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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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NASA NTRS1993

Teaching high-performance skills using above-real-time training

The above real-time training (ARTT) concept is an approach to teaching high-performance skills. ARTT refers to a training paradigm that places the operator in a simulated environment that functions at faster than normal time. It represents a departure from the intuitive, but not often supported, feeling that the best practice is determined by the training environment with the highest fidelity. This approach is hypothesized to provide greater 'transfer value' per simulation trial, by incorporating training techniques and instructional features into the simulator. Two related experiments are discussed. In the first, 25 naive male subjects performed three tank gunnery tasks on a simulator under varying levels of time acceleration (i.e., 1.0x, 1.6x, 2.0x, sequential, and mixed). They were then transferred to a standard (1.0x) condition for testing. Every accelerated condition or combination of conditions produced better training and transfer than the standard condition. Most effective was the presentation of trials at 1.0x, 1.6x, and 2.0x in a random order during training. Overall, the best ARTT group scored about 50 percent higher and trained in 25 percent less time compared to the real-time control group. In the second experiment, 24 mission-capable F-16 pilots performed three tasks on a part-task F-16A flight simulator under varying levels of time compression (i.e., 1.0x, 1.5x, 2.0x, and random). All subjects were then tested in a real-time environment. The emergency procedure (EP) task results showed increased accuracy for the ARTT groups. In testing (transfer), the ARTT groups not only performed the EP more accurately, but dealt with a simultaneous enemy significantly better than a real-time control group. Although the findings on an air combat maneuvering task and stern conversion task were mixed, most measures indicated that the ARTT groups performed better and faster than a real-time control group. Other implications for ARTT are discussed along with future research directions.

Guckenberger, Dutch↗
NASA NTRS2007

Effects of Artificial Gravity and Bed Rest on Spatial Orientation and Balance Control

While the vestibular system should be well-adapted to bed rest (a condition it experiences approximately 8/24 hrs each day), questions remain regarding the degree to which repeated exposures to the unusual gravito-inertial force environment of a short-radius centrifuge might affect central processing of vestibular information used in spatial orientation and balance control. Should these functions be impaired by intermittent AG, its feasibility as a counter-measure would be diminished. We, therefore, examined the effects of AG on spatial orientation and balance control in 15 male volunteers before and after 21 days of 6 HDT bed rest (BR). Eight of the subjects were treated with daily 1hr AG exposures (2.5g at the feet; 1.0g at the heart) aboard a short radius (3m) centrifuge, while the other seven served as controls (C). Spatial orientation was assessed by measures of ocular counter-rolling (OCR; rotation of the eye about the line of sight, an otolith-mediated reflex) and subjective visual vertical (SVV; perception of the spatial upright). Both OCR and SVV measurements were made with the subject upright, lying on their left sides, and lying on their right sides. OCR was measured from binocular eye orientation recordings made while the subjects fixated for 10s on a point target directly in front of the face at a distance of 1 m. SVV was assessed by asking subjects (in the dark) to adjust to upright (using a handheld controller) the orientation of a luminous bar randomly perturbed (15) to either side of the vertical meridian. Balance control performance was assessed using a computerized dynamic posturography (CDP) protocol similar to that currently required for all returning crew members. During each session, the subjects completed a combination of trials of sensory organization test (SOT) 2 (eyes closed, fixed platform) and SOT 5 (eyes closed, sway-referenced platform) with and without static and dynamic pitch plane head movements (plus or minus 20 deg., dynamic paced by an audible tone at 0.33Hz). OCR and CDP performance were unaffected by BR and BR+AG; post-BR measures were unchanged from baseline for both AG and C groups. Similarly, BR did not affect SVV in the C group. However, BR+AG disrupted one measure of spatial orientation: SVV error was significantly increased on R+0 and R+1 following BR in the AG group. These results suggest a transient untoward effect on central vestibular processing may accompany repeated exposure to intermittent AG, a potential side-effect that should be studied more closely in future studies.

