeing studies reported in NASA-CR-165836 Software Reliability: Repetitive Run Experimentation and Modeling, and NASA-CR-172378 Software Reliability: Additional Investigations into Modeling With Replicated Experiments, respectively. That is, the results confirm the log-linear pattern of software error rates and reject the hypothesis of equal error rates per individual fault. This rejection casts doubt on the assumption that the program's failure rate is a constant multiple of the number of residual bugs; an assumption which underlies some of the current models of software reliability. data raises new questions concerning the phenomenon of interacting faults.

Dunham, Janet R.↗

NASA NTRS2007

Adaptive Modeling of the International Space Station Electrical Power System

Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

Thomas, Justin Ray↗

DOE OSTI2023

Methods for the Automated Determination of Sustained Maximum Amplitudes in Oscillating Signals

Machine condition monitoring has been proven to reduce machine downtime and increase productivity. The state-of-the-art research uses vibration monitoring for tasks such as maintenance and tool wear prediction. A less explored aspect is how vibration monitoring might be used to monitor equipment sensitive to vibration. In a manufacturing environment, one example of where this might be needed is in monitoring the vibration of optical linear encoders used in high-precision machine tools and coordinate measuring machines. Monitoring the vibration of sensitive equipment presents a unique case for vibration monitoring because an accurate calculation of the maximum sustained vibration is needed, as opposed to extracting trends from the data. To do this, techniques for determining sustained peaks in vibration signals are needed. Here, this work fills this gap by formalizing and testing methods for determining sustained vibration amplitudes. The methods are tested on simulated signals based on experimental data. Results show that processing the signal directly with the novel Expire Timer method produces the smallest amounts of error on average under various test conditions. Additionally, this method can operate in real-time on streaming vibration data.

Industrial Internet of Things↗

DOE OSTI2025

Deep Learning Approaches for Predicting the Surface Tension of Ionic Liquids

Ionic liquids (ILs) are a novel class of solvents that have attracted significant attention due to their unique and tunable properties. Among their physiochemical characteristics, surface tension plays a critical role in various industrial applications including electrolytes, heat transfer fluids, and separation processes. However, because of the exploratory nature of IL design and the vast combinatorial space of possible anion–cation pairs, the experimental determination of these properties is often impractical, being both time-consuming and costly. To overcome these challenges, computational approaches are increasingly employed to develop accurate predictive models that can accelerate IL discovery and design. In this study, we present two deep learning (DL) models for predicting the surface tension of ILs across a broad temperature range at a constant pressure. The models use simplified molecular input line entry system, SMILES, representations of ILs to extract molecular features as inputs. Both DL models demonstrate excellent agreement with experimental data, achieving an R 2 value of 0.990 and a root-mean-square error of 0.792 mN/m. In conclusion, these results offer valuable insights for the rapid screening and rational design of ILs with tailored surface tension values.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Optimizing process-based models to predict current and future soil organic carbon stocks at high-resolution

From hillslope to small catchment scales (< 50 km 2 ), soil carbon management and mitigation policies rely on estimates and projections of soil organic carbon (SOC) stocks. Here we apply a process-based modeling approach that parameterizes the MIcrobial-MIneral Carbon Stabilization (MIMICS) model with SOC measurements and remotely sensed environmental data from the Reynolds Creek Experimental Watershed in SW Idaho, USA. Calibrating model parameters reduced error between simulated and observed SOC stocks by 25%, relative to the initial parameter estimates and better captured local gradients in climate and productivity. The calibrated parameter ensemble was used to produce spatially continuous, high-resolution (10 m 2 ) estimates of stocks and associated uncertainties of litter, microbial biomass, particulate, and protected SOC pools across the complex landscape. Here, subsequent projections of SOC response to idealized environmental disturbances illustrate the spatial complexity of potential SOC vulnerabilities across the watershed. Parametric uncertainty generated physicochemically protected soil C stocks that varied by a mean factor of 4.4 × across individual locations in the watershed and a – 14.9 to + 20.4% range in potential SOC stock response to idealized disturbances, illustrating the need for additional measurements of soil carbon fractions and their turnover time to improve confidence in the MIMICS simulations of SOC dynamics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

A discussion on various experimental methods of impact ionization coefficient measurement in GaN

