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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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85 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Multiplicity dependence of charged-particle production in pp, p–Pb, Xe–Xe and Pb–Pb collisions at the LHC

Multiplicity (N ch ) distributions and transverse momentum (p T ) spectra of inclusive primary charged particles in the kinematic range of |η| < 0.8 and 0.15 GeV/c < p T < 10 GeV/c are reported for pp, p–Pb, Xe–Xe and Pb–Pb collisions at centre-of-mass energies per nucleon pair ranging from $\sqrt{s_{NN}}$ = 2.76 TeV up to 13 TeV. A sequential two-dimensional unfolding procedure is used to extract the correlation between the transverse momentum of primary charged particles and the charged-particle multiplicity of the corresponding collision. This correlation sharply characterises important features of the final state of a collision and, therefore, can be used as a stringent test of theoretical models. The multiplicity distributions as well as the mean and standard deviation derived from the p T spectra are compared to state-of-the-art model predictions. Providing these fundamental observables of bulk particle production consistently across a wide range of collision energies and system sizes can serve as an important input for tuning Monte Carlo event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Learning to Trigger: Reinforcement Learning at the Large Hadron Collider

High-throughput scientific facilities such as the Large Hadron Collider depend on real-time event filtering (\textit{triggering}) under tight constraints on bandwidth, latency, and storage. In practice, trigger menus are largely static and hand-tuned and can become suboptimal as detector conditions, pileup, and background composition drift over time. We cast online threshold tuning as a sequential decision-making problem: a reinforcement learning agent ingests streaming summaries of recent rates and signal-sensitive features and updates trigger thresholds to maximize signal efficiency while tracking a target background rate within a tolerance band. We adapt Group-Filtered Policy Optimization (GFPO) to streaming control and introduce two variants (GFPO-F, GFPO-FR) that enforce background rate feasibility during training. On a benchmark that emulates realistic collider operation, we study two representative triggers: a total transverse energy ($H_{T}$) trigger sensitive to pileup variation, and an anomaly-detection (AD) trigger based on reconstruction loss for rare or non-standard signatures. On Monte Carlo streams, our agent increases the fraction of in-tolerance time intervals by 48% ($H_T$) and 28% (AD), with a cumulative gain of up to 2% in signal efficiency on those in-tolerance intervals. Transferring from simulation to \emph{real} collision data (CMS Run 283408), the same agent, without fine-tuning, achieves a 56% ($H_T$) and 28% (AD) in-tolerance improvement over baselines, with further signal-efficiency gain on both triggers. To our knowledge, this is the \emph{first} demonstration of RL-based trigger control on real Large Hadron Collider collision data. Code is available at https://github.com/Zixind/GFPO_LHC (see repo for details).

Ding, Zixin [Chicago U.]↗
DOE OSTI2023

X-ray induced electron and ion fragmentation dynamics in IBr

Characterization of the inner-shell decay processes in molecules containing heavy elements is key to understanding x-ray damage of molecules and materials and for medical applications with Auger-electron-emitting radionuclides. The 1s hole states of heavy atoms can be produced by absorption of tunable x rays and the resulting vacancy decays characterized by recording emitted photons, electrons, and ions. The 1s hole states in heavy elements have large x-ray fluorescence yields that transfer the hole to intermediate electron shells that then decay by sequential Auger-electron transitions that increase the ion’s charge state until the final state is reached. In molecules, the charge is spread across the atomic sites, resulting in dissociation to energetic atomic ions. We have used x-ray/ion coincidence spectroscopy to measure charge states and energies of Iq+ and Brq′+ atomic ions following 1s ionization at the I and Br K-edges of IBr. We present the charge states and kinetic energies of the two correlated fragment ions associated with core-excited states produced during the various steps of the cascades. Here, to understand the dynamics leading to the ion data, we develop a computational model that combines Monte-Carlo/Molecular-Dynamics (MC/MD) simulations with a classical over-the-barrier model to track inner-shell cascades and redistribution of electrons in valence orbitals and nuclear motion of fragments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1997

Efficient Sequential Attitude Estimation from Vector Observations

This paper presents a computationally efficient, sequential method for attitude matrix estimation using gyro and vector measurements. The method is based on a recently introduced, minimal-parameter third-order method for solving the orthogonal matrix differential equation in R(sup n). In the three-dimensional case, these third-order attitude parameters can be interpreted as temporal-integrals of the body-frame angular velocity components. A nonlinear algorithm is developed, which uses this minimal set of three parameters to estimate the nine-parameter direction-cosine matrix. Having an extremely simple kinematic equation, these parameters render the resulting estimator highly computationally efficient. An orthogonalization procedure, incorporated into the measurement processing stage, enhances the accuracy and stability of the resulting algorithm, yet retains reasonable simplicity. The performance of the estimator is demonstrated via a Monte Carlo simulation study.

