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NASA NTRS2002

Minnowbrook III: 2000 Workshop on Boundary Layer Transition and Unsteady Aspects of Turbomachinery Flows

This volume and its accompanying CD-ROM contain materials presented at the Minnowbrook III-2000 Workshop on Boundary Layer Transition and Unsteady Aspects of Turbomachinery Flows held at the Syracuse University Minnowbrook Conference Center, Blue Mountain Lake, New York, August 20-23, 2000. Workshop organizers were John E. LaGraff (Syracuse University), Terry V Jones (Oxford University), and J. Paul Gostelow (University of Leicester). The workshop followed the theme, venue, and informal format of two earlier workshops: Minnowbrook I (1993) and Minnowbrook II (1997). The workshop was focused on physical understanding the late stage (final breakdown) boundary layer transition, separation, and effects of unsteady wakes with the specific goal of contributing to engineering application of improving design codes for turbomachinery. The workshop participants included academic researchers from the USA and abroad, and representatives from the gas-turbine industry and government laboratories. The physical mechanisms discussed included turbulence disturbance environment in turbomachinery, flow instabilities, bypass and natural transition, turbulent spots and calmed regions, wake interactions with attached and separated boundary layers, turbulence and transition modeling and CFD, and DNS. This volume contains abstracts and copies of the viewgraphs presented, organized according to the workshop sessions. The viewgraphs are included on the CD-ROM only. The workshop summary and the plenary-discussion transcripts clearly highlight the need for continued vigorous research in the technologically important area of transition, separated and unsteady flows in turbomachines.

LaGraff, John E.↗

NASA NTRS2015

Comparison of Computational and Experimental Results for a Transonic Variable-Speed Power-Turbine Blade Operating with Low Inlet Turbulence Levels

A computational assessment of the aerodynamic performance of the midspan section of a variable-speed power-turbine blade is described. The computation comprises a periodic single blade that represents the 2-D Midspan section VSPT blade that was tested in the NASA Glenn Research Center Transonic Turbine Blade Cascade Facility. A commercial, off-the-shelf (COTS) software package, Pointwise and CFD++, was used for the grid generation and RANS and URANS computations. The CFD code, which offers flexibility in terms of turbulence and transition modeling options, was assessed in terms of blade loading, loss, and turning against test data from the transonic tunnel. Simulations were assessed at positive and negative incidence angles that represent the turbine cruise and take-off design conditions. The results indicate that the secondary flow induced at the positive incidence cruise condition results in a highly loaded case and transitional flow on the blade is observed. The negative incidence take-off condition is unloaded and the flow is very two-dimensional. The computational results demonstrate the predictive capability of the gridding technique and COTS software for a linear transonic turbine blade cascade with large incidence angle variation.

turbomachinery↗

NASA NTRS2015

Comparison of Computational and Experimental Results for a Transonic Variable-speed Power-Turbine Blade Operating with Low Inlet Turbulence Levels

rotary wing↗

NASA NTRS1979

Multivariable control altitude demonstration on the F100 turbofan engine

The control system designed under the Multivariable Control Synthesis (MVCS) program for the F100 turbofan engine is described. The MVCS program, applied the linear quadratic regulator (LQR) synthesis methods in the design of a multivariable engine control system to obtain enhanced performance from cross-coupled controls, maximum use of engine variable geometry, and a systematic design procedure that can be applied efficiently to new engine systems. Basic components of the control system, a reference value generator for deriving a desired equilibrium state and an approximate control vector, a transition model to produce compatible reference point trajectories during gross transients, gain schedules for producing feedback terms appropriate to the flight condition, and integral switching logic to produce acceptable steady-state performance without engine operating limit exceedance are described and the details of the F100 implementation presented. The engine altitude test phase of the MVCS program, and engine responses in a variety of test operating points and power transitions are presented.

