Search NASA⌕ Search

SEARCH · Search NASA

Results for “Accelerator Driven Systems”

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 667 records · Page 37

Evaluating Safety with Automated Vehicles at Signalized Intersections: Application of Adaptive Cruise Control in Mixed Traffic

Automated Vehicles (AV) can potentially improve the performance of transportation system by reducing human errors and enhancing mobility and safety. In lower levels of automation, humans are still controlling the vehicle and receiving some advisory information regarding their surrounding environment. This paper investigates the safety impact of low and high levels of AVs, and their interaction with conventional human-driven vehicles at intersections. In order to enhance our understanding of the future interactions between conventional vehicles with AVs, we developed a framework to simulate the mixed traffic environment. Different market penetration scenarios are simulated using VENTOS (VEhicular NeTwork Open Simulator) software. A modified Wiedemann car-following model was calibrated to represent the behavior of human drivers of both conventional and low-level AVs, while an Adaptive Cruise Control model was used to represent high-level AVs. Notably, this study investigates purely the automation improvement in the system. We modified the acceleration and deceleration regimes of the Wiedemann model and tuned it by harnessing real-world connected vehicle data. Next, the simulation was calibrated utilizing two measures of driving volatility to ensure it closely represents the volatility measures of the real-world data. To evaluate the safety performance of a representative intersection under different scenarios, the number of longitudinal conflicts and driving volatility are used as surrogate safety indicators. The results reveal that increase in market penetration rate of LAVs and HAVs substantially improves intersection safety performance by reducing the number of conflicts and driving volatility.

Arvin, Ramin↗

Accelerating computational fluid dynamics simulation of post-combustion carbon capture modeling with MeshGraphNets

Packed columns are commonly used in post-combustion processes to capture CO 2 emissions by providing enhanced contact area between a CO 2 -laden gas and CO 2 -absorbing solvent. To study and optimize solvent-based post-combustion carbon capture systems (CCSs), computational fluid dynamics (CFD) can be used to model the liquid–gas countercurrent flow hydrodynamics in these columns and derive key determinants of CO 2 -capture efficiency. However, the large design space of these systems hinders the application of CFD for design optimization due to its high computational cost. In contrast, data-driven modeling approaches can produce fast surrogates to study large-scale physics problems. We build our surrogates using MeshGraphNets (MGN), a graph neural network framework that efficiently learns and produces mesh-based simulations. We apply MGN to a random packed column modeled with over 160K graph nodes and a design space consisting of three key input parameters: solvent surface tension, inlet velocity, and contact angle. Our models can adapt to a wide range of these parameters and accurately predict the complex interactions within the system at rates over 1700 times faster than CFD, affirming its practicality in downstream design optimization tasks. This underscores the robustness and versatility of MGN in modeling complex fluid dynamics for large-scale CCS analyses.

97 MATHEMATICS AND COMPUTING↗

MO-FG-202-03: Efficient Data Collection of Continuous 2D and Discrete Relative Dosimetric Data for Annual LINAC QA Using TrueBeam Developer Mode and a 1D Scanning Tank

Purpose: To develop a method to exploit real-time dynamic machine and couch parameter control during linear accelerator (LINAC) beam delivery to facilitate efficient performance of TG-142 suggested, Annual LINAC QA tests. Methods: Varian’s TrueBeam Developer Mode (Varian Medical Systems, Palo Alto, CA) facilitates control of Varian’s TrueBeam LINAC via instructions provided in Extensible Markup Language (XML) files. This allows machine and couch parameters to be varied dynamically, in real-time, during beam delivery. Custom XML files were created to allow for the collection of (1) continuous Tissue Maximum Ratios (TMRs), (2) beam profiles, and (3) continuous output factors using a 1D-scanning tank. TMRs were acquired by orienting an ionization chamber (IC) at isocenter (depth=25cm) and synchronizing a depth scan towards the water surface while lowering the couch at 1mm/s. For beam profiles, the couch was driven laterally and longitudinally while logging IC electrometer readings. Output factors (OFs) where collected by continually varying field sizes (4×4 to 30×30-cm{sup 2}) at a constant speed of 6.66 mm/s. To validate measurements, comparisons were made to data collected using traditional methods (e.g. 1D or 3D tank). Results: All data collecting using the proposed methods agreed with traditionally collected data (TMRs within 1%, OFs within 0.5% and beam profile agreement within 1% / 1mm) while taking less time to collect (factor of approximately 1/10) and with a finer sample resolution. Conclusion: TrueBeam developer mode facilitates collection of continuous data with the same accuracy as traditionally collected data with a finer resolution in less time. Results demonstrate an order of magnitude increase in sampled resolution and an order of magnitude reduction in collection time compared to traditional acquisition methods (e.g. 3D scanning tank). We are currently extending this approach to perform other TG-142 tasks.

