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At least 1,477 records · Page 82
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Cosmic Inference: Constraining Parameters with Observations and a Highly Limited Number of Simulations

We look at cosmological probes that pose an inverse problem where the measurement result is obtained through observations, and the objective is to infer values of model parameters that characterize the underlying physical system-our universe, from these observations and theoretical forward-modeling. The only way to accurately forward-model physical behavior on small scales is via expensive numerical simulations, which are further “emulated” due to their high cost. Emulators are commonly built with a set of simulations covering the parameter space with Latin hypercube sampling and an interpolation procedure; the aim is to establish an approximately constant prediction error across the hypercube. In this paper, we provide a description of a novel statistical framework for obtaining accurate parameter constraints. The proposed framework uses multi-output Gaussian process emulators that are adaptively constructed using Bayesian optimization methods with the goal of maintaining a low emulation error in the region of the hypercube preferred by the observational data. In this paper, we compare several approaches for constructing multi-output emulators that enable us to take possible inter-output correlations into account while maintaining the efficiency needed for inference. Using a Lyα forest flux power spectrum, we demonstrate that our adaptive approach requires considerably fewer-by a factor of a few in the Lyα P(k) case considered here-simulations compared to the emulation based on Latin hypercube sampling, and that the method is more robust in reconstructing parameters and their Bayesian credible intervals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Optimal PV Inverter Control in Distribution Systems via Data-Driven Distributionally Robust Optimization

Distribution systems with high penetration of uncertain solar generation call for advanced control strategies of photovoltaics (PVs) inverters. This paper proposes a data-driven distributionally robust optimization (DDDRO) approach to optimally controlling the PV inverters to improve the system operation performance under solar power uncertainties. In the proposed DDDRO approach, a Wasserstein ball-based method is proposed to construct the distributional ambiguity set to model the uncertainties of PV generation through partial observations of historical data without knowing exact probability distributions. We further reformulate the computationally intractable DDDRO model to a mixed integer second order cone programming (MISOCP) problem. The effectiveness and out-of-sample performance of the proposed approach have been demonstrated on a modified IEEE 33-node system. We conduct a comparative study to compare the proposed method with traditional chance constrained programming (CCP). It shows that the proposed DDDRO approach can provide a less conservative yet robust solution to minimize the worse-case expectation of the total network loss while maintaining nodal voltages in a secure range.

Xue, Yaosuo↗
DOE OSTI2020

Simultaneously Integrating Single Atomic Cobalt Sites and Co 9 S 8 Nanoparticles into Hollow Carbon Nanotubes as Trifunctional Electrocatalysts for Zn–Air Batteries to Drive Water Splitting

The development of rechargeable metal–air batteries and water electrolyzers are highly constrained by electrocatalysts for the oxygen reduction reaction (ORR), oxygen evolution reaction (OER), and hydrogen evolution reaction (HER). However, the construction of efficient trifunctional electrocatalysts for ORR/OER/HER are highly desirable yet challenging. Herein, hollow carbon nanotubes integrated single cobalt atoms with Co9S8 nanoparticles (CoSA + Co 9 S 8 /HCNT) are fabricated by a straightforward in situ self-sacrificing strategy. The structure of the CoSA + Co 9 S 8 /HCNT are verified by X-ray absorption spectroscopy and aberration-corrected scanning transmission electron microscopy. Theoretical calculations and experimental results embrace the synergistic effects between Co 9 S 8 nanoparticles and single cobalt atoms through optimizing the electronic configuration of the CoN4 active sites to lower the reaction barrier and facilitating the ORR, OER, and HER simultaneously. Consequently, rechargeable liquid and all-solid-state flexible Zn–air batteries based on CoSA + Co 9 S 8 /HCNT exhibit remarkable stability and excellent power density of 177.33 and 51.85 mW cm -2 , respectively, better than Pt/C + RuO 2 counterparts. Moreover, the as-fabricated Zn–air batteries can drive an overall water splitting device assembled with CoSA + Co 9 S 8 /HCNT and achieve a current density of 10 mA cm -2 at a low voltage of 1.59 V, also superior to Pt/C + RuO 2 . Therefore, we conclude, this work presents a promising approach to an efficient trifunctional electrocatalyst toward practical applications.