Paloski, William H.↗
NASA NTRS2019

Cleanroom Contamination Identification Method Development

During fabrication, assembly, and testing of spacecraft and flight hardware it is vital to avoid contaminants that can cause degradation and could result in significant failure. Yet, there is no existing contamination monitoring method that provides the identity of airborne particles in a cleanroom facility. Knowing the particle identities, would allow scientists and engineers to determine the source of the contaminants and prevent setbacks before they occur or cause damage. Current cleanliness monitoring methods include airborne particle counters (APCs), fallout filters, and visual inspections. Particle counts from APCs are the primary metric used to define a cleanroom class and hence its level of cleanliness, but do not provide identification nor can they differentiate between large and small sizes of particles. In addition, using fallout filters is not a proactive, timely, or representative approach to cleanroom contamination monitoring because these samples are only retrieved after 30 days and are placed away from spacecraft processing to avoid interference with operations. In contrast, the forced air sampling method can collect a sample within an hour at any location required and provide results in less than a day. This system uses a cassette and filter sample medium to capture airborne particles which are then taken to a scanning electron microscope with energy dispersive spectroscopy (SEM/EDS) to identify and size the captured particles. Development of forced air sampling into an established laboratory capability will allow for fast sampling and routine identification of unknown contamination sources within the cleanroom. The test method development required market research for an air sampling cassette that increases sample collection efficiency and a filter with low enough background contamination to allow differentiation between a blank (control) and the collected sample. It was determined that a conductive black cassette and a polycarbonate filter were the best options. Conductive black cassettes, in comparison to the standard styrene, are manufactured using polypropylene filled with carbon. This makes the cassette conductive and minimizes the tendency of particles to stick to the wall of the cassette due to electrostatic force. In previous trials a mixed cellulose ester (MCE) filter was used to capture the contaminants, however the rougher surface of the filter contributed to entrapment of the particles within the filter structure and made it harder to identify the particles. In comparison, track etched polycarbonate filters have random cylindrical pores and a smooth surface which contributes to uniform sample distribution on the surface of the filter. Future work includes: testing the system using control samples to determine the efficiency and suitability of the medium, performing sample collection in various environments to establish ideal operating parameters and analyzing contaminant particles using SEM/EDS and assistant characterization techniques. Once fully developed, employing the forced air sampling method will help to prevent damage to spacecraft, avoid schedule delays, and allow for mission success.

Hernandez Melendez, Jailyn M.↗
NASA NTRS2009

Evaluation of Learning Associated with Multiple Exposures to Computerized Dynamic Posturography

Computerized dynamic posturography has been used to quantitatively assess the time course of functional sensorimotor recovery after exposure to spaceflight or to groundbased analogs such as head-down bed rest. An assessment of balance recovery may be confounded as subjects develop new strategies through repeated exposures to test paradigms. The purpose of this control study was to characterize the learning effects of sensory organization and motor control tests across multiple sessions. METHODS: Twenty-eight healthy subjects were tested over four sessions. To examine the effects of between-session interval, subjects were assigned to one of four groups in which the interval between the 1 st and 2nd sessions was 7 (+/- 1) days, 14 (+/-1) days, 28 (+/-2) days, or 56 (+/-3) days. The interval between remaining sessions was 28 (+/-4) days. Peak-to-peak anterior-posterior sway was measured during standard Sensory Organization Tests (SOTs) using either fixed or unstable sway-referenced support with eyes open, eyes closed, or sway-referenced vision. Sway was also measured during modified SOTs using eyes-closed conditions with either static or dynamic head tilts. Postural recovery to unexpected support surface perturbations (translations or rotations) was measured during Motor Control Tests. The test order was block randomized across subjects. RESULTS: The learning effects varied with test condition. There were no measurable differences with a stable support surface. The more challenging conditions (unstable support surface with and without head tilts) led to greater differences and took more trials to stabilize. The effect of time interval between the first two sessions was negligible across conditions. Evidence suggested that learning carried across similar conditions (such as unstable support SOTs). DISCUSSION: Familiarization session and/or trials are recommended to minimize learning effects when characterizing functional recovery after exposure to altered sensory environments. The number of practice trials required depends on task difficulty and similarity across conditions. Learning statement: This presentation will review the learning effects of computerized d

Dean, S. Lance↗
NASA NTRS2007

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗
NASA NTRS2011

FPGA Implementation of Stereo Disparity with High Throughput for Mobility Applications

High speed stereo vision can allow unmanned robotic systems to navigate safely in unstructured terrain, but the computational cost can exceed the capacity of typical embedded CPUs. In this paper, we describe an end-to-end stereo computation co-processing system optimized for fast throughput that has been implemented on a single Virtex 4 LX160 FPGA. This system is capable of operating on images from a 1024 x 768 3CCD (true RGB) camera pair at 15 Hz. Data enters the FPGA directly from the cameras via Camera Link and is rectified, pre-filtered and converted into a disparity image all within the FPGA, incurring no CPU load. Once complete, a rectified image and the final disparity image are read out over the PCI bus, for a bandwidth cost of 68 MB/sec. Within the FPGA there are 4 distinct algorithms: Camera Link capture, Bilinear rectification, Bilateral subtraction pre-filtering and the Sum of Absolute Difference (SAD) disparity. Each module will be described in brief along with the data flow and control logic for the system. The system has been successfully fielded upon the Carnegie Mellon University's National Robotics Engineering Center (NREC) Crusher system during extensive field trials in 2007 and 2008 and is being implemented for other surface mobility systems at JPL.