Oshman, Yaakov↗
DOE OSTI2026

Finite-element-based simulations of electrodes for CO 2 cascade reduction reactions

The multielectron reduction of CO 2 to liquid fuels could be a path to scalable energy storage, but reaching this goal requires major advances in catalysis and systems engineering. Cascade catalysis, which couples sequential reactions without isolating intermediates, has emerged as a promising route to enhance selectivity and efficiency in CO 2 reduction (CO 2 R). In this review, we examine how finite-element-based simulations of continuum model [finite element method (FEM)] approaches are being used to analyze and guide CO 2 R cascade systems. We first outline the fundamentals of cascade catalysis and recent advances in catalytic materials (metallic, molecular, and hybrid architectures). We then focus on FEM developments at the electrode and device scales, emphasizing how these models capture transport phenomena, local microenvironments, and geometry-dependent effects. To clarify design principles, we present case studies of cascade electrodes organized in systems without and with integrated semiconductors. We further emphasize the integration of FEM with multiscale frameworks (density functional theory, molecular dynamics, kinetic Monte Carlo) and its role in bridging atomic-level insights with device-level performance. Finally, we identify current limitations and future prospects, including improved boundary conditions, coupling with operando experiments, and machine learning-accelerated model development. Together, these insights provide design principles for next-generation CO 2 R cascade systems for efficient solar fuel production.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2014

Generalized Linear Covariance Analysis

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

Navagation↗
NASA NTRS2014

Generalized Linear Covariance Analysis

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

n/a↗
DOE OSTI2025

Heavy ion collisions from $\sqrt{s_{NN}}$ of 62.4 GeV down to 7.7 GeV in the EPOS4 framework

The EPOS4 project is an attempt to construct a realistic model for describing relativistic collisions of different systems, from proton-proton (𝑝⁢𝑝) to nucleus-nucleus (𝐴⁢𝐴), at energies from several TeV per nucleon down to several GeV. We argue that a parallel scattering formalism (as in EPOS4) is relevant for primary scatterings in 𝐴⁢𝐴 collisions above 4 GeV, whereas sequential scattering (cascade) is appropriate below. We present briefly the basic elements of EPOS4, and then investigate heavy ion collisions from 62.4 GeV down to 7.7 GeV, to understand how physics changes with energy, studying in particular the disappearance of the fluid component at low energies.

Monte Carlo methods↗
DOE OSTI2022

An Online Approach to Solve the Dynamic Vehicle Routing Problem with Stochastic Trip Requests for Paratransit Services

Many transit agencies operating paratransit and microtransit services have to respond to trip requests that arrive in real-time, which entails solving hard combinatorial and sequential decision-making problems under uncertainty. To avoid decisions that lead to significant inefficiency in the long term, vehicles should be allocated to requests by optimizing a non-myopic utility function or by batching requests together and optimizing a myopic utility function. While the former approach is typically offline, the latter can be performed online. We point out two major issues with such approaches when applied to paratransit services in practice. First, it is difficult to batch paratransit requests together as they are temporally sparse. Second, the environment in which transit agencies operate changes dynamically (e.g., traffic conditions can change over time), causing the estimates that are learned offline to become stale. To address these challenges, we propose a fully online approach to solve the dynamic vehicle routing problem (DVRP) with time windows and stochastic trip requests that is robust to changing environmental dynamics by construction. We focus on scenarios where requests are relatively sparse—our problem is motivated by applications to paratransit services. We formulate DVRP as a Markov decision process and use Monte Carlo tree search to evaluate actions for any given state. Accounting for stochastic requests while optimizing a non-myopic utility function is computationally challenging; indeed, the action space for such a problem is intractably large in practice. To tackle the large action space, we leverage the structure of the problem to design heuristics that can sample promising actions for the tree search. Our experiments using real-world data from our partner agency show that the proposed approach outperforms existing state-of-the-art approaches both in terms of performance and robustness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS2012