Lehtinen, B.↗

NASA NTRS1981

Viscous-inviscid interaction for transonic wing-body configurations including wake effects

An existing three-dimensional compressible integral boundary-layer method was modified to account for mean dilatation effects, to model transition properly, and to provide better numerical stability near computational boundaries. Results of this method were compared against those from a three-dimensional finite-difference boundary-layer method on a difficult test case. An interaction procedure was developed to couple this integral method with a number of wing-alone and wing-body transonic potential codes to account for viscous effects. A strip wake model, including thickness and curvature effects, was developed and incorporated into this interaction procedure. Results from this procedure were compared against experimental data and results from previous procedures, on test cases where viscous effects were large.

Streett, C. L.↗

NASA NTRSDate not supplied

AMMPER: a user-friendly agent-based model that recapitulates simple metabolic responses of yeast to deep-space radiation

For humans venturing to deep space, radiation exposure poses a major health risk. Fundamental research into the biological effects of space radiation are essential for enabling exploration, and the first experimental organisms we send to deep space will be microbial. Yet there are many ways in which microorganisms are likely to experience the effects of high-energy particle radiation (such as Galactic Cosmic Rays) differently from multicellular animals, partly due to the simple fact that microbes are small and unicellular-- less likely to get hit in the first place, and less likely to communicate damage between cells. Computational modeling can aid in designing experiments and predicting the biological effects of radiation, but thus far particle radiation models have not focused on microbes. Here we present the latest developments in AMMPER, the Agent-based Model for Microbial Populations Exposed to Radiation. Originally written in 2021, AMMPER is a Python-based model that incorporates radiation track data from NASA's RITRACKS software and simulates the growth, damage, and death of yeast cells in 3D. It is now freely available as an open-source package on NASA's GitHub repository. Recent improvements include the ability to simulate the dynamics of alamarBlue, a color-changing redox dye commonly used to track metabolic activity in microbial spaceflight experiments. We demonstrate that a simple blue-pink-clear transition model is able to recapitulate key features observed in empirical data from ground studies. AMMPER also includes a new graphical user interface and introductory tutorial to facilitate ease of use by a wider audience. AMMPER can help us to understand how spatially heterogeneous particle radiation damage at the single-cell level can translate to growth differences at the population level, ultimately allowing us to better interpret experiments using microbes as model organisms and how well their results apply to humans.

yeast↗

DOE OSTI2023

Optimizing Renewable Ammonia Production for a Sustainable Fertilizer Supply Chain Transition

Local renewable ammonia production using electrolytic hydrogen is an emerging approach to alleviate emissions attributed to synthetic nitrogen fertilizer production while also insulating against fluctuations in fertilizer prices and mitigating transportation costs and emissions. However, replacing ammonia currently produced using fossil fuels will not be immediate. To this end, we develop a supply chain transition model, which first optimizes the design and hourly operation of new renewable ammonia facilities to minimize production costs and then optimizes the annual installation timing, production scale, and location of these new renewable facilities along with ammonia transportation to meet county resolution demands. The objective is to augment and eventually replace conventional ammonia market imports in an economically competitive manner. We performed a case study for Minnesota's ammonia supply chain and found that a full transition to in-state renewable production by 2032 is optimal. This is incentivized by the U.S. federal government's clean hydrogen production credits. This transition results in 99 % reduction in carbon intensity along with stable supply costs below $475 per metric tonne. New renewable production facilities are an order of magnitude smaller than existing conventional plants. They use both wind and solar resources and operate dynamically to minimize expensive battery and hydrogen storage capacities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1990

MEASURE: An integrated data-analysis and model identification facility

The first phase of the development of MEASURE, an integrated data analysis and model identification facility is described. The facility takes system activity data as input and produces as output representative behavioral models of the system in near real time. In addition a wide range of statistical characteristics of the measured system are also available. The usage of the system is illustrated on data collected via software instrumentation of a network of SUN workstations at the University of Illinois. Initially, statistical clustering is used to identify high density regions of resource-usage in a given environment. The identified regions form the states for building a state-transition model to evaluate system and program performance in real time. The model is then solved to obtain useful parameters such as the response-time distribution and the mean waiting time in each state. A graphical interface which displays the identified models and their characteristics (with real time updates) was also developed. The results provide an understanding of the resource-usage in the system under various workload conditions. This work is targeted for a testbed of UNIX workstations with the initial phase ported to SUN workstations on the NASA, Ames Research Center Advanced Automation Testbed.