61 RADIATION PROTECTION AND DOSIMETRY↗

Novel Hybrid Monte Carlo/Deterministic Technique for Shutdown Dose Rate Analyses of Fusion Energy Systems

The rigorous 2-step (R2S) method uses three-dimensional Monte Carlo transport simulations to calculate the shutdown dose rate (SDDR) in fusion reactors. Accurate full-scale R2S calculations are impractical in fusion reactors because they require calculating space- and energy-dependent neutron fluxes everywhere inside the reactor. The use of global Monte Carlo variance reduction techniques was suggested for accelerating the neutron transport calculation of the R2S method. The prohibitive computational costs of these approaches, which increase with the problem size and amount of shielding materials, inhibit their use in the accurate full-scale neutronics analyses of fusion reactors. This paper describes a novel hybrid Monte Carlo/deterministic technique that uses the Consistent Adjoint Driven Importance Sampling (CADIS) methodology but focuses on multi-step shielding calculations. The Multi-Step CADIS (MS-CADIS) method speeds up the Monte Carlo neutron calculation of the R2S method using an importance function that represents the importance of the neutrons to the final SDDR. Using a simplified example, preliminarily results showed that the use of MS-CADIS enhanced the efficiency of the neutron Monte Carlo simulation of an SDDR calculation by a factor of 550 compared to standard global variance reduction techniques, and that the increase over analog Monte Carlo is higher than 10,000.

hybrid Monte Carlo/deterministic↗

A high-throughput workflow to analyze sequence-conformation relationships and explore hydrophobic patterning in disordered peptoids

Understanding how a macromolecule’s primary sequence governs its conformational landscape is crucial for elucidating its function, yet these design principles are still emerging for macromolecules with intrinsic disorder. Herein, we introduce a high-throughput workflow that implements a practical colorimetric conformational assay, introduces a semi-automated sequencing protocol using matrix-assisted laser desorption/ionization and tandem mass spectrometry (MALDI-MS/MS), and develops a generalizable sequence-structure algorithm. Using a model system of 20mer peptidomimetics containing polar glycine and hydrophobic N-butylglycine residues, we identified nine classifications of conformational disorder and isolated 122 unique sequences across varied compositions and conformations. Conformational distributions of three compositionally identical library sequences were corroborated through atomistic simulations and ion mobility spectrometry coupled with liquid chromatography. A data-driven strategy was developed using existing sequence variables and data-derived “motifs” to inform a machine-learning algorithm toward conformation prediction. Here, this multifaceted approach enhances our understanding of sequence-conformation relationships and offers a powerful tool for accelerating the discovery of materials with conformational control.

data-driven analysis↗

Stellar winds in binary X-ray systems

It is thought that accretion from a strong stellar wind by a compact object may be responsible for the X-ray emission from binary systems containing a massive early-type primary. To investigate the effect of X-ray heating and ionization on the mass transfer process in systems of this type, an idealized model is constructed for the flow of a radiation-driven wind in the presence of an X-ray source of specified luminosity, L sub x. It is noted that for low values of L sub x, X-ray photoionization gives rise to additional ions having spectral lines with wavelengths situated near the peak of the primary continuum flux distribution. As a consequence, the radiation force acting on the gas increases in relation to its value in the absence of X-rays, and the wind is accelerated to higher velocities. As L sub x is increased, the degree of ionization of the wind increases, and the magnitude of the radiation force is diminished in comparison with the case in which L sub x = 0. This reduction leads at first to a decrease in the wind velocity and ultimately (for L sub x sufficiently large) to the termination of radiatively driven mass loss.

