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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1991

Recent rotorcraft aeroelastic testing in the Langley Transonic Dynamics Tunnel

Wind-tunnel testing of a properly scaled aeroelastic model helicopter rotor is considered a necessary phase in the design and development of new rotor systems. For this reason, extensive testing of aeroelastically scaled model rotors is done in the Transonic Dynamics Tunnel (TDT) located at the Langley Research Center. A unique capability of this facility, which enables proper dynamic scaling, is the use of diflourodichloromethane, or Refrigerant-12 (R-12) as a test medium. The paper presents a description of the TDT and a discussion of the benefits of using R-12 as a test medium. A description of the system used to conduct model tests is provided and examples of recent rotor tests are cited to illustrate the types of aeroelastic model rotor tests conducted in the TDT.

Yeager, William T., Jr.↗

NASA NTRS2013

Multi-Scale Dynamics, Control, and Simulation of Granular Spacecraft

In this paper, we present some ideas regarding the modeling, dynamics and control aspects of granular spacecraft. Granular spacecraft are complex multibody systems composed of a spatially disordered distribution of a large number of elements, for instance a cloud of grains in orbit. An example of application is a spaceborne observatory for exoplanet imaging, where the primary aperture is a cloud instead of a monolithic aperture. A model is proposed of a multi-scale dynamics of the grains and cloud in orbit, as well as a control approach for cloud shape maintenance and alignment, and preliminary simulation studies are carried out for the representative imaging system.

granular media↗

DOE OSTI2025

Dynamic Surface Restructuring in Cu(Au) Alloys Driven by Oxygen-Mediated Au Mobility

Alloying plays a crucial role in tuning the surface properties of metals, but the atomic-level mechanisms by which alloying elements influence surface structure dynamics under reactive conditions remain elusive. Using Cu(Au) in oxidizing environments as a model system, we reveal a dynamic oxygen-induced transformation of the topmost atomic layer into a periodically hill-and-valley morphology with reversible switching between undulated and flattened surface states. These interconversions are driven by the retreat of surface Au to the subsurface during oxygen adsorption and its resegregation to the surface upon oxygen desorption. This cyclical mobility establishes a feedback loop, allowing the surface to dynamically reconfigure in response to changes in the oxygen pressure. The results offer a broadly applicable framework for understanding atomic-scale surface restructuring in alloy systems, where differences in the chemical reactivity of alloying elements drive dynamic redistribution between surface and subsurface regions. As a result, this dynamic coupling has practical implications for designing corrosion-resistant coatings and metastable nanostructures with tunable catalytic properties.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS2020

An Electrical Modeling and Thermal Analysis Toolbox for Electrified Aircraft Propulsion Simulation

A simulation toolbox has been developed to model the electrical portions of Electrified Aircraft Propulsion (EAP) systems, including self-heating of electrical systems. Dynamic models of EAP systems often include turbomachinery, an electrical power system, and a thermal management system. These portions of the propulsion system can operate on timescales covering six orders of magnitude, which poses a challenging modeling task. Assumptions and approximations are made in an effort to capture the dynamics relevant to engine, electrical system, and thermal system interactions, while still allowing for fast simulations. These assumptions and approximations enable the electrical component models to run at the time scale of the turbomachinery, neglecting the very high frequency electrical dynamics, while demonstrating representative behavior of the end-to-end system. Thus the models execute in an acceptable time frame for what would otherwise be an extremely stiff simulation. The resulting simulations of EAP systems are appropriate for system-level control design and analysis. The objective of this paper is to present an overview of the Electrical Modeling and Thermal Analysis Toolbox (EMTAT). It will describe some of the approximations made to accommodate rapid execution, and some of the design tools that allow matching the model to component specifications. This paper will also provide some examples of EAP system modeling using EMTAT.

Mark E Bell↗

NASA NTRS2020

An Electrical Modeling and Thermal Analysis Toolbox for Electrified Aircraft Propulsion Simulation