Singh, Jaidip↗

NASA NTRS1975

Propagation of acoustic modes in the transitional ionosphere

Continuum theory is unsatisfactory for describing wave propagation in the transitional ionosphere, since the mean free path is of the same order as the characteristic length (i.e., Knudsen number in this region is of the order of unity). Therefore a transition model in which isotropic electrons behave as a fluid while the ions are governed by the kinetic equation modified by ion-electron collision effects is proposed to study acoustic wave propagation in the upper atmosphere in the altitude region from 500 to 2000 km. The results show that the dissipation of acoustic waves by electrons is through the viscous and thermal conduction effects, and the dissipation of acoustic waves by ions is through Landau damping. Comparisons of the characteristics of acoustic mode propagation and wave dissipation mechanisms in the collision-dominated, transitional from collisional to collisionless, and collisionless media are also discussed.

Hung, R. J.↗

NASA NTRS1991

Free-stream turbulence and concave curvature effects on heated, transitional boundary layers

An experimental investigation of the transition process on flat-plate and concave curved-wall boundary layers for various free-stream turbulence levels was performed. Results show that for transition of a flat-plate, the two forms of boundary layer behavior, identified as laminar-like and turbulent-like, cannot be thought of as separate Blasius and fully-turbulent profiles, respectively. Thus, simple transition models in which the desired quantity is assumed to be an average, weighted on intermittency, of the theoretical laminar and fully turbulent values is not expected to be successful. Deviation of the flow identified as laminar-like from theoretical laminar behavior is shown to be due to recovery after the passage of a turbulent spot, while deviation of the flow identified as turbulent-like from the full-turbulent values is thought to be due to incomplete establishment of the fully-turbulent power spectral distribution. Turbulent Prandtl numbers for the transitional flow, computed from measured shear stress, turbulent heat flux and mean velocity and temperature profiles, were less than unity. For the curved-wall case with low free-stream turbulence intensity, the existence of Gortler vortices on the concave wall within both laminar and turbulent flows was established using liquid crystal visualization and spanwise velocity and temperature traverses. Transition was found to occur via a vortex breakdown mode. The vortex wavelength was quite irregular in both the laminar and turbulent flows, but the vortices were stable in time and space. The upwash was found to be more unstable, with higher levels of u' and u'v', and lower skin friction coefficients and shape factors. Turbulent Prandtl numbers, measured using a triple-wire probe, were found to be near unity for all post-transitional profiles, indicating no gross violation of Reynolds analogy. No evidence of streamwise vortices was seen in the high turbulence intensity case.

Kim, J.↗

DOE OSTI2025

DriveSense: A Noise-Resilient Framework for Driving Mode Identification

Accurate drive mode classification is essential for enhancing the reliability and predictive maintenance of heavy-duty electric trucks. This study proposes a novel fuzzy logic-based framework, DriveSense, for real-time drive mode classification, addressing key challenges such as sensor noise, transitional behaviors, and computational efficiency. The proposed approach integrates a two-stage filtering pipeline, combining adaptive outlier removal and a dynamic Kalman filter to enhance data quality. A fuzzy inference system with smoothened trapezoidal membership functions is then applied to classify driving modes into standstill, constant speed, acceleration, and deceleration while mitigating the effects of noise and edge cases. Performance evaluation using real-world and simulated drive cycles demonstrates significant improvements in classification accuracy (up to 97.8%), F1-score (up to 0.97), and robustness against noise, while reducing false positives. Comparative analysis against baseline models, demonstrates DriveSense’s superior accuracy and generalizability across diverse driving patterns. The framework’s lightweight and interpretable fuzzy inference engine operates with low computational latency, ensuring compatibility with real-time embedded systems typical of heavy-duty electric trucks. Moreover, DriveSense models transitional behaviors through overlapping fuzzy sets and adaptive borderline classification logic, enabling smooth identification of subtle shifts such as rolling stops or gradual deceleration. These results highlight DriveSense’s potential to enhance predictive maintenance strategies, reduce downtime, and support scalable, fleet-wide diagnostics.

