Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “accelerator modeling”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22

DE1 observations of polar O(+) stream bulk parameters and comparison with a model of the centrifugally-accelerated polar wind

A survey of bulk parameters of analyzable O(+) outward streams in the midaltitude (3-4.7 R(sub E) geocentric distance) polar cap magnetosphere is obtained from measurments by the Retarding Ion Mass Spectrometer (RIMS) aboard the Dynamics Explorer 1 (DE1) spacecraft. There is wide scatter in the obtained densities, but they do display discernible trends: the average O(+) density in these decreases from about 30 ions/cu cm at 3.5 R(sub E) to about 1 ion/cu cm at 4.6 R(sub E). The streaming velocities are somewhat more defined, and their average increases from about 8 km/s at 3.5 R(sub E) to about 12 km/s at 4 R(sub E). The outward ion flux increases by a factor of 4 with magnetic activity from K(sub p) = 2 to 5. We have further compared these observational trends with model profiles for the centrifugally-accelerated polar wind as recently described by Horwitz et al. (1994). The large outflow velocities observed can be understood in part as centrifugally-driven by convection with ionospheric electric field magnitudes of the order 50-70 mV/m, purhaps including plasma expansion effects.

Wing Ho, C.↗

Matrix Approach to Land Carbon Cycle Modeling

Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin-up of land carbon cycle models by tens of times. The accelerated spin-up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever-increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle.

54 ENVIRONMENTAL SCIENCES↗

On the possibility of footprint compression with one lens in nonlinear accelerator lattice

Electromagnetic interaction of colliding beams along with other nonlinear fields often limits the beams' lifetimes and luminosities. Nonlinearities result in the spread of betatron frequencies (footprint) and, thus, may enhance dynamic diffusion of particles due to high order resonances. One of the possible ways to eliminate nonlinearities and overcome the corresponding difficulties is compensation of nonlinear forces, but, in practice, it is hardly possible to obtain exact linearity of the system. The compensation with a single nonlinear lens cannot cope with distributed nonlinearities, nonlinearities due to parasitic crossings, etc. Here, we present a method to compute parameters of nonlinear element (lens) that eliminates both the footprint and resonance strength without achieving full compensation.

43 PARTICLE ACCELERATORS↗

Diffusive shock acceleration - Comparison of a unified shock model to bow shock observations

A comparison is made between recent AMPTE/IRM observations of diffuse ions detected upstream of the earth's bow shock when the interplanetary magnetic field was nearly parallel to the solar wind direction and a known collisionless quasi-parallel shock model. These observations, which provide the proton spectrum for all of velocity space, give a direct measure of the shock acceleration efficiency and show how thermal solar winds are injected into the diffusive shock acceleration mechanism. The model accurately describes the proton spectrum; moreover, it predicts the shock structure, the complete particle spectrum, the relative velocity distributions of different ion species in the down stream region, and the enhancement of heavy ions over protons relative to the unshocked solar wind.

Ellison, Donald C.↗

Dynamic Finite Element Predictions for Mars Sample Return Cellular Impact Test #4

The nonlinear, transient dynamic finite element code, MSC.Dytran, was used to simulate an impact test of an energy absorbing Earth Entry Vehicle (EEV) that will impact without a parachute. EEVOs are designed to return materials from asteroids, comets, or planets for laboratory analysis on Earth. The EEV concept uses an energy absorbing cellular structure designed to contain and limit the acceleration of space exploration samples during Earth impact. The spherical shaped cellular structure is composed of solid hexagonal and pentagonal foam-filled cells with hybrid graphite-epoxy/Kevlar cell walls. Space samples fit inside a smaller sphere at the center of the EEVOs cellular structure. Pre-test analytical predictions were compared with the test results from a bungee accelerator. The model used to represent the foam and the proper failure criteria for the cell walls were critical in predicting the impact loads of the cellular structure. It was determined that a FOAM1 model for the foam and a 20% failure strain criteria for the cell walls gave an accurate prediction of the acceleration pulse for cellular impact.

Fasanella, Edwin L.↗

Numerical modeling of a proton spin-flipping system in the spin transparency mode at an integer spin resonance in JINR's Nuclotron

In this paper we propose a lattice insertion for the Nuclotron ring called a “spin navigator” that can adjust any direction of the proton polarization in the orbital plane using weak solenoids. The polarization control is realized in the spin transparency mode at the energy of 108 MeV, which corresponds to the integer spin resonance γ G = 2. The requirements on the navigator solenoid fields are specified considering the criteria for stability of the spin motion during any manipulation of the polarization direction in an experiment. Additionally, this paper presents the results of numerical modeling of the proton spin dynamics in the Nuclotron ring operated in the spin transparency mode. The verified spin navigator is aimed at an experimental study of a spin-flipping system using the Nuclotron ring. The results are relevant to the NICA (JINR), EIC (BNL) and COSY (FZJ) facilities where the spin transparency mode can be applied for polarization control.