25 ENERGY STORAGE↗
DOE OSTI2025

Convergence and Quantum Advantage of Trotterized MERA for Strongly-Correlated Systems

Strongly-correlated quantum many-body systems are difficult to study and simulate classically. We recently proposed a variational quantum eigensolver (VQE) based on the multiscale entanglement renormalization ansatz (MERA) with tensors constrained to certain Trotter circuits. Here, we determine the scaling of computation costs for various critical spin chains which substantiates a polynomial quantum advantage in comparison to classical MERA simulations based on exact energy gradients or variational Monte Carlo. Algorithmic phase diagrams suggest an even greater separation for higher-dimensional systems. Hence, the Trotterized MERA VQE is a promising route for the efficient investigation of strongly-correlated quantum many-body systems on quantum computers. Furthermore, we show how the convergence can be substantially improved by building up the MERA layer by layer in the initialization stage and by scanning through the phase diagram during optimization. For the Trotter circuits being composed of single-qubit and two-qubit rotations, it is experimentally advantageous to have small rotation angles. We find that the average angle amplitude can be reduced considerably with negligible effect on the energy accuracy. Benchmark simulations suggest that the structure of the Trotter circuits for the TMERA tensors is not decisive; in particular, brick-wall circuits and parallel random-pair circuits yield very similar energy accuracies.

Miao, Qiang [Duke Quantum Center, Duke University,↗
NASA NTRS1991

Small convolution kernels for high-fidelity image restoration

An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

Reichenbach, Stephen E.↗
NASA NTRSDate not supplied

Datascope to Enable Earth Independent Medical Operations (EIMO)

BACKGROUND: NASA has amassed sixty years of knowledge and experience relevant to maintenance of crew health and performance in low earth orbit. The Apollo Program introduced the importance of ensuring progressively autonomous operational capability. Earth Independent Medical Operations (EIMO) will require a gradual shift in the balance of medical responsibility, management, and authority from terrestrial to space-based assets. Terrestrial assets will continue to be essential for pre-mission screening and planning in addition to maintenance of crew health and performance. However, new capabilities are needed to enable EIMO and the amount of data required to support these systems, and mitigate the impacts of data transmission delays and reduced bandwidth coupled with lack of cloud-like resources and on-board computing capacity that is currently unclear or operationally insufficient. OVERVIEW: The overall goal of EIMO is to develop artificial intelligence (AI)-based solutions to analyze crew health and performance data utilizing a clinical decision support system (CDSS) to provide crew medical officers (CMO) with the equivalent of real-time, on-board medical consults. The EIMO ecosystem is envisioned as a “system of systems” where embedded reference databases and real-time data streams from multiple input vectors continuously and seamlessly assess crew health and performance. EIMO will be designed to make recommendations to the CMO using multi-modal AI-based natural language processing and machine learning methods with interoperability to push/pull data within and between multiple vehicle and habitat architectures. DISCUSSION: Data flows and storage/retrieval capacity are severely constrained during space missions and the challenges will become even greater during exploration missions. Just as each past program from Mercury to the International Space Station (ISS) required rethinking the interaction between ground-based controllers and space-based crew, so too will future missions to the Moon and Mars. While the NASA High-Performance Spaceflight Computing Processor project aims to increase computational capacity by 100 times over current spaceflight computers, the projected deliverable still lags considerably behind what will be needed to enable an AI-driven CDSS. Restrictions in processing speed and data storage capacity, coupled with transmission bottlenecks and delays, necessitate definition and optimization of an integrated data architecture to enable a progressively autonomous medical capability.

Medical operations↗
DOE OSTI2023

Constraining light thermal inelastic dark matter with NA64

A vector portal between the Standard Model and the dark sector is a predictive and compelling framework for thermal dark matter. Through co-annihilations, models of inelastic dark matter (iDM) and inelastic Dirac dark matter (i2DM) can reproduce the observed relic density in the MeV to GeV mass range without violating cosmological limits. In these scenarios, the vector mediator behaves like a semi-visible particle, evading traditional bounds on visible or invisible resonances, and uncovering new parameter space to explain the muon (g–2) anomaly. By means of a more inclusive signal definition at the NA64 experiment, we place new constraints on iDM and i2DM using a missing energy technique. With a recast-based analysis, we contextualize the NA64 exclusion limits in parameter space and estimate the reach of the newly collected and expected future NA64 data. Our results motivate the development of an optimized search program for semi-visible particles, in which fixed-target experiments like NA64 provide a powerful probe in the sub-GeV mass range.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2005