Macgregor, K. B.↗

Shock Structure and Magnetic Fields Generation Associated with Relativistic Jets Unmagnetized Pair Plasma

Using 3D and 2D particle-in-cell simulations we investigate a shock structure, magnetic field generation, and particle acceleration associated with an unmagnetized relativistic electron-positron jet propagating into an unmagnetized pair plasma. The simulations use long computational grids which allow to study the formation and dynamics of the system in a spatial and temporal way. We find for the first time a relativistic shock system comparable to a predicted magnetohydrodynamic shock structure consisting of leading and trailing shocks separated by a contact discontinuity. Strong electromagnetic fields resulting from the Weibel two-stream instability are generated in the trailing shock where jet matter is thermalized and decelerated. We analyze the formation and nonlinear development through saturation and dissipation of those fields and associated particle acceleration. In the AGN context the trailing shock corresponds to the jet shock at the head of a relativistic astrophysical jet. In the GRB context this trailing shock can be identified with the bow shock driven by relativistic ejecta. The strong electromagnetic field region in the trailing shock provides the emission site for the hot spot at the leading edge of AGN jets and for afterglow emission from GRBs.

Niemiec, J.↗

Bioenergetic consequences of compromised mitochondrial DNA repair in the mouse heart

Highlights: • Loss of mitochondrial DNA repair compromises bioenergetic efficiency. • Impairments in bioenergetic efficiency result from ETS stoichiometry shifts. • Bioenergetic flux in Polg{sup m/m} mitochondria favors accelerated electron leak. The progeroid phenotype of mitochondrial DNA (mtDNA) mutator mice has been nebulously attributed to general mitochondrial ‘dysfunction’, though few studies have rigorously defined the bioenergetic consequences of accumulating mtDNA mutations. Comprehensive mitochondrial diagnostics was employed to interrogate the bioenergetic properties of isolated cardiac mitochondria from mtDNA mutator mice and wild type littermates. Assessment of respiratory flux in conjunction with parallel measurements of mitochondrial free energy all point to the cause of respiratory flux limitations observed in mtDNA mutator mouse mitochondria being due to impairments within the energy transduction step catalyzed by the electron transport system in which NADH/NAD{sup +} free energy is transduced to the proton motive force (ΔP). The primary bioenergetic consequence of this limitation appears to be hyper-reduction of NAD(P)H/NAD(P){sup +} redox poise across multiple substrate conditions, particularly evident at moderate to high respiration rates. This hyper-reduced phenotype appears to result from specific reductions in both complex I and complex IV expression, presumably due to compromised mtDNA integrity. Translation of these findings to the working heart would suggest that the primary biological consequence of accumulated mtDNA damage is accelerated electron leak driven by an increase in electron redox pressure for a given rate of oxygen consumption.

60 APPLIED LIFE SCIENCES↗

Hot Hydride Superconductivity Above 550 K

The search for room temperature superconductivity has accelerated in the last few years driven by experimentally accessible theoretical predictions that indicated alloying dense hydrogen with other elements could produce conventional superconductivity at high temperatures and pressures. These predictions helped inform the synthesis of simple binary hydrides that culminated in the discovery of the superhydride LaH 10 with a superconducting transition temperature T c of 260 K at 180 GPa. We have now successfully synthesized a metallic La-based superhydride with an initial T c of 294 K. When subjected to subsequent thermal excursions that promoted a chemical reaction to a higher order system, the Tc onset was driven irreversibly to 556 K. X-ray characterization confirmed the formation of a distorted LaH 10 based backbone that suggests the formation of ternary or quaternary compounds with substitution at the La and/or H sites. The results provide evidence for hot superconductivity, aligning with recent predictions for higher order hydrides under pressure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Zooming in: SCREAM at 100 m using regional refinement over the San Francisco Bay Area

