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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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At least 289 records · Page 16

Quantitative measurements of dislocations in metals for advancing predictive simulations

LLNL applications require scientists to predict how materials evolve under various thermomechanical conditions. While this is achieved through physics-based simulations, uncertainty in the predictions of mechanical properties remains a serious challenge that limits the predictive capabilities of models because we lack methods to compare predictions of atomic-scale defects (dislocations) with experimental measurements. High energy X-ray diffraction (HEXRD) is the most relevant technique that can provide the necessary statistical information on dislocations. However, this technique is not yet quantitative because we lack a precise understanding of the relationship between X-ray diffraction patterns and the underlying material dislocation content and arrangements. To address this need, we used our novel computational X-ray diffraction method to simulate the effect of dislocations on the diffraction patterns. We compared virtual and experimental diffraction patterns. Results allowed us to clearly establish the relationship between X-ray diffraction patterns and the underlying dislocation structures, proving that it is feasible to quantitatively measure dislocation statistics with HEXRD. This project delivered a method that can provide the missing piece to LLNL’s mechanical property simulations in advanced metals by obtaining experimentally long-needed quantitative dislocation data, which could fully enable predictive capabilities.

36 MATERIALS SCIENCE↗

Direct Numerical Simulation of a Coolant Jet in a Periodic Crossflow

A Direct Numerical Simulation of a coolant jet injected normally into a periodic crossflow is presented. The physical situation simulated represents a periodic module in a coolant hole array with a heated crossflow. A collocated finite difference scheme is used which is fifth-order accurate spatially and second-order accurate temporally. The scheme is based on a fractional step approach and requires the solution of a pressure-Poisson equation. The simulations are obtained for a blowing ratio of 0.25 and a channel Reynolds number of 5600. The simulations reveal the dynamics of several large scale structures including the Counter-rotating Vortex Pair (CVP), the horse-shoe vortex, the shear layer vortex, the wall vortex and the wake vortex. The origins and the interactions of these vortical structures are identified and explored. Also presented are the turbulence statistics and how they relate to the flow structures.

Sharma, Chirdeep↗

SMC: SCENIC Model Control

NASAs Space Communications and Navigation (SCaN) program manages three active networks: the Near Earth Network, the Space Network, and the Deep Space Network. These networks simultaneously support NASA missions and provide communications services to customers worldwide. To efficiently manage these resources and their capabilities, a team of student interns at the NASA Glenn Research Center is developing a distributed system to model the SCaN networks. Once complete, the system shall provide a platform that enables users to perform capacity modeling of current and prospective missions with finer-grained control of information between several simulation and modeling tools. This will enable the SCaN program to access a holistic view of its networks and simulate the effects of modifications in order to provide NASA with decisional information. The development of this capacity modeling system is managed by NASAs Strategic Center for Education, Networking, Integration, and Communication (SCENIC). Three primary third-party software tools offer their unique abilities in different stages of the simulation process. MagicDraw provides UMLSysML modeling, AGIs Systems Tool Kit simulates the physical transmission parameters and de-conflicts scheduled communication, and Riverbed Modeler (formerly OPNET) simulates communication protocols and packet-based networking. SCENIC developers are building custom software extensions to integrate these components in an end-to-end space communications modeling platform. A central control module acts as the hub for report-based messaging between client wrappers. Backend databases provide information related to mission parameters and ground station configurations, while the end user defines scenario-specific attributes for the model. The eight SCENIC interns are working under the direction of their mentors to complete an initial version of this capacity modeling system during the summer of 2015. The intern team is composed of four students in Computer Science, two in Computer Engineering, one in Electrical Engineering, and one studying Space Systems Engineering.