Impact ionization coefficients play a critical role in semiconductors. In addition to silicon, silicon carbide and gallium nitride are important semiconductors that are being seen more as mainstream semiconductor technologies. As a reflection of the maturity of these semiconductors, predictive modeling has become essential to device and circuit designers, and impact ionization coefficients play a key role here. Recently, several studies have measured impact ionization coefficients. We dedicated the first part of our study to comparing three experimental methods to estimate impact ionization coefficients in GaN, which are all based on photomultiplication but feature characteristic differences. The first method inserts an InGaN hole-injection layer, the accuracy of which is challenged by the dominance of ionization in InGaN, leading to possible overestimation of the coefficients. The second method utilizes the Franz–Keldysh effect for hole injection but not for electrons, where the mixed injection of induced carriers would require a margin of error. The third method uses complementary p–n and n–p structures that have been at the basis of this estimation in Si and SiC and leans on the assumption of a constant electric field, and any deviation would require a margin of error. In the second part of our study, we evaluated the models using recent experimental data from diodes demonstrating avalanche breakdown.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Thermally anisotropic building envelope for thermal management: finite element model calibration using field evaluation data

The thermally anisotropic building envelope (TABE) is an active building envelope that redistributes thermal loads in response to weather conditions and building energy demand. Conductive layers throughout the TABE distribute low-grade heat among hydronic loops, altering heat flow direction and intensity. Finite element models of TABE roof and wall panels were developed and calibrated using field evaluation data. The calibration results showed that heat flux differences between the experimental data and finite element models averaged –0.42% and 3.57%, with a maximum mean square error of 1.78 and 3.96 for roof and wall panels, respectively. A reduction in heat flux from the environment to the building living space over the entire testing period (weeks in July/August) was found to be 85% for roof panels and 335% (load reversed) for wall panels. Finally, these results indicate TABE can effectively harness low-grade thermal energy sources to achieve high energy efficiency and promote demand-side management.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Joint iterative reconstruction and 3D rigid alignment for X-ray tomography

X-ray tomography is widely used for three-dimensional structure determination in many areas of science, from the millimeter to the nanometer scale. The resolution and quality of the 3D reconstruction is limited by the availability of alignment parameters that correct for the mechanical shifts of the sample or sample stage for the images that constitute a scan. In this paper we describe an algorithm for marker-free, fully automated and accurately aligned and reconstructed X-ray tomography data. Our approach solves the tomographic reconstruction jointly with projection data alignment based on a rigid-body deformation model. We demonstrate the robustness of our method on both synthetic phantom and experimental data and show that our method is highly efficient in recovering relatively large alignment errors without prior knowledge of a low resolution approximation of the 3D structure or a reasonable estimate of alignment parameters.

36 MATERIALS SCIENCE↗

NASA NTRS1973

Evaluation of fatigue-crack growth rates by polynomial curve fitting

Fundamental characterization of the constant-amplitude fatigue crack propagation is achieved by an analysis of the rate of change of crack length with change in number of applied loading cycles, defining the rate values such that they are consistent with the basic assumption of smoothness and continuity in the fatigue crack growth process. The technique used to satisfy the analytical conditions and minimize the effects of local material anomalies and experimental errors is that of fitting a smooth curve to the entire set of basic data by least square regression. This yields a well-behaved function relating the number of cycles to the crack length. By taking the first derivative of the function, the crack growth rate is obtained for each point. The class of curve fitting functions used in the analysis is the polynomial of degree n.

Davies, K. B.↗

NASA NTRS1977

LANDSAT/coastal processes

The author has identified the following significant results. Correlations between the satellite radiance values water color, Secchi disk visibility, turbidity, and attenuation coefficients were generally good. The residual was due to several factors including systematic errors in the remotely sensed data, errors, small time and space variations in the water quality measurements, and errors caused by experimental design. Satellite radiance values were closely correlated with the optical properties of the water.

James, W. P.↗

NASA NTRS1985

Measurement of Seebeck coefficient using a light pulse

A high-temperature (1900 K) Seebeck coefficient apparatus is described in which small thermal gradients are generated in a sample by light pulses transmitted via light pipes. By employing an analog subtraction circuit, the Seebeck coefficient is displayed directly on an X-Y recorder. This technique presents a convenient, accurate, and rapid method for measuring the Seebeck coefficient in highly doped semiconductors as a function of temperature. The nature of the resulting display (X-Y recording) is a valuable tool in determining validity of the data. A straight line results (i.e., a minimum of hysteresis) only if all potential experimental errors are minimized. Under these conditions, the error of measurements of the Seebeck coefficient is estimated to be less than + or - 1 percent.

