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NASA NTRS2007

Lunar Dust Characterization for Exploration Life Support Systems

Lunar dust effects can have a significant impact on the performance and maintenance of future exploration life support systems. Filtration systems will be challenged by the additional loading from lunar dust, and mitigation technology and strategies have to be adapted to protect sensitive equipment. An initial characterization of lunar dust and simulants was undertaken. The data emphasize the irregular morphology of the dust particles and the frequency dependence of lunar dust layer detachment from shaken surfaces.

Agui, Juan H.↗

NASA NTRS2011

Full Mission Astronaut Radiation Exposure Assessments for Long Duration Lunar Surface Missions

Risk to astronauts due to ionizing radiation exposure is a primary concern for missions beyond Low Earth Orbit (LEO) and will drive mission architecture requirements, mission timelines, and operational practices. For short missions, radiation risk is dominated by the possibility of a large Solar Particle Event (SPE). Longer duration missions have both SPE and Galactic Cosmic Ray (GCR) risks. SPE exposure can contribute significantly toward cancer induction in combination with GCR. As mission duration increases, mitigation strategies must address the combined risks from SPE and GCR exposure. In this paper, full mission exposure assessments were performed for the proposed long duration lunar surface mission scenarios. In order to accomplish these assessments, previously developed radiation shielding models for a proposed lunar habitat and rover were utilized. End-to-End mission exposure assessments were performed by first calculating exposure rates for locations in the habitat, rover, and during Extra-Vehicular Activities (EVA). Subsequently, total mission exposures were evaluated for the proposed timelines. Mission exposure results, assessed in terms of effective dose, are presented for the proposed timelines and recommendations are made for improved astronaut shielding and safer operational practices.

Adamczyk, Anne↗

NASA NTRS2004

Mitigation of Damage to the International Space Station (ISS) from Water Dumps

The International Space Station (ISS) and Orbiter dump water overboard. This water is from the ISS condensate system, and from the Orbiter s fuel cell (supply side) and wastewater (urine and condensate) systems. Water dumped from either the ISS or Orbiter is a possible source of damage. When water is dumped into a vacuum, some of it flashes into a vapor. The expanding vapor bursts the liquid stream into vapor, and small and large liquid/ice particles. The large liquid/ice particles are approximately 2 mm in diameter and have nominal velocities of approximately 31 Wsec (U.S. Lab) and 50 Wsec (Orbiter). As these liquid/ice particles impact, they can cause mechanical damage due to erosion/pitting of sensitive surfaces, including solar array or radiator surfaces. Solar arrays are of particular concern because of the thin optical coatings on the surface of the cells. The thickness of these coatings is in the range of 1300 to 44000 angstroms. Damage to these coatings can cause degradation of the cells optical characteristics. To mitigate damage from water dumps, the characteristics of the water dumps were studied and an impact code was used to study damage to sensitive surfaces. The results were used to develop the constraints needed to mitigate damage to ISS hardware from Orbiter and U.S. Lab dumps.

Schmidl, William↗

DOE OSTI2025

Development of direct ink write radially graded alumina/zirconia

Functionally graded materials (FGMs) are of interest in multiple fields, yet many materials combinations are limited by coefficient of thermal expansion (CTE) mismatch. Here, a radially graded alumina/yttria-doped zirconia (Al 2 O 3 /8YZ) FGM is used to demonstrate processing strategies to mitigate CTE and sintering behavior differences between these oxides. FGM materials are especially sensitive to ink stability during printing, as all components (in this case, Al 2 O 3 and 8YZ) must be stabilized in the same dispersant or additive solution. Thus, this system is also ideal to demonstrate ink optimization best practices. Materials were characterized throughout processing to correlate the effects of common additives on both the ceramic particle suspensions and final sintered components. Aggregation observed in the initial additive-containing suspensions were present in the sintered component. The differences in sintering onset temperature and shrinkage rate resulted in internal stresses within the sintered component, which ultimately caused mechanical failure of the component under low stress. In conclusion, a processing strategy was recommended to mitigate the sintering behavior mismatch of alumina and 8 wt% yttria-stabilized zirconia.