Current-State Constrained Filter Bank for Wald Testing of Spacecraft Conjunctions

We propose a filter bank consisting of an ordinary current-state extended Kalman filter, and two similar but constrained filters: one is constrained by a null hypothesis that the miss distance between two conjuncting spacecraft is inside their combined hard body radius at the predicted time of closest approach, and one is constrained by an alternative complementary hypothesis. The unconstrained filter is the basis of an initial screening for close approaches of interest. Once the initial screening detects a possibly risky conjunction, the unconstrained filter also governs measurement editing for all three filters, and predicts the time of closest approach. The constrained filters operate only when conjunctions of interest occur. The computed likelihoods of the innovations of the two constrained filters form a ratio for a Wald sequential probability ratio test. The Wald test guides risk mitigation maneuver decisions based on explicit false alarm and missed detection criteria. Since only current-state Kalman filtering is required to compute the innovations for the likelihood ratio, the present approach does not require the mapping of probability density forward to the time of closest approach. Instead, the hard-body constraint manifold is mapped to the filter update time by applying a sigma-point transformation to a projection function. Although many projectors are available, we choose one based on Lambert-style differential correction of the current-state velocity. We have tested our method using a scenario based on the Magnetospheric Multi-Scale mission, scheduled for launch in late 2014. This mission involves formation flight in highly elliptical orbits of four spinning spacecraft equipped with antennas extending 120 meters tip-to-tip. Eccentricities range from 0.82 to 0.91, and close approaches generally occur in the vicinity of perigee, where rapid changes in geometry may occur. Testing the method using two 12,000-case Monte Carlo simulations, we found the method achieved a missed detection rate of 0.1%, and a false alarm rate of 2%.

Carpenter, J. Russell↗
NASA NTRS2010

Design and Implementation of the Automated Rendezvous Targeting Algorithms for Orion

The Orion vehicle will be designed to perform several rendezvous missions: rendezvous with the ISS in Low Earth Orbit (LEO), rendezvous with the EDS/Altair in LEO, a contingency rendezvous with the ascent stage of the Altair in Low Lunar Orbit (LLO) and a contingency rendezvous in LLO with the ascent and descent stage in the case of an aborted lunar landing. Therefore, it is not difficult to realize that each of these scenarios imposes different operational, timing, and performance constraints on the GNC system. To this end, a suite of on-board guidance and targeting algorithms have been designed to meet the requirement to perform the rendezvous independent of communications with the ground. This capability is particularly relevant for the lunar missions, some of which may occur on the far side of the moon. This paper will describe these algorithms which are designed to be structured and arranged in such a way so as to be flexible and able to safely perform a wide variety of rendezvous trajectories. The goal of the algorithms is not to merely fly one specific type of canned rendezvous profile. Conversely, it was designed from the start to be general enough such that any type of trajectory profile can be flown.(i.e. a coelliptic profile, a stable orbit rendezvous profile, and a expedited LLO rendezvous profile, etc) all using the same rendezvous suite of algorithms. Each of these profiles makes use of maneuver types which have been designed with dual goals of robustness and performance. They are designed to converge quickly under dispersed conditions and they are designed to perform many of the functions performed on the ground today. The targeting algorithms consist of a phasing maneuver (NC), an altitude adjust maneuver (NH), and plane change maneuver (NPC), a coelliptic maneuver (NSR), a Lambert targeted maneuver, and several multiple-burn targeted maneuvers which combine one of more of these algorithms. The derivation and implementation of each of these algorithms will be discussed in detail, as well and the Rendezvous Targeting "wrapper" which will sequentially tie them all together into a single onboard targeting tool which can produce a final integrated rendezvous trajectory. In a similar fashion, the various guidance modes available for flying out each of these maneuvers will be discussed as well. This paradigm of having the onboard guidance & targeting capability described above is different than the way the Space Shuttle has operated thus far. As a result, a discussion of these differences in terms of operations and ground and crew intervention will also be discussed. However, the general framework of how the mission designers on the ground first perform all mission design and planning functions, and then uplink that burn plan to the vehicle ensures that the ground will be involved to ensure safety and reliability. The only real difference is which of these functions will be done onboard vs. on the ground as done currently. Finally, this paper will describe the performance of each of these algorithms individually as well as the entire suite of algorithms as applied to the Orion ISS and EDS/Altair rendezvous missions in LEO. These algorithms have been incorporated in both a Linear Covariance environment and a Monte Carlo environment and the results of these dispersion analyses will be presented in the paper as well.