Wood, C.↗

NASA NTRS1987

Laboratory measurements and a theoretical analysis of the TCT fading channel radio system

This paper documents the laboratory and theoretical performance of a pilot-aided digital radio system. The technique considered transmits a midband pilot tone to improve the receiver data detection performance in a multipath fading channel and is referred to as the tone calibrated technique (TCT). The performance of a 860 MHz prototype system carrying 2.4 kbit/s data under Rician fading conditions is reported. Both experimental and analytical results show that the error floor experienced with nonpilot-aided transmission methods is effectively removed by the TCT scheme, resulting in significant performance gains at high signal-to-noise ratio values. The paper also examines the TCT system performance under typical operating conditions and presents a new analysis of the TCT theoretical error probability.

Rafferty, William↗

NASA NTRS1988

Accurate solutions, parameter studies and comparisons for the Euler and potential flow equations

Parameter studies are conducted using the Euler and potential flow equation models for unsteady and steady flows in both two and three dimensions. The Euler code is an implicit, upwind, finite volume code which uses the Van Leer method of flux-vector-splitting which has been recently extended for use on dynamic meshes and maintain all the properties of the original splitting. The potential flow code is an implicit, finite difference method for solving the transonic small disturbance equations and incorporates both entropy and vorticity corrections into the solution procedures thereby extending its applicability into regimes where shock strength normally precludes its use. Parameter studies resulting in benchmark type calculations include the effects of spatial and temporal refinement, spatial order of accuracy, far field boundary conditions for steady flow, frequency of oscillation, and the use of subiterations at each time step to reduce linearization and factorization errors. Comparisons between Euler and potential flows results are made as well as with experimental data where available.

Anderson, W. Kyle↗

NASA NTRS1988

Accurate solutions, parameter studies and comparisons for the Euler and potential flow equations

Parameter studies are conducted using the Euler and potential flow equation models for steady and unsteady flows in both two and three dimensions. The Euler code is an implicit, upwind, finite volume code which uses the Van Leer method of flux vector splitting which has been recently extended for use on dynamic meshes and maintain all the properties of the original splitting. The potential flow code is an implicit, finite difference method for solving the transonic small disturbance equations and incorporates both entropy and vorticity corrections into the solution procedures thereby extending its applicability into regimes where shock strength normally precludes its use. Parameter studies resulting in benchmark type calculations include the effects of spatial and temporal refinement, spatial order of accuracy, far field boundary conditions for steady flow, frequency of oscillation, and the use of subiterations at each time step to reduce linearization and factorization errors. Comparisons between Euler and potential flow results are made, as well as with experimental data where available.

Anderson, W. Kyle↗

NASA NTRS1984

Dual-mode coaxial feed with low crosspolarisation

Design data for optimized TE(11)-TM(11) dual-mode coaxial prime focus feeds is presented. The optimized feeds have a crosspolarization below -30 dB, an input reflection coefficient below 0.1 and very little phase error in their radiation patterns, over a 5 percent bandwidth. Experimental patterns are also given that show that the theoretically derived design data can be relied upon. The optimized feeds are useful for paraboloidal reflectors with focal-length/diameter ratios in the range 0.3 to 0.5, and will give overall efficiencies as high as 70 percent or more with sidelobes below -30 dB.

Collin, R. E.↗

DOE OSTI2022

Planning, design and logistics of a decision analysis study: The FBI/Ames study involving forensic firearms examiners

This paper describes design and logistical aspects of a decision analysis study to assess the performance of qualified firearms examiners working in accredited laboratories in the United States in terms of accuracy (error rate), repeatability, and reproducibility of decisions involving comparisons of fired bullets and cartridge cases. The purpose of the study was to validate current practice of the forensic discipline of firearms/toolmarks (F/T) examination. It elicited error rate data by counting the number of false positive and false negative conclusions. Preceded by the experimental design, decisions, and logistics described herein, testing was ultimately administered 173 qualified, practicing F/T examiners in public and private crime laboratories. The first round of testing evaluated accuracy, while two subsequent rounds evaluated repeatability and reproducibility of examiner conclusions. This project expands on previous studies by involving many F/T examiners in challenging comparisons and by executing the study in the recommended double-blind format.

99 GENERAL AND MISCELLANEOUS↗