Lamm, Benjamin W. [Oak Ridge National Laboratory (↗

NASA NTRSDate not supplied

Developing Materials and Coating Technologies for Mitigation of Lunar Dust Adhesion and Abrasion

In order to support long duration missions on the Moon’s surface, materials resistant to the harsh lunar environment are critically needed. Lunar dust poses a major threat to the durability of components and vehicles due to its fine, jagged morphology and highly abrasive nature, which enables the particles to adhere and embed into surfaces of components and devices potentially leading to premature failure. Consequently, significant effort within NASA aims to develop novel materials and coating technologies to limit lunar dust adhesion and abrasion by exploring a variety of production routes and examining properties of candidate material systems, including ceramic, metallic and polymeric. Manufacturing methods investigated include traditional powder processing, additive manufacturing and surface modification via laser ablation patterning of bulk materials and coatings. An overview of ongoing NASA materials and coating research and development to enable lunar exploration will be presented.

Materials↗

DOE OSTI2024

Accelerating cavity fault prediction using deep learning at Jefferson Laboratory

Abstract Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive window criterion to identify fault events, ensuring a low false positive rate. Results obtained from analysis of a real dataset collected from the accelerating cavities simulating a deployed scenario demonstrate the model’s ability to identify normal signals with 99.99% accuracy and correctly predict 80% of slowly developing faults. Notably, these achievements were achieved in the context of a highly imbalanced dataset, and fault predictions were made several hundred milliseconds before the onset of the fault. Anticipating faults enables preemptive measures to improve operational efficiency by preventing or mitigating their occurrence.

43 PARTICLE ACCELERATORS↗

DOE OSTI2025

Post-DTL Beam Delivery

Ensuring that the beam delivered from the upgraded Front-End (FE) meets the Key Performance Parameters (KPPs) at each user facility is critical to the success of the LANSCE Accelerator Modernization Project (LAMP). For a high-intensity, multi-user facility like LANSCE, compliance with beam loss and radiation thresholds is as important as the charge delivered to each target. While early LAMPF/LANSCE operations relied on iterative tuning to minimize losses from beam halo and tail particles, the new FE may introduce different beam distributions and loss modes—making predictive modeling essential. To manage this, the F2E (Front-End to End) effort is developing detailed particle-tracking models that reflect realistic beamline conditions, including halo formation and expected diagnostic readings. These "snapshot" simulations aim to benchmark live machine performance at a given moment. This will help quantify how beam quality from the new FE will propagate downstream through the facility. Only by validating these models can we confidently assess and mitigate the potential impacts of the LAMP FE on beam delivery. Post-DTL, the beam splits to serve five major user facilities. Historically, low-energy beam transport has been modeled using TRACE, and higher-energy sections with TRANSPORT. These have now been unified into MAD-X format and validated with codes such as Elegant, pyOrbit, XSuite, Impact-Z, and HPSim. The primary focus now is on accurate modeling of full particle distributions (including beam halo) as they traverse the accelerator and beamlines to each experimental station. All models are at various stages of validation with empirical data.

43 PARTICLE ACCELERATORS↗

NASA NTRS2008

The Cosmic Ray Electron Excess

This slide presentation reviews the possible sources for the apparent excess of Cosmic Ray Electrons. The presentation reviews the Advanced Thin Ionization Calorimeter (ATIC) instrument, the various parts, how cosmic ray electrons are measured, and shows graphs that review the results of the ATIC instrument measurement. A review of Cosmic Ray Electrons models is explored, along with the source candidates. Scenarios for the excess are reviewed: Supernova remnants (SNR) Pulsar Wind nebulae, or Microquasars. Each of these has some problem that mitigates the argument. The last possibility discussed is Dark Matter. The Anti-Matter Exploration and Light-nuclei Astrophysics (PAMELA) mission is to search for evidence of annihilations of dark matter particles, to search for anti-nuclei, to test cosmic-ray propagation models, and to measure electron and positron spectra. There are slides explaining the results of Pamela and how to compare these with those of the ATIC experiment. Dark matter annihilation is then reviewed, which represent two types of dark matter: Neutralinos, and kaluza-Kline (KK) particles, which are next explained. The future astrophysical measurements, those from GLAST LAT, the Alpha Magnetic Spectrometer (AMS), and HEPCAT are reviewed, in light of assisting in finding an explanation for the observed excess. Also the Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) could help by revealing if there are extra dimensions.