Constraining Oceanic Sources and Sinks of CO2 by Inverse Modeling: A First Step Toward Assimilation of In Situ and Remote Data

The primary goal of this collaborative project, lead by Nicholas Gruber at UCLA, is to better quantify the air-sea fluxes of pre-industrial and anthropogenic carbon dioxide CO2 for the global ocean with a newly developed inverse method. The method involves using ocean general circulation models (OGCMs) to characterize the subsurface distribution of tracers injected for different regions of the ocean surface. By linearly combining a series of these basis (or Greens) functions, one should be able to recreate any arbitrary ocean tracer field. In our case, we are using the global database of ocean dissolved inorganic carbon (DIC) from the WOCE/JGOFS global CO2 survey from the 1990s. The observed DIC field has been partitioned into pre-industrial and anthropogenic components using the empirical C* technique. We then solve for an optimal combination of the regional basis functions that best match the two sets observations in a least-squares sense with singular value decomposition. This in turn provides solutions for the regional air-sea CO2 fluxes (pre-industrial and anthropogenic) that are independent of more traditional estimates derived from surface water disequilibria in the partial pressure of CO2 and wind speed gas exchange parameterizations. We are apply the method to a suite of nine different OGCMs to test the robustness of the derived surface fluxes fields to differences in ocean circulation. Together with a collegue Keith Lindsay at NCAR, S. Doney's role in this project was to create the appropriate steady-state and temporally evolving basis functions from the NCAR CSM-1 ocean circulation model. Because of a slow start across the project in defining a common set of experimental protocols, we requested and were given a one year, no cost extension. Both the steady-state and temporally evolving basis functions were delivered to the UCLA group for further analysis. Additional information is included in the original extended abstract.

Doney, Scott↗
NASA NTRS1973

Constrained low-thrust guidance.

Constrained low thrust guidance algorithms for three axis and spin-stabilized, constant power, solar electric propelled spacecraft on fixed time rendezvous missions are developed. A 'bang-bang' type of minimum-propellant thrust program is used. Control constraints arise from the specification that the thrust vector must remain fixed relative to the solar panels. The guidance law is derived from deterministic linear perturbation theory and is controllable to first order on trajectories containing at least two thrust arcs. The number and timing of guidance updates and the effectiveness of the guidance law in compensating for state and control estimation biases and uncertainties are discussed. Numerical comparisons between the optimal control and the restricted control case are presented on a Encke comet rendezvous.

Ungs, M. J.↗
NASA NTRSDate not supplied

Neo – Mars Adaptive Training Integrative Knowledge System (MATRIKS) to Improve Operational Performance and its Neural Basis for Spaceflight