Pushing global climate models to large-eddy simulation (LES) scales over complex terrain has remained a major challenge. This study presents the first known implementation of a global model – SCREAM (Simple Cloud-Resolving E3SM Atmosphere Model) – at 100 m horizontal resolution using a regionally refined mesh (RRM) over the San Francisco Bay Area. Two hindcast simulations were conducted to test performance under both strong synoptic forcing and weak, boundary-layer-driven conditions. We demonstrate that SCREAM can stably run at LES scales while realistically capturing topography, surface heterogeneity, and coastal processes. The 100 m SCREAM-RRM substantially improves near-surface wind speed, temperature, humidity, and pressure biases compared to the baseline 3.25 km simulation, and better reproduces fine-scale wind oscillations and boundary-layer structures. These advances leverage SCREAM's scale-aware SHOC turbulence parameterization, which transitions smoothly across scales without tuning. Performance tests show that while CPU-only simulations remain costly, GPU acceleration with SCREAMv1 on NERSC's Perlmutter system enables two-day hindcasts to complete in under two wall-clock days. Our results open the door to LES-scale studies of orographic flows, boundary-layer turbulence, and coastal clouds within a fully comprehensive global modeling framework.

Geosciences↗

Measurement of the Mo 100 ( α , x n ) cross section at weak r -process energies

Here, the weak r process in neutrino-driven winds following a core-collapse supernova is thought to contribute to the cosmic abundances of the first r-process peak elements between Se and Ag. Sensitivity studies have found that the early nucleosynthesis in the weak r process is primarily driven by (α, xn) reactions due to the high temperatures, and that current nuclear physics uncertainties in the (α, xn) rates result in significant uncertainties of the calculated abundances. The weak r-process path proceeds several nuclei away from stability where (α, xn) reaction cross sections have not yet been measured. In this paper we report the 100 Mo (α, xn) cross section (between 8.9 and 13.2 MeV in the center of mass, corresponding to 3.5–6.8 GK) in inverse kinematics using the Multi-Sampling Ionization Chamber (MUSIC) detector at the Argonne Tandem Linac Accelerator System (ATLAS) facility. With this first measurement of the 100 Mo (α, xn) cross section, we have demonstrated the ability of MUSIC to measure (α, xn) cross sections for A up to 100, therefore paving the way for further measurements with radioactive beams at ATLAS or the Facility for Rare Isotope Beams.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Cyber Physical Security (CPS) Extension to Air Traffic Management (ATM) Testbed

The Air Traffic Management (ATM) Testbed is being developed at NASA to enable benefit, impact, safety and cost assessments for accelerating the deployment of Concept and Technologies (C&T) in the National Airspace System (NAS). Today, C&T introduction into the NAS takes decades. The primary reason for this is an inability to assess the operational impact of the interaction between the proposed C&T and operationally deployed systems (Realistic Technologies) in terms of NAS-wide safety, traffic flow efficiency, roles and workload of controllers and traffic managers, and impact on airline fleet operations. Transition of C&T to operations requires mathematical modeling and simulation, Human-in-the-Loop (HITL) testing and shadow-mode evaluation driven by operational data. Whereas interaction with the operational system during testing and stages of deployment is not permissible due to safety concerns, it is certainly possible to create a simulation environment that closely mimics the NAS using the same operational systems/hardware for enabling such assessments. This presentation focuses on a proposed Cyber Physical Security extension to the ATM Testbed for creating a modeling and simulation architecture to study how well the Air Traffic Management system will perform and analyze effectiveness of mitigating security measures against particular cyber-attack scenarios.