Simulation↗

Numerical Simulations of a 20-kW Class Hall Thruster Using the Magnetic-Field-Aligned-Mesh Code Hall2De

This paper reports on numerical simulations of the NASA-300M, a 20-kW class Hall thruster developed at the NASA Glenn Research Center (GRC). The numerical simulations have been performed with a 2-D axisymmetric, magnetic field-aligned-mesh (MFAM) plasma solver developed at the Jet Propulsion Laboratory (JPL). The main objective of the collaborative effort is to combine physics-based simulation, plasma diagnostics and recent findings on erosion physics to design and demonstrate a high-power, high-performance Hall thruster that exceeds the life of state-of-the-art Hall thrusters by more than one order of magnitude. The thruster simulations have been carried out at a discharge voltage of 500 V and discharge current of 40 A. The results indicate that although the impact energy of ions may attain values that are comparable to the discharge voltage along the downstream portions of the channel, a withdrawn ionization region and significant ion focusing combine to sustain erosion rates below 1 mm/kh. A more extensive evaluation of the baseline NASA-300M configuration and re-design of this thruster with magnetically shielded walls constitute the main focus of our work in the coming months.

plasma simulations↗

AutonomieAI: An efficient and deployable vehicle energy consumption estimation toolkit

Here, this paper presents AutonomieAI, a novel toolkit designed for efficient energy estimation of vehicles across diverse trip scenarios, routes, and drive cycles, applicable to a broad range of vehicle powertrain technologies. It leverages state-of-the-art Machine Learning techniques to deliver real-time energy prediction of vehicles, enabling co-simulation with transportation level system tools and opening doors for large-scale optimization at city, network or national level. Benchmark results show that AutonomieAI achieves high accuracy, with an average percentage error below 2% for most powertrain types, and computational efficiency capable of processing over 10,000 trips per second. Applications of AutonomieAI have potential to offer the flexibility to assist in solving eco-routing problems, optimize for vehicle and powertrain selection, study charging decision behavior, and optimize for charging station placement. AutonomieAI is the result of large neural network based model architectures, trained on very large and unique high fidelity vehicle simulation data. It is lightweight, deployable, efficient and has accuracy comparable to specialized and complex physics based simulation softwares.

Autonomie↗

A Framework for Optimization-Based ISRU Tool Design Using Discrete Element Modeling

Novel robotic excavation technologies are needed to perform in-situ resource utilization (ISRU) tasks at levels required to sustain a long-term presence on the lunar surface. Developing and testing multiple iterations of functional hardware is time and cost prohibitive, thus slowing down the pace of progress and delaying humanity’s settlement of the Moon. High-fidelity, physics-based simulation can reduce the time and effort required to develop and deploy robotic systems [1]. We have adopted this approach to create high-fidelity models of robotic test hardware to enable rapid virtual design and optimization of excavation technologies [2]. Such models can leverage modern computational tools like Discrete Element Method (DEM) simulations that can be coupled with automated design approaches like topology optimization to reduce the amount of prototyping and physical testing needed to realize useful tools.

ISRU↗

Expanding the representation of aerosol, cloud, and precipitation processes with graph network-based simulators

We explored a novel framework for simulating the small-scale processes that drive the evolution of aerosol, cloud, and precipitation particles, which are a critical gap in the predictive understanding of weather and climate. Particle-based methods have emerged as an effective tool for modeling aerosol-cloud-precipitation interactions, but existing particle-based models are computationally too expensive to simulate the large domains relevant for the atmosphere or to represent the full suite of relevant processes. The lack of a comprehensive and efficient reference model is a critical bottleneck in our understanding of cloud and precipitation processes and our ability to parameterize these processes for regional- and global-scale simulations. To address this need, we explored an approach to accelerate and expand particle-based models using a new machine learning approach, graph network-based simulators (GNS). Rather than modeling the evolution of the system by numerically integrating continuity equations, the GNS represents dynamics through learned message passing. Our aim was to develop fast and accurate surrogate models for particle-based simulations. We explored applying GNS to simulate cloud droplet transport, growth, and evaporation under turbulent conditions, but we found the GNS over-smoothed the simulations. We then applied the GNS to simulate aerosol dynamics through gas condensation and found the GNS was able to reproduce the benchmark, physics-based simulation with high accuracy.