With prolonged mission durations, spaceflight crews will become increasingly dependent on onboard technologies for knowledge acquisition and maintenance. It is expected that not all skills and knowledge required for these missions can be retained and retrieved based on pre-mission training alone. Limited and delayed communication will significantly constrain support from Mission Control and crews will increasingly rely on autonomous onboard technologies to successfully perform post-landing operations. With the present project we will target NASA’s particular interest in developing and assessing an adaptive, just-in-time countermeasure that will consolidate and improve skills that are most relevant to space flight operations. To achieve this aim, NASA established a Virtual NASA Specialized Center of Research (VNSCOR)referred to as “Mars Adaptive Training Integrative Knowledge System (MATRIKS)”, comprising the following three projects: (1) “Trinity–Multi-Environment Virtual Training for Long Duration Exploration Missions”, PI: A. Anderson (UC Boulder); (2) “Morpheus–A Haptic Sensory Supplement to Optimize In-Flight Adaptive Training for Human Control of Spacecraft Robotic Arms”, PI: S. Robinson, UC Davis); and the present project “Neo–Adaptive Training integrative knowledge System to Improve Operational Performance and its Neural Basis for Spaceflight” (UPenn, PI: A.C. Stahn). Neo leverages a validated workstation called 6DF that simulates a rendezvous and docking maneuver using real spacecraft flight dynamics. It is designed to (1) train and improve sensorimotor skills relevant for inflight and post-landing operational tasks; (2) feature an autonomous and adaptive training approach that does not rely on feedback from flight operations on the ground; (3) maximize the transfer of mission-relevant motor skills; (4) allow the assessment of the neural circuitry underlying the task; and (5) deliver the training in a motivating and meaningful way to astronauts. Neocomprises two overarching aims: First, we will identify the neural circuitry underlying spaceflight relevant tasks by performing a subset of the 6DFtaskduring functional magnetic resonance imaging (MRI)in a total of up to N=30 subjects with varying levels of 6DF training experience. Second, as part of the above-mentioned VNSCOR MATRIKS the proposed 6DF autonomous intelligent tutor system will be integrated in an additive manner with a haptic feedback intervention (Morpheus), and a multi-environment virtual trainer(Trinity).It is expected that Neo, Morpheus and Trinity mutually complement each other to facilitate an effective countermeasure tool to acquire and retain operational skills that are critical for exploration class missions. To assess the efficacy of this combined effort, the VNSCOR MATRIKS will collect data inN=16 crew members in one HERA campaign of 45 days duration with N=16 crew members(four missions with N=4 crew member seach).The primary goal is to identify changes in operational performance as assessed by NASA’s simulator of Canadarm2 operations, i.e., Robotic On-board Trainer (ROBoT-r) in response to MATRIKS. As part of Neo we will also identify if, and to what extent MATRIKS will promote transfer to general cognitive performance (Cognition battery), distinctive visuo-spatial tasks critical for telerobotic tasks (Spatial Cognition battery), and affect brain structural changes and the neural circuitry of key brain networks expected to be relevant for spaceflight-related performance. At the conclusion of the research, we will have defined and demonstrated the use of a neuroscience-based, adaptive training integrative knowledge system to potentially mitigate visuo-spatial and sensorimotor brain changes associated with prolonged isolation and confinement to reduce the likelihood or impact of potential decrements in human performance capabilities during long-duration space missions. The expected significance of this 4-year project relates to its relevance for facilitating effective countermeasure tools to acquire and retain operational skills that are critical for exploration class missions. This will support the development of necessary countermeasures and technologies in support of human space exploration, focusing on mitigating operational performance risks.

A C Stahn↗
DOE OSTI2022

Estimating List-Mode Data Sensitivities to Nuclear Data with MCNP6

Nuclear data are a vital component of predictive simulations used in applications like experiment design, stockpile stewardship, nuclear nonproliferation/safeguards, health physics, and criticality safety. A singular simulation requires the coalescence of different areas of nuclear data such as cross sections, angular distributions, and energy distributions of emitted neutrons for different materials and energy ranges. Improving nuclear data and thus reducing the uncertainty in simulated parameters could enable smaller, better-informed safety factors and ultimately reduce operational and procedural costs. There is a constant effort to garner a better understanding of the physical quantities represented by nuclear data through experiments. Integral experiment benchmarks use simulated and measured results to validate current nuclear data values. In the past, benchmarks primarily focused on the effective multiplication factor (k eff ); however, this limited scope has caused compensating errors and areas of nuclear data that lack validation. Compensating errors are inaccuracies in nuclear data that are obfuscated by cancellation when observing integrated values such as k eff . Diverse integral benchmark experiments that look for quantities of interest other than k eff and include multiple responses minimize the possibility of compensating errors and provides validation to areas of nuclear data previously lacking experimental validation. Benchmark experiments can be optimized during the design process to be highly dependent on specific areas of nuclear data. The dependence of a response in an experiment to a specific area/type of nuclear data is defined as sensitivity. A larger sensitivity means that nuclear data uncertainties will play a larger role in the response(s) resulting in larger bias. Currently, the sensitivity capabilities of the Monte Carlo N-Particle (MCNP ®1 ) transport code are limited to responses of k eff and tallied values (e.g., flux, surface current). As a part of the EUCLID project, this work explores estimating list-mode nuclear data sensitivities that can be used to design experiments aimed to constrain and reduce compensating errors in nuclear data by focusing on responses other than k eff . Tallied values are ideal quantities that are estimated with detectors during experiments. List-mode data (a list of neutron collection times) are the direct output of detector systems in subcritical neutron noise experiments. Expanding MCNP sensitivity capabilities to include the sensitivity of responses estimated from list-mode data, such as the prompt neutron decay constant (α) and multiplicity estimates (S and D), enables more direct comparison of simulated and measured experimental quantities. Additionally, deterministic tools such as SENSMG are capable of obtaining sensitivities to a wide variety of responses; however, these tools cannot handle complex geometries due to the assumptions made in discretizing the phase-space variables of the Boltzman transport equation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Frequency reproducibility of solid-state thorium-229 nuclear clocks