Mark E Bell↗

NASA NTRS2020

Electrical Modeling and Thermal Analysis Toolbox (EMTAT) User’s Guide

A simulation toolbox has been developed to model the electrical portions of Electrified Aircraft Propulsion (EAP) systems, including self-heating of electrical systems. Dynamic models of EAP systems often include turbomachinery, an electrical power system, and a thermal management system. These portions of the propulsion system can operate on timescales covering six orders of magnitude, which poses a challenging modeling task. Assumptions and approximations are made in an effort to capture the dynamics relevant to engine, electrical system, and thermal system interactions, while still allowing for fast simulations. These assumptions and approximations enable the electrical component models to run at the time scale of the turbomachinery, neglecting the very high frequency electrical dynamics, while demonstrating representative behavior of the end-to-end system. Thus the models execute in an acceptable time frame for what would otherwise be an extremely stiff simulation. The resulting simulations of EAP systems are appropriate for system-level control design and analysis. The objective of this User's Guide is to present an overview of the usage of the Electrical Modeling and Thermal Analysis Toolbox (EMTAT). It will describe some of the approximations made to accommodate rapid execution, and some of the design tools that allow matching the model to component specifications. This paper will describe the basic usage of the software toolbox, and also provide an example of EAP system modeling using EMTAT.

Mark E. Bell↗

NASA NTRSDate not supplied

Predicting Orion Launch Abort Acoustics

Computational fluid dynamics (CFD) scale-resolving simulations were performed to help assess the Orion launch abort system’s vibro-acoustic environment in collaboration with the Orion Loads and Dynamics team at the Johnson Space Center (JSC). The primary objectives are to establish best practices and to validate CFD predictions for surface fluctuating pressure spectra with ground, wind tunnel, and flight test data. Excellent agreement is obtained between CFD predictions by the Cartesian adaptive mesh refinement (AMR) module of the Launch, Ascent, and Vehicle Aerodynamics (LAVA) solver and measurements from a ground test representative of the start of a pad abort scenario, and with measurements from a wind tunnel test case corresponding to a transonic, high total angle of attack ascent abort scenario. A simplified (static and at rest) simulation of a pad abort flight test shows good agreement with the flight data, whereas a more costly simulation where the vehicle is accelerating relative to the ground from rest to Mach 0.4 shows consistent over-prediction of the spectra. Simulation results for a supersonic ascent abort flight test are in reasonable agreement with the measurements, but show larger excursions in regions where non-linear interactions between the plume turbulence, shocks, and turbulent boundary layer are strongest – likely due to CFD modeling assumptions, the effect of which are discussed. Overall, the CFD results demonstrate that scale-resolving simulation methodologies like the one presented can help characterize full-scale launch abort vehicle near-field noise and can complement wind tunnel, ground and flight tests by providing trends and reducing uncertainty for scenarios that cannot or are not planned to be tested.

Orion↗

NASA NTRS2025

CFD Validation and Scaling of a Condenser Used in an ISRU Propellant Production System

This work develops a Computational Fluid Dynamics (CFD) model of a Commercial-Off-The-Shelf (COTS) condenser used for ground-based testing of an In-Situ Resource Utilization (ISRU) propellant production system. STAR-CCM+ was used to simulate water condensing through the condenser downstream of a methanation reactor. The computational data of the digital model is validated with test cases using nitrogen and water in ambient conditions. After validation with the test data, the digital model can be used to predict scale at higher production targets. The StarCCM+ simulation of the digital model shows good agreement with the test data provided. From the simulation, the condensation rate calculated was 18.3 g/hr and the process gas mass flow rate was 709.2 g/hr. The test data measured an average 16.9 g/hr condensation rate and 693.6 g/hr process gas mass flow rate. The simulation shows a 7.3% error in the water condensation and 2.2% error in the process gas at the outlet.

Condenser↗

DOE OSTI2020

Nonadiabatic Energy Fluctuations of Scale-Invariant Quantum Systems in a Time-Dependent Trap

We consider the nonadiabatic energy fluctuations of a many-body system in a time-dependent harmonic trap. In the presence of scale-invariance, the dynamics becomes self-similar and the nondiabatic energy fluctuations can be found in terms of the initial expectation values of the second moments of the Hamiltonian, square position, and squeezing operators. Nonadiabatic features are expressed in terms of the scaling factor governing the size of the atomic cloud, which can be extracted from time-of-flight images. We apply this exact relation to a number of examples: the single-particle harmonic oscillator, the one-dimensional Calogero-Sutherland model, describing bosons with inverse-square interactions that includes the non-interacting Bose gas and the Tonks-Girdardeau gas as limiting cases, and the unitary Fermi gas. We illustrate these results for various expansion protocols involving sudden quenches of the trap frequency, linear ramps and shortcuts to adiabaticity. Our results pave the way to the experimental study of nonadiabatic energy fluctuations in driven quantum fluids.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

Understanding flow dynamics in membrane distillation: Effects of reactor design on polarization