54 ENVIRONMENTAL SCIENCES↗

An experimental study of jet exhaust simulation

Afterbody drag predictions for jet aircraft are usually made experimentally with the jet exhaust flow simulated. The physical gas properties of the fluid used for the model jet exhaust can affect the accuracy of simulation of the airplane's jet exhaust plume. The effect of the accuracy of this simulation on afterbody drag was investigated by wind-tunnel tests with single engine model. In addition to unheated air as the exhaust gas, the decomposition products of three different concentrations of hydrogen peroxide were utilized. The air jet simulation consistently resulted in higher boattail drag than hydrogen peroxide simulation. The differences in drag for the various exhaust gases are attributed to different plume shapes and entrainment properties of the gases. The largest differences in drag due to exhaust gas properties were obtained for the combination of high transonic Mach numbers and high boattail angles. For these conditions, the current data indicate that the use of air to simulate a nonafterburning turbojet exhaust can result in an increase in afterbody amounting to 20 percent of the nonafterburning turbojet value.

Compton, W. B., III↗

Development of Standardized Lunar Regolith Simulant Materials

Lunar exploration requires studies using standardized testing procedures. Previous lunar simulants focused on physical aspects of the lunar regolith. Renewed lunar exploration requires standardized lunar regolith simulant (SLRS) materials that simulate the physical, chemical, and mineralogical properties of the regolith [l]. A root simulant models an end-member, and a derivative is formed by addition of material [2]. The 2005 Workshop recommended a low-Ti mare basalt and a high-Ca highland anorthosite set of roots. Derivatives involve addition of ilmenite and glassy agglutinates [3]. An ideal SLRS material is homogeneous. Geochemical standards are finely-ground to reduce chemical variability, but lunar simulants have a grain size variation and mineralogy that must match the lunar regolith. The simulant homogeneity is monitored using major, minor, and trace element data of progressively smaller samples compared to bulk material. Both chemical and geotechnical properties depend on the contrast from grain to grain. The variability of simulant material is an inherent property that must be taken into account. Simulant production requires monitoring of adherence to simulant requirements and homogeneity during production. Quality control establishes a traceability to a master set of reference standards.

Carpenter, P.↗

Characteristics of flight simulator visual systems

The physical parameters of the flight simulator visual system that characterize the system and determine its fidelity are identified and defined. The characteristics of visual simulation systems are discussed in terms of the basic categories of spatial, energy, and temporal properties corresponding to the three fundamental quantities of length, mass, and time. Each of these parameters are further addressed in relation to its effect, its appropriate units or descriptors, methods of measurement, and its use or importance to image quality.

Statler, I. C.↗

Next Generation Simulation Framework for Robotic and Human Space Missions

The Dartslab team at NASA's Jet Propulsion Laboratory (JPL) has a long history of developing physics-based simulations based on the Darts/Dshell simulation framework that have been used to simulate many planetary robotic missions, such as the Cassini spacecraft and the rovers that are currently driving on Mars. Recent collaboration efforts between the Dartslab team at JPL and the Mission Operations Directorate (MOD) at NASA Johnson Space Center (JSC) have led to significant enhancements to the Dartslab DSENDS (Dynamics Simulator for Entry, Descent and Surface landing) software framework. The new version of DSENDS is now being used for new planetary mission simulations at JPL. JSC is using DSENDS as the foundation for a suite of software known as COMPASS (Core Operations, Mission Planning, and Analysis Spacecraft Simulation) that is the basis for their new human space mission simulations and analysis. In this paper, we will describe the collaborative process with the JPL Dartslab and the JSC MOD team that resulted in the redesign and enhancement of the DSENDS software. We will outline the improvements in DSENDS that simplify creation of new high-fidelity robotic/spacecraft simulations. We will illustrate how DSENDS simulations are assembled and show results from several mission simulations.