Kumar, Praveen [Oak Ridge National Laboratory (ORN↗

NASA NTRS1983

Outer atmospheres of cool stars. XIV - A model for the chromosphere and transition region of Beta Ceti (G9.5 III)

In the present chromospheric and transition region model for Beta Ceti, which is consistent with IUE spectra of the Mg II, C II, and C IV resonance lines, the Mg II h and k lines are treated in partial redistribution and the C II and C IV lines in complete redistribution. Computed line fluxes are presented for a range of models to show the range of permitted temperature structures. A comparison of the Beta Ceti model to models previously computed in a similar way for other stars shows a trend of decreasing chromospheric pressures and increasing geometric scales as single stars evolve across the transition region boundary. The present analysis also suggests that transition region pressures drastically decrease and geometric scales rapidly increase as single giant stars evolve to the right, toward the boudnary. Beta Ceti's exceptional X-ray brightness is discussed.

Eriksson, K.↗

NASA NTRS2015

Utilizing Direct Numerical Simulations of Transition and Turbulence in Design Optimization

Design optimization methods that use the Reynolds-averaged Navier-Stokes equations with the associated turbulence and transition models, or other model-based forms of the governing equations, may result in aerodynamic designs with actual performance levels that are noticeably different from the expected values because of the complexity of modeling turbulence/transition accurately in certain flows. Flow phenomena such as wake-blade interaction and trailing edge vortex shedding in turbines and compressors (examples of such flows) may require a computational approach that is free of transition/turbulence models, such as direct numerical simulations (DNS), for the underlying physics to be computed accurately. Here we explore the possibility of utilizing DNS data in designing a turbine blade section. The ultimate objective is to substantially reduce differences between predicted performance metrics and those obtained in reality. The redesign of a typical low-pressure turbine blade section with the goal of reducing total pressure loss in the row is provided as an example. The basic ideas presented here are of course just as applicable elsewhere in aerodynamic shape optimization as long as the computational costs are not excessive.

Direct numerical simulations of transition and tur↗

NASA NTRS1995

Applying AI tools to operational space environmental analysis

The U.S. Air Force and National Oceanic Atmospheric Agency (NOAA) space environmental operations centers are facing increasingly complex challenges meeting the needs of their growing user community. These centers provide current space environmental information and short term forecasts of geomagnetic activity. Recent advances in modeling and data access have provided sophisticated tools for making accurate and timely forecasts, but have introduced new problems associated with handling and analyzing large quantities of complex data. AI (Artificial Intelligence) techniques have been considered as potential solutions to some of these problems. Fielding AI systems has proven more difficult than expected, in part because of operational constraints. Using systems which have been demonstrated successfully in the operational environment will provide a basis for a useful data fusion and analysis capability. Our approach uses a general purpose AI system already in operational use within the military intelligence community, called the Temporal Analysis System (TAS). TAS is an operational suite of tools supporting data processing, data visualization, historical analysis, situation assessment and predictive analysis. TAS includes expert system tools to analyze incoming events for indications of particular situations and predicts future activity. The expert system operates on a knowledge base of temporal patterns encoded using a knowledge representation called Temporal Transition Models (TTM's) and an event database maintained by the other TAS tools. The system also includes a robust knowledge acquisition and maintenance tool for creating TTM's using a graphical specification language. The ability to manipulate TTM's in a graphical format gives non-computer specialists an intuitive way of accessing and editing the knowledge base. To support space environmental analyses, we used TAS's ability to define domain specific event analysis abstractions. The prototype system defines events covering reports of natural phenomena such as solar flares, bursts, geomagnetic storms, and five others pertinent to space environmental analysis. With our preliminary event definitions we experimented with TAS's support for temporal pattern analysis using X-ray flare and geomagnetic storm forecasts as case studies. We are currently working on a framework for integrating advanced graphics and space environmental models into this analytical environment.