47 OTHER INSTRUMENTATION↗

Accelerating scientific discoveries through data-driven innovations

Developing artificial intelligence (AI) and machine learning (ML) methods that can accelerate scientific discoveries and advance science has become one of the important research directions for the AI/ML research community. It has been gaining increasing attention from researchers in diverse scientific areas, including biomedical science, materials science, climate science, physics, chemistry, and many others. Data-driven AI/ML innovations to enable reliable predictions and optimal decision making for scientific discoveries face several critical challenges, among which are high system complexity, large search space, incomplete knowledge, and small data, all of which demand novel strategies to effectively address them. Meeting these challenges and thereby accelerating scientific discoveries and industrial innovations, calls for research that can take full advantage of the latest advances in AI/ML to integrate data-driven techniques with scientific knowledge and is able to execute them in modern high-performance computing (HPC) environments at scale. This Patterns special collection "Accelerating scientific discoveries through data-driven innovations" features articles that showcase the promising roles of AI/ML and data-driven modeling in accelerating scientific discoveries and may inspire the next wave of data-driven innovations in various scientific domains.

97 MATHEMATICS AND COMPUTING↗

A feasibility study of a hypersonic real-gas facility

A four month feasibility study of a hypersonic real-gas free flight test facility for NASA Langley Research Center (LARC) was performed. The feasibility of using a high-energy electromagnetic launcher (EML) to accelerate complex models (lifting and nonlifting) in the hypersonic, real-gas facility was examined. Issues addressed include: design and performance of the accelerator; design and performance of the power supply; design and operation of the sabot and payload during acceleration and separation; effects of high current, magnetic fields, temperature, and stress on the sabot and payload; and survivability of payload instrumentation during acceleration, flight, and soft catch.

Gully, J. H.↗

A generalizable machine learning-assisted fast Fourier transform algorithm to simulate the large strain phenomena in polycrystalline materials

Machine learning methods have shown initial promise in constitutive modeling for single crystals or homogenized polycrystals, delivering notable computational efficiency. However, existing machine learning-based constitutive models often lack generalizability, limiting their application across diverse boundary value problems. This study introduces a thermodynamics-informed artificial neural network model to accelerate rate-tangent crystal plasticity fast Fourier transform simulations for cross-scale deformation behaviors of polycrystals under complex loading. Our model integrates microstructural variability and local interactions effectively. To address local effects in each grain, we employ K-means clustering to group Gauss points within the microstructure into clusters assumed to be in similar mechanical states. This approach, based on self-clustering analysis, extends model scope from macroscopic stress response to the granular level, capturing mechanical responses and orientation evolution across grains. This reduces the number of nonlinear problems to solve, with cluster responses propagated throughout each group. The thermodynamics-based artificial neural network-extracted features are further processed using local material state clusters to account for history-dependent deformation and evolving microstructures. Additionally, representative volume element simulations with rate-tangent crystal plasticity fast Fourier transform provide reliable datasets for model training. The proposed model demonstrates high efficiency, accuracy, self-consistency, and enhanced generalizability in predicting strain–stress responses and orientation evolution at both individual grain and aggregate scales under complex loading conditions, such as biaxial tension and arbitrary loading scenarios.

36 MATERIALS SCIENCE↗

Considerations for a TeV collider based on dielectric laser accelerators

Particle acceleration in dielectric microstructures powered by infrared lasers, or "dielectric laser acceleration" (DLA), is a promising area of advanced accelerator research with the potential to enable more affordable and higher-gradient accelerators for energy frontier science and a variety of other applications. DLA leverages well-established industrial fabrication capabilities and the commercial availability of tabletop lasers to reduce cost, with axial accelerating fields in the GV/m range. Further, desirable luminosities would be obtained by operating with very low charge per bunch but at extremely high repetition rates. And as a consequence of its unique operating parameter regime, coupling of the laser to the accelerator can potentially be in the 50% range and with low beamstrahlung energy loss due at the interaction point, making DLA a promising approach for a future multi-TeV linear collider.