Dartslab↗

Heterogeneous Computing

To leverage the increasing heterogeneity in modern computing resources, Geant4 incorporates advanced software tools and a task-based framework (G4Tasking) that enables efficient parallelism at event, sub-event, and track levels. Ongoing R&D efforts focus on integrating GPUs into high-energy physics (HEP) simulations, including optical photon simulation with Opticks/NVIDIA OptiX, offloading electromagnetic particle transport using G4HepEM/AdePT and Celeritas, and employing advanced surface-based geometry models such as VecGeom2.0 and ORANGE. As Geant4 continues evolving toward high-performance computing (HPC) and heterogeneous architectures, it remains a key tool for large-scale simulations in HEP and beyond.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Investigation of Drift Effects in UEDGE Simulations of NSTX-U Edge Plasma With Lithium Divertors

Lithium is a low-Z material, and lithium-based plasma-facing components (PFCs) are planned for the National Spherical Torus Experiment Upgrade (NSTX-U) to explore potential benefits for divertor power exhaust and core plasma management. NSTX-U is a medium-sized spherical tokamak with up to 12 MW of auxiliary heating, capable of generating reactor-relevant plasma conditions. This work presents boundary plasma simulations for NSTX-U with lithium PFCs using the UEDGE code, incorporating full magnetic and 𝐄 ×𝐁 drift physics. The simulations show that drifts strongly influence heat and particle transport: they enhance convective transport, broaden the scrape-off layer heat-flux width 𝜆 𝑞 , and reduce the anomalous heat diffusivity 𝜒 required to reproduce predicted SOL heat-flux width. 𝐄 ×𝐁 drifts provide poloidal transport, while ∇𝐵 (which includes both gradB and curvature) drifts provide radial heat and particle transport. Lithium transport is also affected by drifts, with lithium ions migrating from the outer divertor to the inner divertor through the private flux region (PFR) following the 𝐄 ×𝐁 drifts flow, lowering upstream impurity lithium densities. UEDGE is self-consistently coupled with the Wall-Li model to study plasma lithium PFC interactions depending on the local lithium sourcing based on local plasma conditions and lithium surface temperature. In these simulations, lithium evaporation shows a vapor-shielding effect that reduces divertor heat flux and increases radiative losses once surface temperatures exceed 450°C. This research work provides a first step toward self-consistent modeling of lithium PFCs in NSTX-U, demonstrating the impact of drift-driven plasma transport in SOL and divertor regions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

An investigation of bleed configurations and their effect on shock wave/boundary layer interactions

The design of high efficiency supersonic inlets is a complex task involving the optimization of a number of performance parameters such as pressure recovery, spillage, drag, and exit distortion profile, over the flight Mach number range. Computational techniques must be capable of accurately simulating the physics of shock/boundary layer interactions, secondary corner flows, flow separation, and bleed if they are to be useful in the design. In particular, bleed and flow separation, play an important role in inlet unstart, and the associated pressure oscillations. Numerical simulations were conducted to investigate some of the basic physical phenomena associated with bleed in oblique shock wave boundary layer interactions that affect the inlet performance.

Hamed, Awatef↗

Model-free estimation of completeness, uncertainties, and outliers in atomistic machine learning using information theory

Abstract An accurate description of information is relevant for a range of problems in atomistic machine learning (ML), such as crafting training sets, performing uncertainty quantification (UQ), or extracting physical insights from large datasets. However, atomistic ML often relies on unsupervised learning or model predictions to analyze information contents from simulation or training data. Here, we introduce a theoretical framework that provides a rigorous, model-free tool to quantify information contents in atomistic simulations. We demonstrate that the information entropy of a distribution of atom-centered environments explains known heuristics in ML potential developments, from training set sizes to dataset optimality. Using this tool, we propose a model-free UQ method that reliably predicts epistemic uncertainty and detects out-of-distribution samples, including rare events in systems such as nucleation. This method provides a general tool for data-driven atomistic modeling and combines efforts in ML, simulations, and physical explainability.