Solid-state thorium-229 ( 229 Th) nuclear clocks are set to provide new opportunities for precision metrology and fundamental physics. Taking advantage of inherent low sensitivity of a nuclear transition to its environment, orders of magnitude more emitters can be hosted in a solid-state crystal compared with current optical lattice atomic clocks. Furthermore, solid-state systems needing only simple thermal control are key to the development of field-deployable compact clocks. Here we explore and characterize the frequency reproducibility of the 229 Th:CaF 2 nuclear clock transition, a key performance metric for all clocks. We measure the transition linewidth and centre frequency as a function of the doping concentration, temperature and time. We report the concentration-dependent inhomogeneous linewidth of the nuclear transition, limited by the intrinsic host crystal properties. We determine an optimal working temperature for the 229 Th:CaF 2 nuclear clock at 196(5) K, at which the first-order thermal sensitivity vanishes. This would enable in situ temperature co-sensing using different quadrupole-split lines, reducing the temperature-induced systematic shift below the 10 −18 fractional frequency uncertainty level. At 195 K, the reproducibility of the nuclear transition frequency is 220 Hz (fractionally 1.1 × 10 −13 ) for two differently doped 229 Th:CaF 2 crystals over 7 months. Furthermore, these results form the foundation for understanding, controlling and harnessing the coherent nuclear excitation of 229 Th in solid-state hosts and for their applications in constraining temporal variations of fundamental constants.

Atomic and molecular physics↗
NASA NTRS2011

A Concept for Flexible Operations and Optimized Traffic into Metroplex Regions

A "Flexible Flight Operations" concept for airport metroplexes was studied. A flexible flight is one whose destination airport is not assigned until a threshold is reached near the arrival area at which time the runway which reduces overall delay is assigned. The concept seeks to increase throughput by exploiting flexibility. The quantification of best-case benefits from the concept was pursued to establish whether concept research is warranted. Findings indicate that indeed the concept has potential for significant reductions in delay (and cost due to delay) in the N90 (NY/NJ) and SCT (Southern California) metroplexes. Delay reductions of nearly 26% are possible in N90 when 30% of the commercial airline flights are flexible (smartly selected by their low probability of connecting passengers); nearly 40% delay reduction is found when 50% of the flights are flexible. In the SCT metroplex, delay reductions estimates are greater. Greater reductions result at SCT since it is less constrained currently than N90, providing "more room" to take advantage of flexibility. Using the flexible operations concept for on-demand/air taxi and General Aviation flights were found to be beneficial at NY/NJ, indicating the flexible operations concepts may be useful to wide variety of users..

DeLaurentis, Daniel↗
DOE OSTI2026

Simultaneous ELM suppression and divertor detachment via synergistic boron powder and neon injection in EAST

A novel approach for simultaneous power exhaust and edge-localized mode (ELM) control is presented in the Experimental Advanced Superconducting Tokamak discharges, which utilize an ITER-like tungsten divertor. Real-time injection of boron (B) powder and neon (Ne) gas overcomes their limitations encountered when used separately. Pure Ne seeding leads to a narrow operational window constrained by core impurity accumulation and H-mode to L-mode back transitions, while pure solid B injection (SBI) is insufficient for effective divertor cooling. In comparison, their combined use achieves a stable, stationary, ELM-suppressed H-mode with adequate power exhaust. This synergistic scenario features partial energy detachment at the outer divertor while maintaining good plasma confinement (H 98 ∼ 1) with minimal degradation. Two key features of this scenario are: (1) the SBI triggers a persistent Edge Harmonic Mode (EHM), which provides a crucial continuous particle transport channel, preventing Ne and tungsten/molybdenum accumulation without flushing out by ELM, and (2) the B + Ne mixture allows for active optimization of the radiated power profile. Core radiation can be reduced by substituting a portion of the Ne with B, leveraging their complementary non-coronal equilibrium radiation efficiencies. This combined B + Ne injection scheme presents a promising pathway toward integrated core-edge scenarios, offering the potential to minimize total impurity throughput while leveraging an actuator (powder injection) already being considered for ITER.