43 PARTICLE ACCELERATORS↗

The Linac Extension Area at the Advanced Photon Source

The Linac Extension Area has been developed into a beamline area for testing accelerator components and techniques. Beginning commissioning activities in February 2023, we have delivered the first electron beam to the Linac Extension Area at the Advanced Photon Source at 425 MeV. In the present work, we summarise the principal accelerator components and review safety controls of the Linac Extension Area.

47 OTHER INSTRUMENTATION↗

Buoyancy-Driven Heat Transfer During Application of a Thermal Gradient for the Study of Vapor Deposition at Low Pressure Using and Ideal Gas

A mathematical model has been developed to determine heat transfer during vapor deposition of source materials under a variety of orientations relative to gravitational accelerations. The model demonstrates that convection can occur at total pressures as low as 10-2 mm Hg. Through numerical computation, using physical material parameters of air, a series of time steps demonstrates the development of flow and temperature profiles during the course of vapor deposition. These computations show that in unit gravity vapor deposition occurs by transport through a fairly complicated circulating flow pattern when applying heat to the bottom of the vessel with parallel orientation with respect to the gravity vector. The model material parameters for air predict the effect of kinematic viscosity to be of the same order as thermal diffusivity, which is the case for Prandtl number approx. 1 fluids. Qualitative agreement between experiment and the model indicates that 6-(2-methyl-4-nitroanilino)-2,4-hexadiyn-l-ol (DAMNA) at these pressures indeed approximates an ideal gas at the experiment temperatures, and may validate the use of air physical constants. It is apparent that complicated nonuniform temperature distribution in the vapor could dramatically affect the homogeneity, orientation, and quality of deposited films. The experimental test i's a qualitative comparison of film thickness using ultraviolet-visible spectroscopy on films generated in appropriately oriented vapor deposition cells. In the case where heating of the reaction vessel occurs from the top, deposition of vapor does not normally occur by convection due to a stable stratified medium. When vapor deposition occurs in vessels heated at the bottom, but oriented relative to the gravity vector between these two extremes, horizontal thermal gradients induce a complex flow pattern. In the plane parallel to the tilt axis, the flow pattern is symmetrical and opposite in direction from that where the vessel is positioned vertically. The ground-based experiments are sufficient preliminary tests of theory and should be of significant interest regarding vapor deposited films in microgravity.

Frazier, D. O.↗

Enabling Interoperability in Earth System Digital Twins (ESDT): Integrating Observations, Models, and AI for Actionable Insights Through NASA'S Intelligent Systems Technology Program

NASA’s Intelligent Systems Technology Program (IST) is driving a paradigm shift in Earth science through the development of Earth System Digital Twins (ESDT). These integrated information systems create a dynamic "digital replica" of the Earth by harmonizing continuous, multi-source observations with high-fidelity models and state-of-the-art artificial intelligence (AI) that enable “What now?”, “What next?”, and “What if?” scenario building. These scenarios are reflected in NASA IST’s series of ESDTs, from the Coastal Zone Digital Twin that integrates complex data on the current state of the Chesapeake Bay to the Terrestrial Environmental Rapid-Replication and Assimilation Hydrometeorological (TerraHydro) AI-based ESDT that forecasts water movement across Earth’s surface, to the Agriculture Land Information System (AgLIS) which can be used to assess optimal planting dates and crop yield estimates. By bridging the gap between vast data archives and actionable insights, these projects enable a system-of-systems approach to understanding complex, interacting Earth processes. This poster will highlight recent innovations and future directions from NASA’s ESDT initiatives: Continuous Data Assimilation & Multi-Source Fusion. A core requirement of the ESDT work is the transition from static models to dynamic "living" replicas. This involves creating frameworks for the continual assimilation of near-real-time data from uncoordinated, heterogeneous sources, including satellite observations and airborne assets, and ground-based Internet of Things (IoT) sensors. These systems link design, operational status, and environmental data, ensuring the digital twin accurately reflects the current state of the physical Earth system. High-Fidelity Hybrid Modeling & Computational Acceleration to enable interactive "what-if" explorations, programs are moving beyond traditional, slow physical solvers by developing fast surrogate machine learning models and Deep Generative Models (DGMs). These hybrid approaches use neural networks to emulate complex physics, such as cloud feedback or ocean dynamics, at a fraction of the original computing cost, often leveraging advanced hardware like Graphics Processing Units (GPUs) to achieve the necessary scale. Federated Ecosystems & Interoperable Frameworks rather than building isolated tools, NASA IST is moving toward federated ESDTs and reusable analytic collaborative frameworks. This theme focuses on interoperability standards and common ontologies that allow specialized digital twins to interact and share data. This system-of-systems architecture supports multi-discipline investigations, such as analyzing how upstream watershed changes impact downstream urban flooding or how wildfire emissions affect regional air quality. By leveraging these advancements, ESDTs empower researchers and decision-makers to conduct real-time analysis and run complex hypothetical scenarios, ultimately improving our understanding of Earth’s evolving systems and informing critical real-world applications.