Random access memory↗
NASA NTRS2009

Characterization of the Head Stabilization Response to a Lateral Perturbation During Walking in Older Adults

A main contributor of fractures in older adults is from a lateral fall. The decline in sensory systems results in difficulty maintaining balance stability. Head stabilization contributes to postural control by serving as a stable platform for the sensory systems. The purpose of this study was to characterize the head stabilization response to a lateral perturbation while walking. A total of 16 healthy older adults, aged 66-81 years, walked across a foam pathway 6 times. One piece of the foam pathway covered a movable platform that translated to the left when the subject stepped on the foam. Three trials were randomized in which the platform shifted. Angular rate sensors placed on the center of mass of the head and trunk collected head and trunk movement in all three planes of motion. The roll plane was analyzed to examine motion in the plane of the perturbation. Subjects stepped onto the platform with the right foot. Recovery step time and distance were recorded. The first trial was analyzed to capture the novelty of the perturbation. Results indicate a significant difference in footfall distance t=0.004, p<0.05, as well as the speed of foot recovery t=0.001, p<0.05, between natural and perturbed walking. Results indicate that the head t=0.005, p<0.05, and trunk t=0.0001, p<0.05, velocities increase during perturbed compared to natural walking. Older adults place their recovery foot down faster when perturbed to re-establish their base of support. Head and trunk segments are less stable and move with greater velocities to reestablish stability when perturbed.

Buccello-Stout, Regina R.↗
DOE OSTI2025

The Evolution of Randomized Clinical Trial Designs to Assess Therapeutics in Alzheimer Disease

Importance The success of recent randomized clinical trials (RCTs) for Alzheimer disease (AD), particularly those focusing on anti-amyloid therapies, has been discussed at length. However, the evolution of RCT design features for AD that preceded this success remain underexplored. Objective To describe temporal changes in the features of RCT design for interventions in AD. Evidence Review PubMed, Scopus, and Web of Science databases were searched in January 2025 for phase 2 and 3 AD RCTs published between January 1992 and December 2024. RCTs that investigated an intervention for AD, with a placebo or standard-of-care control group, were included. Four assessors independently reviewed full-text articles to capture study characteristics. Main Outcomes and Measures The number of participants and the duration of RCTs as well as the target population, outcomes, and funding were extracted from published reports. These features were analyzed with respect to time using linear regression and χ 2 analyses. Results The study included 203 RCTs with 79 589 participants testing interventions in AD. From 1992 to 2024, the mean sample size increased by 464% for phase 2 RCTs (from 42 to 237), and 50% for phase 3 RCTs (from 632 to 951), while the mean trial duration increased by 188% (from 16 to 46 weeks) for phase 2, and 256% (from 20 to 71 weeks) for phase 3 RCTs. This longer duration of RCTs may be partially attributed by a greater share of disease-modifying rather than symptomatic treatments. Similarly, more recent trials required AD biomarker evidence for enrollment (from 1 of 36 [2.7%] before 2006 to 40 of 76 [52.6%] since 2019). A substantial difference in the type of therapeutics researched was observed, with anti-amyloid and anti-tau RCTs being more likely to be funded by the pharmaceutical industry compared with neurotransmitter or other RCTs (anti-amyloid or anti-tau, 68 of 71 [95.8%]; neurotransmitter, 52 of 69 [77.6%]; other, 33 of 52 [63.5%]). RCT transparency improved, with more frequent data accessibility statements, registered reports, and better reporting on race and ethnicity. Conclusions and Relevance This methodology research of AD RCTs highlights substantial changes in key features of AD clinical trials from 1992 to 2024. AD RCTs have become larger and longer, such that they are powered to detect smaller clinical differences. The increased sample sizes and duration should enable the detection of smaller and more slowly occurring outcomes, which may lead to successful RCTs of therapies with slower and more subtle efficacy.