Datta, Koushik↗

Water and Climate Impacts on ERCOT Long-Term Systems Assessment

Water and climate change pose many potential challenges to the electric power system. Substantial water is withdrawn every day to support thermoelectric power generating unit operations, and changes to water supply have the potential to affect generation dispatch. Climate change can accelerate growing demand for electricity, which can necessitate additional generating capacity, often in locations with limited water supply. Drought conditions also threaten thermoelectric power plant operations due to streamflow and reservoir levels dropping below intake structures, or water temperatures exceeding a power plants' permitted operating conditions. Here we explore how future climate change might influence decisions related to electricity capacity expansion planning in Electric Reliability Council of Texas (ERCOT) using a multi-model framework. Specifically, water resource modeling is used to simulate climate impacts on the future water supply for thermoelectric and hydropower generation for four future climate projections. Separately, temperature impacts on electricity load are evaluated for these scenarios. These climate impacts are applied to five alternative electricity futures in an electricity capacity expansion model that projects future generation and transmission capacity additions in ERCOT. Results indicate that climate has a measurable influence on future generation and transmission capacity needs, with temperature-driven increases in peak and average load resulting in 5-15 GW additional generating capacity and up to 1 GW additional transmission capacity. Additional capacity is a diverse mix of PV, natural gas, and wind, depending on the makeup of economic, policy and technology assumptions. Climate impacts increase total system costs 2-5%, while the marginal cost of energy and emissions are not affected substantially by climate change effects.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Data-driven Chaos Indicator for Nonlinear Dynamics and Applications on Storage Ring Lattice Design

A data-driven chaos indicator concept is introduced to characterize the degree of chaos for nonlinear dynamical systems. The indicator is represented by the prediction accuracy of surrogate models established purely from data. It provides a metric for the predictability of nonlinear motions in a given system. When using the indicator to implement a tune-scan for a quadratic Hénon map, the main resonances and their asymmetric stop-band widths can be identified. When applied to particle transportation in a storage ring, as particle motion becomes more chaotic, its surrogate model prediction accuracy decreases correspondingly. Therefore, the prediction accuracy, acting as a chaos indicator, can be used directly as the objective for nonlinear beam dynamics optimization. This method provides a different perspective on nonlinear beam dynamics and an efficient method for nonlinear lattice optimization. Applications in dynamic aperture optimization are demonstrated as real world examples.

43 PARTICLE ACCELERATORS↗

Deep Learning Based Superconducting Radio-Frequency Cavity Fault Classification at Jefferson Laboratory

This work investigates the efficacy of deep learning (DL) for classifying C100 superconducting radio-frequency (SRF) cavity faults in the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. CEBAF is a large, high-power continuous wave recirculating linac that utilizes 418 SRF cavities to accelerate electrons up to 12 GeV. Recent upgrades to CEBAF include installation of 11 new cryomodules (88 cavities) equipped with a low-level RF system that records RF time-series data from each cavity at the onset of an RF failure. Typically, subject matter experts (SME) analyze this data to determine the fault type and identify the cavity of origin. This information is subsequently utilized to identify failure trends and to implement corrective measures on the offending cavity. Manual inspection of large-scale, time-series data, generated by frequent system failures is tedious and time consuming, and thereby motivates the use of machine learning (ML) to automate the task. This study extends work on a previously developed system based on traditional ML methods (Tennant and Carpenter and Powers and Shabalina Solopova and Vidyaratne and Iftekharuddin, Phys. Rev. Accel. Beams, 2020, 23, 114601), and investigates the effectiveness of deep learning approaches. The transition to a DL model is driven by the goal of developing a system with sufficiently fast inference that it could be used to predict a fault event and take actionable information before the onset (on the order of a few hundred milliseconds). Because features are learned, rather than explicitly computed, DL offers a potential advantage over traditional ML. Specifically, two seminal DL architecture types are explored: deep recurrent neural networks (RNN) and deep convolutional neural networks (CNN). We provide a detailed analysis on the performance of individual models using an RF waveform dataset built from past operational runs of CEBAF. In particular, the performance of RNN models incorporating long short-term memory (LSTM) are analyzed along with the CNN performance. Furthermore, comparing these DL models with a state-of-the-art fault ML model shows that DL architectures obtain similar performance for cavity identification, do not perform quite as well for fault classification, but provide an advantage in inference speed.

