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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Molecular latent space simulators

Latent space simulators learn kinetic models for atomistic simulations and generate novel trajectories at six orders of magnitude lower cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Real-space simulations of the hyperbolic plasmon polaritons in 1T′ tungsten ditelluride

Recent discoveries of hyperbolic surface plasmon polaritons (SPPs) in 1T′ WTe 2 have garnered significant attention in 2D materials and nanophotonics. In this study, we employ finite-element simulations to investigate the real-space characteristics of hyperbolic SPPs in thin WTe 2 flakes. Our results show that the SPPs exhibit a pronounced sensitivity to excitation energy and sample thickness. By analyzing the plasmonic field patterns, we extract key plasmonic parameters including plasmon wavelengths, hyperbolic angles, and plasmonic figures of merit. In addition, we examine SPP modes in stacked WTe 2 flakes with varying twist angles, demonstrating that the plasmonic field patterns can be effectively tuned by adjusting the twist angle. Notably, as the twist angle increases, the SPPs undergo a topological transition from open hyperbolic modes to closed elliptic modes. This twist-engineering capability offers promising potential for the development of tunable plasmonic devices based on WTe 2 .

2D materials↗
DOE OSTI2022

Latent Space Simulation for Carbon Capture Design Optimization

The CO2 capture efficiency in solvent-based carbon capture systems (CCSs) critically depends on the gas-solvent interfacial area (IA), making maximization of IA a foundational challenge in CCS design. While the IA associated with a particular CCS design can be estimated via a computational fluid dynamics (CFD) simulation, using CFD to derive the IAs associated with numerous CCS designs is prohibitively costly. However, previous works such as Deep Fluids (Kim et al., 2019) show that large simulation speed-ups and low error are achievable by replacing CFD simulators with neural-network (NN) surrogates that mimic the CFD simulation process. This raises the possibility for a fast, accurate replacement for a CFD simulator, and thus computationally feasible IA-based CCS-design optimization. As such, here, we explore whether an existing NN-surrogate approach (and variants we develop) can successfully be applied to our complex carbon-capture CFD simulations, with the ultimate goal of obtaining a fast and accurate simulator for our CCS-design application. Our experiments build on the Deep Fluids approach and find that resulting surrogates can produce large speed ups (4000x) while maintaining IA relative errors as low as 4% on unseen CCS configurations (interpolating between configurations seen during training). Thus, despite less faithfulness to the underlying physics of the problem, NN surrogates may be a promising tool for our CCS design optimization problem. Notably, though, the Deep Fluids approach has limitations for our application (such as model non-transferability to CCS-packing changes), which we discuss. We conclude with potential directions for future work that may, like innovations we introduced here (e.g., transformer-based dynamics prediction), improve performance on our complicated dataset of CCS CFD simulations.

AI Surrogate Simulation, Carbon Capture, design op↗
DOE OSTI2025

Injection simulations of space charge dominated proton beams in IOTA

A 2.5 MeV proton injector is being constructed for the IOTA ring at Fermilab to study the interaction of nonlinear integrable optics (NIO) with high space charge beams. Space charge in the transport line from the RFQ to the injection location has a significant current dependent effect on the phase space. Simulation studies to support efficient injection of intense bunches into IOTA are presented, included schemes to inject directly into NIO lattices.

Accelerator Physics↗
DOE OSTI2025

Injection simulations of space charge dominated proton beams in IOTA

A 2.5 MeV proton injector is being constructed for the IOTA ring at Fermilab to study the interaction of nonlinear integrable optics (NIO) with high space charge beams. Space charge in the transport line from the RFQ to the injection location has a significant current dependent effect on the phase space. Simulation studies to support efficient injection of intense bunches into IOTA are presented, included schemes to inject directly into NIO lattices.

Wieland, J. [Fermilab; Michigan State U.] (ORCID:0↗
DOE OSTI2025

Injection simulations of space charge dominated proton beams in IOTA

Injection simulations of space charge dominated proton beams in IOTA ABSTRACT = A 2.5 MeV proton injector has been constructed for the IOTA ring at Fermilab to study the interaction of nonlinear integrable optics (NIO) with high space charge beams. Space charge in the transport line from the RFQ to the injection location has a significant current dependent effect on the phase space. Simulation studies to support efficient injection of intense bunches into IOTA are presented, included schemes to inject directly into NIO lattices.

Wieland, J. [Fermilab]↗
DOE OSTI2026

The Memory Scaling of Reverse-Mode Differentiation in Particle Accelerator Simulations with Space Charge

The recent development of differentiable simulation codes for particle accelerators has enabled gradient-based workflows that promise finer control and more realistic modeling of accelerator facilities. However, when using reverse-mode automatic differentiation, the memory usage continuously increases during the simulation, and can potentially exceed the available hardware memory - especially when costly space charge computation is included. To study the memory requirements for differentiable simulations, we have implemented space charge in Cheetah, a PyTorch-based beam tracking code that supports reverse-mode differentiation. We find that the memory usage for reverse-mode differentiation grows linearly with the number of macroparticles and cells, and that it is proportional to the number of space charge kicks involved in the simulation. This general scaling can be used to evaluate whether a given differentiable simulation is feasible given hardware memory constraints.