General & Internal Medicine↗
NASA NTRS1974

Modern control concepts in hydrology

Two approaches to an identification problem in hydrology are presented based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time invariant or time dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and conform with results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second, by using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

Duong, N.↗
NASA NTRS2002

A statistical model for interpreting computerized dynamic posturography data

Computerized dynamic posturography (CDP) is widely used for assessment of altered balance control. CDP trials are quantified using the equilibrium score (ES), which ranges from zero to 100, as a decreasing function of peak sway angle. The problem of how best to model and analyze ESs from a controlled study is considered. The ES often exhibits a skewed distribution in repeated trials, which can lead to incorrect inference when applying standard regression or analysis of variance models. Furthermore, CDP trials are terminated when a patient loses balance. In these situations, the ES is not observable, but is assigned the lowest possible score--zero. As a result, the response variable has a mixed discrete-continuous distribution, further compromising inference obtained by standard statistical methods. Here, we develop alternative methodology for analyzing ESs under a stochastic model extending the ES to a continuous latent random variable that always exists, but is unobserved in the event of a fall. Loss of balance occurs conditionally, with probability depending on the realized latent ES. After fitting the model by a form of quasi-maximum-likelihood, one may perform statistical inference to assess the effects of explanatory variables. An example is provided, using data from the NIH/NIA Baltimore Longitudinal Study on Aging.

NASA Discipline Neuroscience↗
NASA NTRS1975

Modern control concepts in hydrology

Two approaches to an identification problem in hydrology are presented, based upon concepts from modern control and estimation theory. The first approach treats the identification of unknown parameters in a hydrologic system subject to noisy inputs as an adaptive linear stochastic control problem; the second approach alters the model equation to account for the random part in the inputs, and then uses a nonlinear estimation scheme to estimate the unknown parameters. Both approaches use state-space concepts. The identification schemes are sequential and adaptive and can handle either time-invariant or time-dependent parameters. They are used to identify parameters in the Prasad model of rainfall-runoff. The results obtained are encouraging and confirm the results from two previous studies; the first using numerical integration of the model equation along with a trial-and-error procedure, and the second using a quasi-linearization technique. The proposed approaches offer a systematic way of analyzing the rainfall-runoff process when the input data are imbedded in noise.

Duong, N.↗
NASA NTRS2008

Changes in Head Stability Control in Response to a Lateral Perturbation while Walking in Older Adults

Falling is a main contributor of injury in older adults. The decline in sensory systems associated with aging limits information needed to successfully compensate for unexpected perturbations. Therefore, sensory changes result in older adults having problems maintaining balance stability when experiencing an unexpected lateral perturbation (e.g. slip) in the environment. The goal of this study was to determine head stability movement strategies used by older adults when experiencing an unexpected lateral perturbation during walking. A total of 16 healthy adults, aged 66-81 years, walked across a foam pathway 6 times. One piece of the foam pathway covered a movable platform that translated to the left when the subject stepped on the foam. Three trials were randomized in which the platform shifted. Angular rate sensors were placed on the center of mass for the head and trunk segments to collect head and trunk movement in all three planes of motion. The predominant movement strategies for maintaining head stability were determined from the results of the cross-correlation analyses between the head and trunk segments. The Chi square test of independence was used to evaluate the movement pattern distributions of head-trunk coordination during perturbed and non-perturbed walking. When perturbed, head stabilization was significantly challenged in the yaw and roll planes of motion. Subjects demonstrated a movement pattern of the head leading the trunk in an effort to stabilize the head. The older adult subjects used this head stabilization movement pattern to compensate for sensory changes when experiencing the unexpected lateral perturbation.

Buccello, Regina R.↗
NASA NTRS2007

Influence of Electrotactile Tongue Feedback on Controlling Upright Stance during Rotational and/or Translational Sway-referencing with Galvanic Vestibular Stimulation

Integration of multi-sensory inputs to detect tilts relative to gravity is critical for sensorimotor control of upright orientation. Displaying body orientation using electrotactile feedback to the tongue has been developed by Bach-y-Rita and colleagues as a sensory aid to maintain upright stance with impaired vestibular feedback. MacDougall et al. (2006) recently demonstrated that unpredictably varying Galvanic vestibular stimulation (GVS) significantly increased anterior-posterior (AP) sway during rotational sway referencing with eyes closed. The purpose of this study was to assess the influence of electrotactile feedback on postural control performance with pseudorandom binaural bipolar GVS. Postural equilibrium was measured with a computerized hydraulic platform in 10 healthy adults (6M, 4F, 24-65 y). Tactile feedback (TF) of pitch and roll body orientation was derived from a two-axis linear accelerometer mounted on a torso belt and displayed on a 144-point electrotactile array held against the anterior dorsal tongue (BrainPort, Wicab, Inc., Middleton, WI). Subjects were trained to use TF by voluntarily swaying to draw figures on their tongue, both with and without GVS. Subjects were required to keep the intraoral display in their mouths on all trials, including those that did not provide TF. Subjects performed 24 randomized trials (20 s duration with eyes closed) including four support surface conditions (fixed, rotational sway-referenced, translating the support surface proportional to AP sway, and combined rotational-translational sway-referencing), each repeated twice with and without GVS, and with combined GVS and TF. Postural performance was assessed using deviations from upright (peak-to-peak and RMS sway) and convergence toward stability limits (time and distance to base of support boundaries). Postural stability was impaired with GVS in all platform conditions, with larger decrements in performance during trials with rotation sway-referencing. Electrotactile feedback improved performance with GVS toward non-GVS levels, again with the greatest improvement during trials with rotation sway-referencing. These results demonstrate the effectiveness of tongue electrotactile feedback in providing sensory substitution to maintain postural stability with distorted vestibular input.