Chang, J.↗

NASA NTRS2017

Cloudy with a Chance of Solar Flares: The Sun as a Natural Hazard

Space weather is a naturally occurring phenomenon that represents a quantifiable risk to space- and ground-based infrastructure as well as society at large. Space weather hazards include permanent and correctable faults in computer systems, Global Positioning System (GPS) and high-frequency communication disturbances, increased airline passenger and astronaut radiation exposure, and electric grid disruption. From the National Space Weather Strategy, published by the Office of Science and Technology Policy in October 2015, space weather refers to the dynamic conditions of the space environment that arise from emissions from the Sun, which include solar flares, solar energetic particles, and coronal mass ejections. These emissions can interact with Earth and its surrounding space, including the Earth's magnetic field, potentially disrupting technologies and infrastructures. Space weather is measured using a range of space- and ground-based platforms that directly monitor the Sun, the Earth's magnetic field, the conditions in interplanetary space and impacts at Earth's surface, like neutron ground-level enhancement. The NASA Goddard Space Flight Center's Space Weather Research Center and their international collaborators in government, industry, and academia are working towards improved techniques for predicting space weather as part of the strategy and action plan to better quantify and mitigate space weather hazards. In addition to accurately measuring and predicting space weather, we also need to continue developing more advanced techniques for evaluating space weather impacts on space- and ground-based infrastructure. Within the Earth's atmosphere, elevated neutron flux driven by atmosphere-particle interactions from space weather is a primary risk source. Ground-based neutron sources form an essential foundation for quantifying space weather impacts in a variety of systems.

neutron flux↗

NASA NTRS2009

Overview of Materials International Space Station Experiment 7B

Materials International Space Station Experiment 7B (MISSE 7B) is the most recent in a series of experiments flown on the exterior of International Space Station for the purpose of determining the durability of materials and components in the space environment. A collaborative effort among the Department of Defense, the National Aeronautics and Space Administration, industry, and academia, MISSE 7B will be flying a number of NASA experiments designed to gain knowledge in the area of space environmental effects to mitigate risk for exploration missions. Consisting of trays called Passive Experiment Containers, the suitcase sized payload opens on hinges and allows active and passive experiments contained within to be exposed to the ram and wake or zenith and nadir directions in low Earth orbit, in essence, providing a test bed for atomic oxygen exposure, ultraviolet radiation exposure, charged particle radiation exposure, and thermal cycling. New for MISSE 7B is the ability to monitor experiments actively, with data sent back to Earth via International Space Station communications. NASA?s active and passive experiments cover a range of interest for the Agency. Materials relevant to the Constellation Program include: solar array materials, seal materials, and thermal protection system materials. Materials relevant to the Exploration Technology Development Program include: fabrics for spacesuits, materials for lunar dust mitigation, and new thermal control coatings. Sensors and components on MISSE 7B include: atomic oxygen fluence monitors, ultraviolet radiation sensors, and electro-optical components. In addition, fundamental space environmental durability science experiments are being flown to gather atomic oxygen erosion data and thin film polymer mechanical and optical property data relevant to lunar lander insulation and the James Web Space Telescope. This paper will present an overview of the NASA experiments to be flown on MISSE 7B, along with a summary of the thermal environment to be expected during the 1 yr mission scheduled for launch in 2009.