36 MATERIALS SCIENCE↗

Empirical Scaling Laws of Rocket Exhaust Cratering

When launching or landing a space craft on the regolith of a terrestrial surface, special attention needs to be paid to the rocket exhaust cratering effects. If the effects are not controlled, the rocket cratering could damage the spacecraft or other surrounding hardware. The cratering effects of a rocket landing on a planet's surface are not understood well, especially for the lunar case with the plume expanding in vacuum. As a result, the blast effects cannot be estimated sufficiently using analytical theories. It is necessary to develop physics-based simulation tools in order to calculate mission-essential parameters. In this work we test out the scaling laws of the physics in regard to growth rate of the crater depth. This will provide the physical insight necessary to begin the physics-based modeling.

Donahue, Carly M.↗

Nonequilibrium, large-amplitude MHD fluctuations in the solar wind

Compressible MHD simulations in one dimension with three-dimensional vectors are used to investigate a number of processes relevant to problems in interplanetary physics. The simulations indicate that a large-amplitude nonequilibrium (e.g., linearly polarized) Alfvenic wave, which always starts with small relative fluctuations in the magnitude B of the magnetic field, typically evolves to flatten the magnetic profile in most regions. Under a wide variety of conditions B and the density rho become anticorrelated on average. If the mean magnetic field is allowed to decrease in time, the point where the transverse magnetic fluctuation amplitude delta B(sub T) is greater than the mean field B(sub 0) is not special, and large values of delta B(sub T)/B(sub 0) do not cause the compressive thermal energy to increase remarkably or the wave energy to dissipate at an unusually high rate. Nor does the 'backscatter' of the waves that occurs when the sound speed is less than the Alfven speed result, in itself, in substantial energy dissipation, but rather primarily in a phase change between the magnetic and velocity fields. For isolated wave packets the backscatter does not occur for any of the parameters examined; an initial radiation of acoustic waves away from the packet establishes a stable traveling structure. Thus these simulations, although greatly idealized compared to reality, suggest a picture in which the interplanetary fluctuations should have small deltaB and increasingly quasi-pressure balanced compressive fluctuations, as observed, and in which the dissipation and 'saturation' at delta B(sub T)/B(sub 0) approximately = 1 required by some theories of wave acceleration of the solar wind do not occur. The simulations also provide simple ways to understand the processes of nonlinear steepening and backscattering of Alfven waves and demonstrate the existence of previously unreported types of quasi-steady MHD states.

Roberts, D. Aaron↗

Simulating nonlinear optical processes on a superconducting quantum device

Simulating plasma physics on quantum computers is difficult because most problems of interest are nonlinear, but quantum computers are not naturally suitable for nonlinear operations. In weakly nonlinear regimes, plasma problems can be modelled as wave–wave interactions. In this paper, we develop a quantization approach to convert nonlinear wave–wave interaction problems to Hamiltonian simulation problems. We demonstrate our approach using two qubits on a superconducting device. Unlike a photonic device, a superconducting device does not naturally have the desired interactions in its native Hamiltonian. Nevertheless, Hamiltonian simulations can still be performed by decomposing required unitary operations into native gates. To improve experimental results, we employ a range of error-mitigation techniques. Apart from readout error mitigation, we use randomized compilation to transform undiagnosed coherent errors into well-behaved stochastic Pauli channels. Moreover, to compensate for stochastic noise, we rescale exponentially decaying probability amplitudes using rates measured from cycle benchmarking. We carefully consider how different choices of product-formula algorithms affect the overall error and show how a trade-off can be made to best utilize limited quantum resources. This study provides an example of how plasma problems may be solved on near-term quantum computing platforms.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