Wood, Scott J.↗
NASA NTRS2017

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper.

route advisories↗
NASA NTRS2017

Predicting the Operational Acceptability of Route Advisories

NASA envisions a future Air Traffic Management system that allows safe, efficient growth in global operations, enabled by increasing levels of automation and autonomy. In a safety-critical system, the introduction of increasing automation and autonomy has to be done in stages, making human-system integrated concepts critical in the foreseeable future. One example where this is relevant is for tools that generate more efficient flight routings or reroute advisories. If these routes are not operationally acceptable, they will be rejected by human operators, and the associated benefits will not be realized. Operational acceptance is therefore required to enable the increased efficiency and reduced workload benefits associated with these tools. In this paper, the authors develop a predictor of operational acceptability for reroute advisories. Such a capability has applications in tools that identify more efficient routings around weather and congestion and that better meet airline preferences. The capability is based on applying data mining techniques to flight plan amendment data reported by the Federal Aviation Administration and data on requested reroutes collected from a field trial of the NASA developed Dynamic Weather Routes tool, which advised efficient route changes to American Airlines dispatchers in 2014. 10-Fold cross validation was used for feature, model and parameter selection, while nested cross validation was used to validate the model. The model performed well in predicting controller acceptance or rejection of a route change as indicated by chosen performance metrics. Features identified as relevant to controller acceptance included the historical usage of the advised route, the location of the maneuver start point relative to the boundaries of the airspace sector containing the maneuver start (the maneuver start sector), the reroute deviation from the original flight plan, and the demand level in the maneuver start sector. A random forest with forty trees was the best performing of the five models evaluated in this paper.

operational acceptability↗
DOE OSTI2026

Virtual Growth of SRF Materials

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Fermilab]↗
DOE OSTI2026

Virtual Growth of SRF Materials: A Machine Learning Approach to Predict the Crystalline Structural Ordering in Nb Surface Oxides

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Unlisted, US, IL; Fermilab]↗
NASA NTRS2001

Uncertainty Optimization Applied to the Monte Carlo Analysis of Planetary Entry Trajectories

Recently, strong evidence of liquid water under the surface of Mars and a meteorite that might contain ancient microbes have renewed interest in Mars exploration. With this renewed interest, NASA plans to send spacecraft to Mars approx. every 26 months. These future spacecraft will return higher-resolution images, make precision landings, engage in longer-ranging surface maneuvers, and even return Martian soil and rock samples to Earth. Future robotic missions and any human missions to Mars will require precise entries to ensure safe landings near science objective and pre-employed assets. Potential sources of water and other interesting geographic features are often located near hazards, such as within craters or along canyon walls. In order for more accurate landings to be made, spacecraft entering the Martian atmosphere need to use lift to actively control the entry. This active guidance results in much smaller landing footprints. Planning for these missions will depend heavily on Monte Carlo analysis. Monte Carlo trajectory simulations have been used with a high degree of success in recent planetary exploration missions. These analyses ascertain the impact of off-nominal conditions during a flight and account for uncertainty. Uncertainties generally stem from limitations in manufacturing tolerances, measurement capabilities, analysis accuracies, and environmental unknowns. Thousands of off-nominal trajectories are simulated by randomly dispersing uncertainty variables and collecting statistics on forecast variables. The dependability of Monte Carlo forecasts, however, is limited by the accuracy and completeness of the assumed uncertainties. This is because Monte Carlo analysis is a forward driven problem; beginning with the input uncertainties and proceeding to the forecasts outputs. It lacks a mechanism to affect or alter the uncertainties based on the forecast results. If the results are unacceptable, the current practice is to use an iterative, trial-and-error approach to reconcile discrepancies. Therefore, an improvement to the Monte Carlo analysis is needed that will allow the problem to be worked in reverse. In this way, the largest allowable dispersions that achieve the required mission objectives can be determined quantitatively.

Olds, John↗