Jaworske, Donald A.↗

NASA NTRS2004

Mitigation of High Altitude and Low Earth Orbit Radiation Effects on Microelectronics via Shielding or Error Detection and Correction Systems

The NASA Cooperative Agreement NAG4-210 was granted under the FY2000 Faculty Awards for Research (FAR) Program. The project was proposed to examine the effects of charged particles and neutrons on selected random access memory (RAM) technologies. The concept of the project was to add to the current knowledge of Single Event Effects (SEE) concerning RAM and explore the impact of selected forms of radiation on Error Detection and Correction Systems. The project was established as an extension of a previous FAR awarded to Prairie View A&M University (PVAMU), under the direction of Dr. Richard Wilkins as principal investigator. The NASA sponsored Center for Applied Radiation Research (CARR) at PVAMU developed an electronic test-bed to explore and quantify SEE on RAM from charged particles and neutrons. The test-bed was developed using 486DX microprocessor technology (PC-104) and a custom test board to mount RAM integrated circuits or other electronic devices. The test-bed had two configurations - a bench test version for laboratory experiments and a 400 Hz powered rack version for flight experiments. The objectives of this project were to: 1) Upgrade the Electronic Test-bed (ETB) to a Pentium configuration; 2) Accommodate more than only 8 Mbytes of RAM; 3) Explore Error Detection and Correction Systems for radiation effects; 4) Test modern RAM technologies in radiation environments.

Gupta, Kajal↗

DOE OSTI2024

Space Charge Dominated Momentum Spread and Compensation Strategies in the Post-Linac Section of Proton Improvement Plan-II at Fermilab

The upcoming Proton Improvement Plan-II (PIP-II), designated for enhancements to the Fermilab accelerator complex, features a Beam Transfer Line (BTL) that channels the beam from the linac exit to the booster. In the absence of longitudinal focusing beyond the superconducting linac, the beam experiences an elevated momentum spread, primarily due to nonlinear space-charge forces, surpassing the allowable limit of 2.1e-4. This study presents a detailed examination of the space-charge-induced momentum spread and outlines mitigative strategies. The investigation includes the fine-tuning of a de-buncher cavity, analyzed in terms of operating frequency, longitudinal location, and gap voltage, under both standard and perturbed beam conditions—specifically accounting for momentum jitter and energy variation. The impact of buncher cavity misalignments on the beam's longitudinal phase space is also assessed. The paper concludes by recommending an optimized cavity configuration to effectively mitigate the observed increase in momentum spread along the BTL.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Gain Stability of Hamamatsu R5912-MOD Photo-Multipliers at Low Temperature

The Photon Detection System is a crucial component of the ICARUS detector in the Short Baseline Neutrino (SBN) Program at Fermi National Accelerator Laboratory (FNAL). It consists of 360 Photo Multiplier Tubes (PMTs) 8” Hamamatsu R5912-MOD and, since June 2020, it has been operated at the liquid Argon cryogenic temperature. During these years, the PMTs have shown gain losses as an aging effect. Using a climatic chamber at the INFN Sezione di Catania, we confirmed a stable gain for a single PMT 8” Hamamatsu 5912-MOD when operated at room temperature, and a persistent gain loss at temperatures around -70°C, although far from the liquid Argon one. No gain recovery was obtained bringing the PMT back to room temperature. We suspect that dynode deterioration due to temperature gradient plays a significant role in this phenomenon. During our test, the PMT was illuminated by a 520 nm laser source and operated in current mode. The laser beam was split into two optical fibers, the first one transmitting light through Neutral Density filters and then diffusing it over the surface of the PMT photocathode. The other optical fiber was used for an independent reference measurement of the injected light via a bolometric photodetector. In this presentation, the main technical characteristics of the measurement system are shown together with preliminary results which need further investigation to elucidate the underlying mechanisms driving the gain loss and to propose new mitigation strategies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

A Data-Agnostic, Continuous Machine Learning Framework for Application in High Energy Physics and Beyond: Phase 1 Final Scientific/Technical Report