Earth System↗

Battery Performance, Thermal, and Life Modeling for Southern California Edison (Cooperative Research and Development Final Report)

The objective of this project is to develop battery performance models, thermal models and life models for SCE to use in simulation and analysis of grid services involving energy storage. NREL will fit the models to three separate chemistries using test data provided by SCE. The dataset for each chemistry will include electrical, thermal and aging response to different temperatures and cycling conditions, measured under a variety of cell-level and module-level experiments described in SCE test protocol documents. Once tuned to a test dataset, the battery system model software will provide predictions of battery energy and power loss, and thus cycle and calendar life, for any energy storage grid service power profile of interest to SCE. The automated battery life modeling and simulation tool can also be applied to any other grid battery systems as long as necessary input data is available to accelerate battery model development and battery lifetime analysis.

25 ENERGY STORAGE↗

Dynamic Model Investigation of Water Pressures and Accelerations Encountered During Landings of the Apollo Spacecraft

An experimental investigation was made to determine impact water pressures, accelerations, and landing dynamics of a 1/4-scale dynamic model of the command module of the Apollo spacecraft. A scaled-stiffness aft heat shield was used on the model to simulate the structural deflections of the full-scale heat shield. Tests were made on water to obtain impact pressure data at a simulated parachute letdown (vertical) velocity component of approximately 30 ft/sec (9.1 m/sec) full scale. Additional tests were made on water, sand, and hard clay-gravel landing surfaces at simulated vertical velocity components of 23 ft/sec (7.0 m/sec) full scale. Horizontal velocity components investigated ranged from 0 to 50 ft/sec (15 m/sec) full scale and the pitch attitudes ranged from -40 degrees to 29 degrees. Roll attitudes were O degrees, 90 degrees, and 180 degrees, and the yaw attitude was 0 degrees.

Tests↗

Lithium-Ion Battery Life Model with Electrode Cracking and Early-Life Break-in Processes

This paper develops a physically justified reduced-order capacity fade model from accelerated calendar- and cycle-aging data for 32 lithium-ion (Li-ion) graphite/nickel-manganese-cobalt (NMC) cells. The large data set reveals temperature-, charge C-rate-, depth-of-discharge-, and state of charge (SOC)-dependent degradation patterns that would be unobserved in a smaller test matrix. Model structure is informed by incremental capacity analysis that shows loss of lithium inventory and cathode-material loss as the dominant capacity fade mechanisms. The model includes terms attributable to solid-electrolyte interface (SEI) growth, electrode cracking, cycling-driven acceleration of SEI growth, and "break-in" mechanisms that slightly decrease or increase available Li inventory early in life. The study explores what mathematical couplings of these mechanisms best describe calendar aging, cycle aging, and mixed calendar/cycle aging. Various approaches are discussed for extracting relevant stress factors from complex cycling profiles to predict lifetime during real-world battery loads using models trained on constant-current laboratory test results. The complexity of the present human-driven model identification process motivates future work in machine learning to more widely search and statistically discern the optimal model that correctly extrapolates capacity fade based on physical knowledge.

25 ENERGY STORAGE↗

Modal Correction Method For Dynamically Induced Errors In Wind-Tunnel Model Attitude Measurements

This paper describes a method for correcting the dynamically induced bias errors in wind tunnel model attitude measurements using measured modal properties of the model system. At NASA Langley Research Center, the predominant instrumentation used to measure model attitude is a servo-accelerometer device that senses the model attitude with respect to the local vertical. Under smooth wind tunnel operating conditions, this inertial device can measure the model attitude with an accuracy of 0.01 degree. During wind tunnel tests when the model is responding at high dynamic amplitudes, the inertial device also senses the centrifugal acceleration associated with model vibration. This centrifugal acceleration results in a bias error in the model attitude measurement. A study of the response of a cantilevered model system to a simulated dynamic environment shows significant bias error in the model attitude measurement can occur and is vibration mode and amplitude dependent. For each vibration mode contributing to the bias error, the error is estimated from the measured modal properties and tangential accelerations at the model attitude device. Linear superposition is used to combine the bias estimates for individual modes to determine the overall bias error as a function of time. The modal correction model predicts the bias error to a high degree of accuracy for the vibration modes characterized in the simulated dynamic environment.

Buehrle, R. D.↗