Boron↗
NASA NTRS2011

Investigating the Nature of and Methods for Managing Metroplex Operations

A combination of traffic demand growth, Next Generation Air Transportation System (NextGen) technologies and operational concepts, and increased utilization of regional airports is expected to increase the occurrence and severity of coupling between operations at proximate airports. These metroplex phenomena constrain the efficiency and/or capacity of airport operations and, in NextGen, have the potential to reduce safety and prevent environmental benefits. Without understanding the nature of metroplexes and developing solutions that provide efficient coordination of operations between closely-spaced airports, the use of NextGen technologies and distribution of demand to regional airports may provide little increase in the overall metroplex capacity. However, the characteristics and control of metroplex operations have not received significant study. This project advanced the state of knowledge about metroplexes by completing three objectives: 1. developed a foundational understand of the nature of metroplexes; 2. provided a framework for discussing metroplexes; 3. suggested and studied an approach for optimally managing metroplexes that is consistent with other NextGen concepts

Atkins, Stephen↗
NASA NTRS2017

Efficient Trajectory Options Allocation for the Collaborative Trajectory Options Program

The Collaborative Trajectory Options Program (CTOP) is a Traffic Management Initiative (TMI) intended to control the air traffic flow rates at multiple specified Flow Constrained Areas (FCAs), where demand exceeds capacity. CTOP allows flight operators to submit the desired Trajectory Options Set (TOS) for each affected flight with associated Relative Trajectory Cost (RTC) for each option. CTOP then creates a feasible schedule that complies with capacity constraints by assigning affected flights with routes and departure delays in such a way as to minimize the total cost while maintaining equity across flight operators. The current version of CTOP implements a Ration-by-Schedule (RBS) scheme, which assigns the best available options to flights based on a First-Scheduled-First-Served heuristic. In the present study, an alternative flight scheduling approach is developed based on linear optimization. Results suggest that such an approach can significantly reduce flight delays, in the deterministic case, while maintaining equity as defined using a Max-Min fairness scheme.

Rodionova, O.↗
NASA NTRSDate not supplied

Autonomous Constrained Control for Arbitrary Thruster Configurations of Gimbaling Thrusters in SE(3)

In order to develop robust autonomy in spacecraft, it is desirable to develop methods for guiding and controlling arbitrarily-configured spacecraft with any combination of thrusters of various types, i.e. either static reaction control system thrusters and gimbaling thrusters. Scenarios in which autonomous selection of thrusters may be needed include the case of a stuck or inhibited thruster that restricts the motion of the vehicle, vehicles with changing mass properties such as logistics modules or tugs, or vehicles that have imposed constraints on thrusters during docking in order to avoid plume impingement on a space station or adjacent spacecraft. To that end, a spacecraft must be able to rapidly and autonomously reconfigure thruster firing histories and update guidance protocols in accordance with newly imposed constraints. In this paper, a methodology is presented that enables a spacecraft to autonomously select thrusters of any configuration and type in order to optimally match a desired 6-degree-of-freedom navigation and control within the special Euclidean SE(3) framework. The residual motion imposed by off-nominal thruster configurations or thrusters that are not fully controllable is identified by the spacecraft and solved for over time, both for static reaction control systems and for the case of gimbaling thrusters.

GN&C↗
DOE OSTI2026

Tests of LBNF Beam Monitor Prototypes for the DUNE Experiment

The Deep Underground Neutrino Experiment (DUNE) is a long-baseline on-axis neutrino oscillation experiment that will use a beam from the Long-Baseline Neutrino Facility (LBNF) to constrain the mixing angle $$\theta_{23}$, the neutrino mass hierarchy, and the CP violating phase $\delta_{CP}$. To ensure the beam remains on-axis, the LBNF beamline will employ two ionization chamber systems: the Hadron Alignment Detection System (HADeS) for primary beam alignment and the Muon Monitoring System (MuMS) for continuous beam monitoring and neutrino flux estimation. We have constructed prototypes for these systems at the University of Texas at Austin based on a design currently used in the NuMI hadron monitor. These prototypes were tested with a radioactive source and in beam tests at Fermilab's Irradiation Test Area. We present the results of these studies and discuss ongoing efforts to optimize the HADeS and MuMS designs.

Murthy, Chinmay↗