This Phase 1 effort has focused on the development of continual learning frameworks for use in machine learning, specifically in the applied context of High Energy Physics (HEP). Machine learning (ML) is a transformative technology by which computers, typically through the use of neural networks, are able to perform tasks with proficiency that rivals or surpasses that of human users. Model Degradation & Catastrophic Forgetting are two undesired phenomena which can occur in ML where the performance of a model degrades when either deployed on novel data streams, or trained on novel data which are sufficiently different than the data the models were initially trained on. A natural example where these sorts of effects can be observed is in the performance of detectors in harsh environments, where the detector signature may change over the lifetime of the detector as it ages and deteriorates — precisely what occurs in the experiments conducted in HEP. Real world HEP data is therefore an excellent test-ground and use-case for Continual Learning paradigms, which are techniques used in ML to counteract these problems. Ensemble learning is one such technique, where multiple smaller models are trained on subsets of the overall data and are ensembled together during inference. The intuition behind this technique is that, although there are shifts in the distributions which govern the incoming data streams, these shifts are not expected to be homogeneous or global. If a sufficient diversity in solutions within the various sub-models has been achieved, then at least one sub-model is expected to retain its performance within the overall ensemble. One further strength of this approach is that the architectures of the various models do not need to be identical, and in fact even different modalities of data can naturally be combined in this way. This work focused on applying ensemble learning techniques to derive results using two main datasets, anomaly detection in HEP data & time-series forecasting in semiconductor manufacturing data. Semiconductor manufacturing involves data with surprising similarity to that of HEP (e.g. wafer maps look very similar to digi-occupancy maps) and Cerium Lab’s prominence within the semiconductor industry makes semiconductor manufacturing a natural opportunity for commercialization of this work. Our efforts have led to two strong results. The first is that we evaluated the proposed ensembling techniques using previously proposed machine learning architectures for use in anomaly detection, namely AutoEncoder based models and their derivatives. We also developed new architectures which have not been evaluated in this context before. In fact, this work marks the first use of Vision Transformers for anomaly detection in HEP. Second, we demonstrated that ensemble learning significantly improves model performance in scenarios prone to degradation, validating its effectiveness across both HEP and semiconductor datasets. These results further support ensemble learning as a powerful strategy for mitigating catastrophic forgetting and maintaining robust performance in evolving data environments.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

PID-Regulated Heating System for PIP-II Reference Line

The Proton Improvement Project-2 centers on building a new superconducting linear particle accelerator (Linac) at Fermilab. At the heart of the accelerator is the reference line, a critical system that defines the ideal path for the particle beam as it passes through magnets, RF cavities, and other beamline elements. Temperature stability is crucial for the reliable operation of RF components, such as mixers and filters. Fluctuations affect key performance parameters like conversion loss, isolation, and linearity. To mitigate any drift caused by ambient temperature changes, a heating plate assembly is utilized to maintain key components at a controlled temperature of 40°C. The system utilizes an aluminum 36”x36”x0.5” heat plate powered by a MOSFET-based control circuit, delivering approximately 460 W of thermal energy through a resistor array. Real-time temperature feedback is provided by a PT100 Resistance Temperature Detector (RTD), which interfaces with a Proportional–Integral–Derivative (PID) control algorithm to maintain closed-loop temperature regulation. The control signal actively modulates the gate voltage of an N channel MOSFET, dynamically adjusting power delivery in response to deviations from the temperature setpoint. Simulations and LTspice models validate the functionality and responsiveness of the circuit under varying conditions. The prototype has successfully demonstrated stable thermal control, paving the way for integration into the PIP-II infrastructure. The final design will feature an expanded resistor array, as well as communication with a PLC for continuous data acquisition and diagnostics. This work directly supports Fermilab’s broader mission by contributing to the stability and reliability of core accelerator systems, enhancing the precision of particle beam delivery for future physics experiments.