Dhamrait, Arjun↗
DOE OSTI2021

Modeling Transverse Space Charge effects in IOTA with pyORBIT

The role and mitigation of space charge effects are important aspects of the beam physics research to be performed at the Integrable Optics Test Accelerator (IOTA) at Fermilab. The impact of nonlinear integrability (partial and complete) on space charge driven incoherent and coherent resonances will be a new feature of this accelerator and has the potential to influence the design of future low energy proton synchrotrons. In this report we model transverse space charge effects using the PIC code pyORBIT. First we benchmark the single particle tracking results against MADX with checks on symplecticity, tune footprints, and dynamic aperture in a partially integrable lattice realized with a special octupole string insert. Our space charge calculations begin with an examination of the 4D symplecticity. Short term tracking is done first with the initial bare lattice and then with a matching of the rms values with space charge. Next, we explore slow initialization of charge as a technique to establish steady state and reduce emittance growth and beam loss following injection into a mismatched lattice. We establish values of space charge simulation parameters so as to ensure numerical convergence. Finally, we compare the simulated space charge induced tune shifts and footprints against theory.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Symplectic machine learning model for fast simulation of space-charge effects

Symplectic simulation of space-charge effects is crucial for the design and operation of high-intensity particle accelerators. Traditional methods for simulating these effects are often computationally expensive, resulting in significant overhead. In this work, we introduce a generative model based on a U-Net architecture within a generative adversarial network framework to efficiently simulate space-charge effects. The model is trained to predict the transverse multiparticle space-charge Hamiltonian, which can be physically computed using a gridless spectral method. The one-step symplectic transverse transfer map for the particles is then obtained by differentiating the predicted Hamiltonian. Benchmarking results demonstrate that this generative model achieves an order of magnitude higher computational efficiency compared to the spectral method, providing a highly efficient alternative for simulating space-charge effects with a large number of particles. By maintaining symplecticity, the model effectively preserves the phase-space structure and mitigates nonphysical errors in long-term simulations. This model has been integrated into jutrack, a novel autodifferentiable accelerator modeling code developed in the julia programming language.

Beam code development & simulation techniques↗
DOE OSTI2020

Quantum simulation of hyperbolic space with circuit quantum electrodynamics: From graphs to geometry

We show how quantum many-body systems on hyperbolic lattices with nearest-neighbor hopping and local interactions can be mapped onto quantum field theories in continuous negatively curved space. Here, the underlying lattices have recently been realized experimentally with superconducting resonators and therefore allow for a table-top quantum simulation of quantum physics in curved background. Our mapping provides a computational tool to determine observables of the discrete system even for large lattices, where exact diagonalization fails. As an application and proof of principle we quantitatively reproduce the ground state energy, spectral gap, and correlation functions of the noninteracting lattice system by means of analytic formulas on the Poincaré disk, and show how conformal symmetry emerges for large lattices. This sets the stage for studying interactions and disorder on hyperbolic graphs in the future. Importantly, our analysis reveals that even relatively small discrete hyperbolic lattices emulate the continuous geometry of negatively curved space, and thus can be used to experimentally resolve fundamental open problems at the interface of interacting many-body systems, quantum field theory in curved space, and quantum gravity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Modeling of standing wave RF cavities for tracking through multi-pass energy recovery linac

Short bunches, high current and multiple linac pass are all characteristics of Energy Recovery Linacs (ERLs), which may result in collective effects. They in turn, may affect the beam, degrading its quality, or even yield to instabilities causing a beam loss. To study and mitigate these effects one needs a numerical simulation code, that can take into account both the collective effects, as well as, particular ERL features, such as a multi-turn design that does not reach a steady state or the multiple passages of the beam through Radio-Frequency (RF) cavities at different energies. CODAL [1], a code developed by SOLEIL in collaboration with IJCLab, enables such studies. It is a 6 dimensional (6D) tracking code applying 'kicks' based on the integration of the local Hamiltonian for each element of the lattice. It is also capable of simulating space charge, wakefields and coherent synchrotron radiation. However, to correctly take into account the ERL dynamics, an upgrade had to be made to include the effect of a standing wave RF cavity in 6D. In this paper, we will concentrate on the implementation and benchmarking (with DESY’s tracking code ASTRA [2]) of both the longitudinal and the transverse models (by J.B. Rosenzweig and L. Serafini [3]), which we use to carry out tracking of fully analytical 6D RF cavity.

Bogacz, A.↗
DOE OSTI2025

Space Charge Simulations of High Intensity Proton Beams in the AGS Booster

Computer simulation studies have been performed to understand the beam behavior and to explore intensity limitations of proton beams in the AGS Booster at higher beam intensities. During the 100 GeV polarized proton operations of RHIC Run 2024, sPHENIX operated in modes with a crossing angle at collisions in order to mitigate beam-beam effects. Three different running modes were employed: (a) sPHENIX operated with a negative (-2 mrad) crossing angle, and STAR operated with 0 mrad. Both experiments were brought into collisions at the start of the store. (b) sPHENIX was brought into collisions with 0 mrad first. Then STAR was brought into collisions after the beam-beam parameter from sPHENIX reduced to below $10 \times 10^{-3}$. (c) sPHENIX operated with a positive (+1.5 mrad) crossing angle, and STAR operated with 0 mrad. Both experiments were brought into collisions at the start of the store. The collisions with a crossing angle of up to $\pm 2$ mrad, as in running modes (a) and (c), lead to large Piwinski angle in the new sPHENIX detector, which reduces luminosity if other parameters are unchanged. There are two ways to compensate the reduction in luminosity: squeeze $\beta^{*}$ if there is sufficient dynamic aperture, or increase the injected beam intensity. The first part of polarized proton operation during RHIC Run 2024 was dedicated to increasing the intensity. Different configurations were tested with crossing angle and lattice adjustments on RHIC. At the same time, new injector configurations were developed and tested in an effort to push for both higher intensity and better quality of the beam injected into RHIC. When the beam intensity is increased, space charge is a concern particularly in the lower energy stages of acceleration, such as during the injection and the early part of the Booster cycle, which could become a dominant effect in limiting the intensity of the beam that can be delivered to RHIC.

43 PARTICLE ACCELERATORS↗