Krajnak, Mike↗

NASA NTRSDate not supplied

The Effect of Trailing Edge Grid Resolution in Large-Eddy Simulations

Ceramic Matrix Composite (CMC) with environmental barrier coating can tolerate significantly higher temperatures compared with the conventional metal alloy blades and thus can help achieve higher thermal efficiency in gas turbine engines. Due to the complex fabrication process of CMC blades, larger blade trailing edge thicknesses and larger leading-edge radii of curvature are expected. These features significantly alter aerodynamic performance especially near the trailing edge and thus the loss profile. In previous studies, the authors used the large eddy simulation (LES) as well as the Reynolds Averaged Navier-Stokes (RANS) coupled with an intermittency function-based transition model to simulate an aerodynamics performance of three different CMC blades and compared the predictions against the data acquired at NASA Glenn Transonic Turbine Blade Cascade Rig. Although we were able to successfully predict different characteristics of aerodynamic performance among three different blades (e.g., pressure loading and integrated losses), LES consistently predicted a small recirculation bubble at the end of the suction side. This was not inconsistent with the physics of the flow, but the pressure loading, locally, near the trailing edge, and as a result, the measured wake profiles did not match the experimental data. To delve further into these issues, a new LES grid with a much finer mesh near the trailing edge was generated where the spanwise extent of the grid was increased by 50%. An LES simulation for the CMC blade with the largest trailing edge thicknesses at the high-freestream turbulence (Tu=13%) condition showed that using such a mesh is necessary for LES to accurately capture the transition phenomena on the suction side. The resulting total pressure coefficient profile and the shift of the wake profile were greatly improved.

CMC↗

NASA NTRSDate not supplied

The Effect of Trailing Edge Grid Resolution in Large-Eddy Simulations

LES↗

DOE OSTI2025

Many-body expansion based machine learning models for octahedral transition metal complexes

Abstract Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol −1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol −1 (i.e. a 0.73 kcal mol −1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.

Meyer, Ralf (ORCID:0000000322360261)↗

DOE OSTI2025

First Measurement of Missing Energy due to Nuclear Effects in Monoenergetic Neutrino Charged-Current Interactions

We present the first measurement of the missing energy due to nuclear effects in monoenergetic, muon neutrino charged-current interactions on carbon, originating from 𝐾 + → 𝜇 + ⁢𝜈 𝜇 decay at rest (𝐸 𝜈 𝜇 = 235.5 MeV), performed with the J-PARC Sterile Neutrino Search at the J-PARC Spallation Neutron Source liquid scintillator based experiment. Toward characterizing the neutrino interaction, ostensibly 𝜈 𝜇 ⁢𝑛 → 𝜇 − ⁢𝑝 or 𝜈 𝜇 ⁢ 12 C → 𝜇 − ⁢ 12 N, we define the missing energy as the energy transferred to the nucleus (𝜔) minus the kinetic energy of the outgoing proton(s), 𝐸 𝑚 ≡ 𝜔−∑ 𝑇 𝑝 , and relate this to visible energy in the detector, 𝐸 𝑚 = 𝐸 𝜈 𝜇 ⁡(235.5 MeV) − 𝑚 𝜇⁡ (105.7 MeV) + [𝑚 𝑛 − 𝑚 𝑝⁡ (1.3 MeV)] − 𝐸 vis . The missing energy, which is naively expected to be zero in the absence of nuclear effects (e.g., nucleon separation energy, Fermi momenta, and final-state interactions), is uniquely sensitive to many aspects of the interaction, and has previously been inaccessible with neutrinos. The shape-only, differential cross section measurement reported, based on a (77 ± 3)% pure double-coincidence kaon decay-at-rest signal (621 total events), provides detailed insight into neutrino-nucleus interactions, allowing even the nuclear orbital shell of the struck nucleon to be inferred. The measurement provides an important benchmark for models and event generators at hundreds of MeV neutrino energies, characterized by the difficult-to-model transition region between neutrino-nucleus and neutrino-nucleon scattering, and relevant for applications in nuclear physics, neutrino oscillation measurements, and Type-II supernova studies.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