97 MATHEMATICS AND COMPUTING↗

Strategies for Semiconductor/Electrocatalyst Coupling toward Solar‐Driven Water Splitting

Abstract Hydrogen (H 2 ) has a significant potential to enable the global energy transition from the current fossil‐dominant system to a clean, sustainable, and low‐carbon energy system. While presently global H 2 production is predominated by fossil‐fuel feedstocks, for future widespread utilization it is of paramount importance to produce H 2 in a decarbonized manner. To this end, photoelectrochemical (PEC) water splitting has been proposed to be a highly desirable approach with minimal negative impact on the environment. Both semiconductor light‐absorbers and hydrogen/oxygen evolution reaction (HER/OER) catalysts are essential components of an efficient PEC cell. It is well documented that loading electrocatalysts on semiconductor photoelectrodes plays significant roles in accelerating the HER/OER kinetics, suppressing surface recombination, reducing overpotentials needed to accomplish HER/OER, and extending the operational lifetime of semiconductors. Herein, how electrocatalyst coupling influences the PEC performance of semiconductor photoelectrodes is outlined. The focus is then placed on the major strategies developed so far for semiconductor/electrocatalyst coupling, including a variety of dry processes and wet chemical approaches. This Review provides a comprehensive account of advanced methodologies adopted for semiconductor/electrocatalyst coupling and can serve as a guideline for the design of efficient and stable semiconductor photoelectrodes for use in water splitting.

Thalluri, Sitaramanjaneya Mouli↗

Corotating Magnetic Reconnection Site in Saturn’s Magnetosphere

Using measurements from the Cassini spacecraft in Saturn’s magnetosphere, we propose a 3D physical picture of a corotating reconnection site, which can only be driven by an internally generated source. Our results demonstrate that the corotating magnetic reconnection can drive an expansion of the current sheet in Saturn’s magnetosphere and, consequently, can produce Fermi acceleration of electrons. This reconnection site lasted for longer than one of Saturn’s rotation period. The long-lasting and corotating natures of the magnetic reconnection site at Saturn suggest fundamentally different roles of magnetic reconnection in driving magnetospheric dynamics (e.g., the auroral precipitation) from the Earth. Our corotating reconnection picture could also potentially shed light on the fast rotating magnetized plasma environments in the solar system and beyond.

79 ASTRONOMY AND ASTROPHYSICS↗

Sloshing dynamics on rotating helium dewar tank

The generalized mathematical formulation of sloshing dynamics for partially filled liquid of cryogenic superfluid helium II in dewar containers driven by both the gravity gradient and jitter accelerations applicable to scientific spacecraft which is eligible to carry out spinning motion and/or slew motion for the purpose to perform scientific observation during the normal spacecraft operation are investigated. An example is given with Gravity Probe-B (GP-B) spacecraft which is responsible for the sloshing dynamics. The jitter accelerations include slew motion, spinning motion, atmospheric drag on the spacecraft, spacecraft attitude motions arising from machinery vibrations, thruster firing, pointing control of spacecraft, crew motion, etc. Explicit mathematical expressions to cover these forces acting on the spacecraft fluid systems are derived. The numerical computation of sloshing dynamics were based on the non-inertia frame spacecraft bound coordinate, and solve time dependent, three-dimensional formulations of partial differential equations subject to initial and boundary conditions. The explicit mathematical expressions of boundary conditions to cover capillary force effect on the liquid vapor interface in microgravity environments are also derived. The formulations of fluid moment and angular moment fluctuations in fluid profiles induced by the sloshing dynamics, together with fluid stress and moment fluctuations exerted on the spacecraft dewar containers were derived. Results were widely published in the open journals.

Hung, R. J.↗