Optimization and design of full-scale membrane distillation (MD) systems usually require Sherwood and Nusselt correlations that are developed from lab-scale systems. However, entrance effects in lab-scale systems can significantly impact heat, mass and momentum transfer in the reactor, therefore affect the accuracy of the developed experimental Sherwood and Nusselt correlations. Here, Computational Fluid Dynamics (CFD) simulations using OpenFOAM are performed to understand the effects of right-angled bends and inlet design on flow dynamics, temperature and concentration polarization in MD systems. Simulation results show that the presence of right-angled bends and inlets with sudden expansions lead to the formation of Dean vortices. Dean vortices enhance perpendicular mixing in MD systems and reduce both temperature and concentration polarization. Temperature and concentration polarization coefficients in MD systems with right-angled bends and inlets with sudden expansions vary significantly for the same volumetric flow rate. Our studies show that lab-scale systems with the same volumetric flow rate but different designs lead to significantly different Nusselt and Sherwood correlations. Here, this study demonstrates the importance of CFD-informed design of lab-scale systems to minimize entrance effects and suppress Dean vortices for consistent model development and calibration across multiple scales.

42 ENGINEERING↗

DOE OSTI2023

Understanding Dynamics and Thermodynamics of ENSO and Its Complexity Simulated by E3SM and Other Climate Models

Despite the seeming success of most state-of-the-art climate models in simulating the El Niño-Southern Oscillation (ENSO), there is strong evidence that models achieve realistic levels of ENSO activity do so often for wrong reasons. This is owing to an often occurred near cancelation of large errors in terms of contributions to ENSO growth rate from coupled dynamic and thermodynamic feedback processes. Climate models remain deficient in simulating the observed ENSO’s spatial and temporal complexity that involves interplays of coupled dynamic and thermodynamic feedbacks, interactions across multiple scales, nonlinear processes in the tropical atmosphere and ocean system, biases in mean sate and physical processes, and influences external to equatorial Pacific coupled ENSO dynamics. Our proposed research aims at advancing predictive and process-level understandings of ENSO simulated in E3SM and other climate models under current and future climate conditions with two main objectives: (i) better understanding the aforementioned broad range interactive processes and sources that control fundamental properties of ENSO in E3SM and CIMP6 outputs as well as in observational (reanalysis) data sets, using a hierarchical of coupled dynamical frameworks consisting of theoretical analysis, intermediate complexity modeling, and coupled dynamic diagnostics; (ii) to use this understanding to explore pathways towards improving E3SM’s capability of simulating ENSO and its complexity. More specifically, we will focus on four main thrusts of research: (1) ENSO’s dynamic and thermodynamic feedbacks; (2) the across-scale interactions of ENSO with annual cycle and MJO/WWB/TIW (Madden Julian Oscillation/Westerly Wind Burst/Tropical Instability Wave) activity; (3) key nonlinear processes of ENSO involving atmospheric convective thresholds, nonlinear ocean dynamic heating, and thermocline outcropping; and (4) the impacts of climate mean-state biases/changes and perturbed physical processes on simulated ENSO and its complexity.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

First-Principles-Based Machine Learning Models for Phase Behavior and Transport Properties of CO 2

In this work, we construct distinct first-principles-based machine-learning models of CO 2 , reproducing the potential energy surface of the PBE-D3, BLYP-D3, SCAN and SCAN-rvv10 approximations of density functional theory. Here we employ the Deep Potential methodology to develop the models and consequently achieve a significant computational efficiency over ab initio molecular dynamics (AIMD) that allows for larger system sizes and time scales to be explored. Although our models are trained only with liquid phase configurations, they are able to simulate a stable interfacial system and predict vapor-liquid equilibrium properties, in good agreement with results from the literature. Because of the computational efficiency of the models, we are also able to obtain transport properties, such as viscosity and diffusion coefficients. We find that the SCAN-based model presents a temperature shift in the position of the critical point, while the SCAN-rvv10-based model shows improvement but still exhibits a temperature shift that remains approximately constant for all properties investigated in this work. We find that the BLYP-D3-based model generally performs better for liquid phase and vapor-liquid equilibrium properties, but the PBE-D3-based model is better suited for predicting transport properties.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS1987

Visual display and alarm system for wind tunnel static and dynamic loads

A wind tunnel balance monitor and alarm system developed at NASA Ames Research Center will produce several beneficial results. The costs of wind tunnel delays because of inadvertent balance damage and the costs of balance repair or replacement can be greatly reduced or eliminated with better real-time information on the balance static and dynamic loading. The wind tunnel itself will have enhanced utility with the elimination of overly cautious limits on test conditions. The microprocessor-based system features automatic scaling and 16 multicolored LED bargraphs to indicate both static and dynamic components of the signals from eight individual channels. Five individually programmable alarm levels are available with relay closures for internal or external visual and audible warning devices and other functions such as automatic activation of external recording devices, model positioning mechanisms, or tunnel shutdown.