DSouza, Christopher↗
DOE OSTI2020

Ethanol Conversion over La 0.7 Sr 0.3 MnO 3–x (100): Autocatalysis, Adjacent O-Vacancies, Disproportionation, and Dehydrogenation

The mechanism for catalytic conversion of ethanol over La 0.7 Sr 0.3 MnO 3– x (100) surface to acetaldehyde and ethene was investigated. Pre-exposure temperature-programmed reaction (PE-TPR) experiments were performed in which ethanol was introduced to oxidized or reduced surfaces followed by heating. In particular, sequential PE-TPR experiments were conducted to incrementally and gradually reduce the surface. The products and their ratios were investigated as a function of surface reduction. The data show that acetaldehyde and ethene production is catalyzed with hydrogen abstraction and oxygen abstraction reactions occurring by intermediates in vacancies at various temperatures >400 K. Adsorption of acetaldehyde followed by a temperature-programmed reaction does not produce ethene, indicating that acetaldehyde is not an intermediate to ethene and that the hydrogen and oxygen abstraction from ethanol to ethene are decoupled steps. Further evidence for this mechanistic nuance was obtained using isotopically labeled ethanol (CD 3 CH 2 OH), which produces CD 3 CHO and CD 2 CH 2 . Additionally, the ratio of aldehyde production to alkene production increases with reduction, suggesting that aldehyde is produced from a disproportionation reaction between ethoxy species in adjacent O-vacancies, while ethene is produced from a dehydrogenation reaction with ethoxy species in vacancies without requiring adjacent O-vacancies. Counterintuitively, this finding indicates that the more oxygenated product (aldehyde vs ethene) is favored with more vacancies and that the net alcohol conversion is autocatalytic. Density functional theory calculations were able to find the previously unknown disproportionation pathway between ethoxies in adjacent O-vacancies, and kinetic Monte Carlo simulations support this interpretation by reproducing experimental selectivities. The activation energies for these pathways are estimated as 132 ± 10 kJ/mol for the disproportionation reaction (when occurring between ethoxies in adjacent vacancies) and as 148 ± 11 kJ/mol for the direct dehydrogenation reaction of an ethoxy in a vacancy. Based on these results, a mechanism with operative pathways based on elementary steps in O-vacancies is reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRSDate not supplied

Towards Plume Impingement Modeling in Space Environments

After 30 years human presence in low-earth orbit, NASA is returning to the moon and eventually will go to Mars. To this end, NASA is constructing the Lunar Gateway, an ISS-like space station to act as a home base for Lunar exploration. A large space station must be assembled while in orbit, using a “piecemeal” approach. In this context, it means that the different modules will arrive at different times and attach to what is already in service. The ISS provides an excellent example of this approach, and the proposed Lunar Gateway will undergo a similar assembly process. This assembly is achieved via “docking” maneuvers between modules, which are made possible by sequential firings of the onboard reaction control system (RCS) thrusters. They work by firing hot gases to produce adverse thrust and the needed change in velocity to safely finish the docking approach. The issue is that the gas from these thrusters' forms flow structures described as “plumes” and can impinge onto the outer surfaces of the space station, causing unwanted forces and moments, heat loads, sediment deposition, and in extreme cases, even surface erosion. All mechanisms that can damage the space station and must be avoided. Both permanent and visiting modules will have these RCS thruster exhaust impingement problems. Accurately and efficiently modeling these plume is an involved multi-physics calculation but also an important tool when designing the control algorithms of approaching modules. This poster presents progress towards this simulation on two fronts. First is the verification of OpenFOAM for rarefied plume impingement calculations by direct comparison to published DAC cases. Second is the estimation of plume impingement strikes over the time scale of an entire docking event. This is done by using a simple plume source flow model and a prescribed motion visualizer—coded in Python. Together these tools help push NASA's capabilities for simulating these plume impingement effects.

Rarefied Flows↗