Mosher, Alexander [Fermilab]↗

DOE OSTI2024

Evaluation of SPARC divertor conditions in H-mode operation using SOLPS-ITER

The predicted divertor conditions for the SPARC tokamak are calculated using SOLPS-ITER for a range of scrape-off-layer (SOL) heat flux widths λ q , input powers, and particle fueling locations. Under H-mode scenario conditions with an upstream separatrix density of 1 x 10 20 m -3 , the most conservative range of λ q extrapolations ( 0.15 mm) results in extremely high unmitigated particle and energy fluxes to the divertor, both under full field (12.2 T) and power (P SOL = 29 MW) conditions, and 2/3 field with P SOL = 10 MW. Increasing the cross-field SOL diffusivities by 2–10× reduces the magnitude of the mitigation challenge, however strategies such as impurity seeding or strike-point-sweeping will likely still be required. A combination of steady-state and time-dependent SOLPS-ITER simulations are used to map out phase space diagrams of upstream and divertor conditions. The simulations include parallel currents but neglect cross-field drifts. At low upstream density the inner and outer divertor conditions are highly asymmetric, with a large temperature difference and significant heat fluxes driven by parallel currents. The solution has sharp bifurcations with a region of hysteresis, depending on whether the initial state is at a low or high density. This behavior is observed even when the fueling location, cross-field diffusivity, and impurity level is changed, although the density window with asymmetry is reduced with increasing diffusivity. The addition of neon impurity seeding reduces the divertor heat fluxes, but also causes a drop in the upstream electron density with fixed particle throughput. This drop can be counteracted by increased main ion throughput, however too much neon results in a back transition into the asymmetric divertor regimes suggesting a need for control of both main ion and impurity seeding levels to achieve a desired divertor state.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Tailoring the Reaction Heterogeneity for Robust Li‐Rich Cathodes

The practical application of Li-rich Mn-based layered oxides (LLO) cathode is hindered by severe capacity and voltage degradation resulting from severe oxygen release and irreversible phase transition. In this work, the reaction heterogeneity, which describes the spatially resolved electrochemical divergence within individual cathode particles, is engineered through compositional gradient design to couple Li + transport kinetics and the anion redox activity between particle interiors and surfaces. It is revealed that Co/Mn concentration gradient within particles creates heterogeneous phase content distribution and structural ordering, inducing surface-bulk reaction heterogeneity that significantly impacts the overall electrochemical performance. Specifically, Li 2 MnO 3 -poor and Co-enriched surface effectively mitigates the oxygen loss and enhances electrochemical reaction kinetics, benefited from the reduced surface redox reactivity and induced highly ordered intra-layered cationic arrangement. Meanwhile, the Li 2 MnO 3 -enriched core with slight Li/Ni intermixing provides high reversible capacity and strong mechanical stability. Consequently, the greatly enhanced anion redox reversibility, Li + diffusion dynamics, and structure stability endow LLO with exceptional electrochemical properties, showing a capacity retention of 86.0% and a reduced voltage decay of 0.518 mV per cycle after 500 cycles at 1 C. This work provides a valuable strategy to tailor the redox chemistry and achieve robust LLO.

25 ENERGY STORAGE↗

NASA NTRSDate not supplied

Aerosol Physics for the Lunar Environment: Equations for Lunar Dust Control and Mitigation Technologies

Sticky and jagged dust was ubiquitous during the Apollo missions, causing soiling and abrasion problems with seals, coatings and equipment, in addition to eye irritation and breathing discomfort in the cabin. The Artemis Program of NASA aims to place astronauts on the lunar surface by 2024 and establish a sustainable presence in the following decade. Returning to the Moon requires controlling and mitigating the dust which will be inevitably brought inside the cabins. The state-of-the-science for effective collection of aerosols is based on dynamics of airborne particulate matter under terrestrial conditions. However, the governing physics does not apply to extra-vehicular activity in the hard-vacuum lunar condition. For example, the substantial difference in gravity will dictate particle transport both outside and inside the cabin. In this study, we revisited the aerosol physical phenomena that are assumed in the design of Earth-based aerosol instruments and extend the applicability to different scenarios in lunar missions. As shown, long-term lunar habitats, transfer vehicles to lunar orbital platforms, and low pressure cabin atmospheres have different aerosol dynamics. In all cases, the impact of dust control strategies using gravitational, electrical, and thermal techniques for various mitigation and monitoring hardware is explored. The guidelines provided through this study will show how terrestrial aerosol equipment can translate to lunar dust applications.

Nima Afshar-Mohajer↗