Hanly, Richard D.↗

NASA NTRS1987

Visual display and alarm system for wind tunnel static and dynamic loads

Hanly, Richard D.↗

NASA NTRS2009

Ares I Stage Separation System Design Certification Testing

NASA is committed to the development of a new crew launch vehicle, the Ares I, that can support human missions to low Earth orbit (LEO) and the moon with unprecedented safety and reliability. NASA's Constellation program comprises the Ares I and Ares V launch vehicles, the Orion crew vehicle, and the Altair lunar lander. Based on historical precedent, stage separation is one of the most significant technical and systems engineering challenges that must be addressed in order to achieve this commitment. This paper surveys historical separation system tests that have been completed in order to ensure staging of other launch vehicles. Key separation system design trades evaluated for Ares I include single vs. dual separation plane options, retro-rockets vs. pneumatic gas actuators, small solid motor quantity/placement/timing, and continuous vs. clamshell interstage configuration options. Both subscale and full-scale tests are required to address the prediction of complex dynamic loading scenarios present during staging events. Test objectives such as separation system functionality, and pyroshock and debris field measurements for the full-scale tests are described. Discussion about the test article, support infrastructure and instrumentation are provided.

Mayers, Stephen L.↗

DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Coarsening dynamics of Ising-nematic order in a frustrated Heisenberg antiferromagnet

We study the phase ordering dynamics of the classical antiferromagnetic 𝐽 1 −𝐽 2 (nearest-neighbor and next-nearest-neighbor couplings) Heisenberg model on the square lattice in the strong frustration regime (𝐽 2 /𝐽 1 > 1/2). While thermal fluctuations preclude any long-range magnetic order at finite temperatures, the system exhibits a long-range spin-driven nematic phase at low temperatures. The transition into the nematic phase is further shown to belong to the two-dimensional Ising universality class based on the critical exponents near the phase transition. Our large-scale stochastic Landau-Lifshitz-Gilbert simulations find a two-stage phase ordering when the system is quenched from a high-temperature paramagnetic state into the nematic phase. In the early stage, collinear alignments of spins lead to a locally saturated Ising-nematic order. Once domains of well-defined Ising order are developed, the late-stage relaxation is dominated by curvature-driven domain coarsening, as described by the Allen-Cahn equation. The characteristic size of Ising-nematic domains scales as the square root of time, similar to the kinetic Ising model described by the time-dependent Ginzburg-Landau theory. Our results confirm that the late-stage ordering kinetics of the spin-driven nematic, which is a vestigial order of the frustrated Heisenberg model, belongs to the dynamical universality class of a nonconserved Ising order. Interestingly, the system shows no violation of the superuniversality hypothesis under weak bond disorder. The dynamic scaling invariance is preserved in the presence of weak bond disorder. Here, we also discuss possible applications of our results to materials for which vestigial Ising-nematic order is realized.

Antiferromagnets↗

NASA NTRS2009

Multiscale Cloud System Modeling

The central theme of this paper is to describe how cloud system resolving models (CRMs) of grid spacing approximately 1 km have been applied to various important problems in atmospheric science across a wide range of spatial and temporal scales and how these applications relate to other modeling approaches. A long-standing problem concerns the representation of organized precipitating convective cloud systems in weather and climate models. Since CRMs resolve the mesoscale to large scales of motion (i.e., 10 km to global) they explicitly address the cloud system problem. By explicitly representing organized convection, CRMs bypass restrictive assumptions associated with convective parameterization such as the scale gap between cumulus and large-scale motion. Dynamical models provide insight into the physical mechanisms involved with scale interaction and convective organization. Multiscale CRMs simulate convective cloud systems in computational domains up to global and have been applied in place of contemporary convective parameterizations in global models. Multiscale CRMs pose a new challenge for model validation, which is met in an integrated approach involving CRMs, operational prediction systems, observational measurements, and dynamical models in a new international project: the Year of Tropical Convection, which has an emphasis on organized tropical convection and its global effects.

Tao, Wei-Kuo↗