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NASA NTRS2018

The Interplay Between Radiation Pressure and the Photoelectric Instability in Optically Thin Disks of Gas and Dust

In optically thin disks, dust grains are photoelectrically stripped of electrons by starlight, heating nearby gas and possibly creating a dust clumping instability-the photoelectric instability (PeI)-that significantly alters global disk structure. In the current work, we use the Pencil Code to perform the first numerical models of the PeI that include stellar radiation pressure on dust grains in order to explore the parameter regime in which the instability operates. In some models with low gas and dust surface densities, we see a variety of dust structures, including sharp concentric rings. In the most gas- and dust-rich models, nonaxisymmetric clumps, arcs, and spiral arms emerge that represent dust surface density enhancements of factors of ∼5-20. In one high gas surface density model, we include a large, low-order gas viscosity and find that it observably smooths the structures that form in the gas and dust, suggesting that resolved images of a given disk may be useful for deriving constraints on the effective viscosity of its gas. Our models show that radiation pressure does not preclude the formation of complex structure from the PeI, but the qualitative manifestation of the PeI depends strongly on the parameters of the system. The PeI may provide an explanation for unusual disk morphologies, such as the moving blobs of the AU Mic disk, the asymmetric dust distribution of the 49Ceti disk, and the rings and arcs found in the HD 141569A disk.

photoelectric instability (PeI)↗

NASA NTRS2019

A new environment to simulate the dynamics in the close proximity of rubble-pile asteroids

This paper presents a new environment to simulate close-proximity dynamics around rubble-pile asteroids. The code provides methods for modeling the asteroid’s gravity field and surface through granular dynamics. It implements stateof-the-art techniques to model both gravity and contact interaction between particles: 1) mutual gravity as either direct N2 or Barnes-Hut GPU-parallel octree and 2) contact dynamics with a soft-body (force-based, smooth dynamics), hard-body (constraint-based, non-smooth dynamics), or hybrid (constraint-based with compliance and damping) approach. A very relevant feature of the code is its ability to handle complex-shaped rigid bodies and their full 6D motion. Examples of spacecraft close-proximity scenarios and their numerical simulations are shown.

Ferrari, Fabio↗

NASA NTRS1997

Incompatible Stochastic Processes and Complex Probabilities

The definition of conditional probabilities is based upon the existence of a joint probability. However, a reconstruction of the joint probability from given conditional probabilities imposes certain constraints upon the latter, so that if several conditional probabilities are chosen arbitrarily, the corresponding joint probability may not exist.

Probabilities Mathematics↗

NASA NTRS2010

Constraint and Flight Rule Management for Space Mission Operations

The exploration of space is one of the most fascinating domains to study from a human factors perspective. Like other complex work domains such as aviation (Pritchett and Kim, 2008), air traffic management (Durso and Manning, 2008), health care (Morrow, North, and Wickens, 2006), homeland security (Cooke and Winner, 2008), and vehicle control (Lee, 2006), space exploration is a large-scale sociotechnical work domain characterized by complexity, dynamism, uncertainty, and risk in real-time operational contexts (Perrow, 1999; Woods et al, 1994). Nearly the entire gamut of human factors issues - for example, human-automation interaction (Sheridan and Parasuraman, 2006), telerobotics, display and control design (Smith, Bennett, and Stone, 2006), usability, anthropometry (Chaffin, 2008), biomechanics (Marras and Radwin, 2006), safety engineering, emergency operations, maintenance human factors, situation awareness (Tenney and Pew, 2006), crew resource management (Salas et al., 2006), methods for cognitive work analysis (Bisantz and Roth, 2008) and the like -- are applicable to astronauts, mission control, operational medicine, Space Shuttle manufacturing and assembly operations, and space suit designers as they are in other work domains (e.g., Bloomberg, 2003; Bos et al, 2006; Brooks and Ince, 1992; Casler and Cook, 1999; Jones, 1994; McCurdy et al, 2006; Neerincx et aI., 2006; Olofinboba and Dorneich, 2005; Patterson, Watts-Perotti and Woods, 1999; Patterson and Woods, 2001; Seagull et ai, 2007; Sierhuis, Clancey and Sims, 2002). The human exploration of space also has unique challenges of particular interest to human factors research and practice. This chapter provides an overview of those issues and reports on some of the latest research results as well as the latest challenges still facing the field.

Barreiro, J.↗

NASA NTRS2024

EdgeCortix SAKURA-I Machine-Learning, PCIe Accelerator SEE Heavy Ion Test Report

To enable autonomy in space, machine-learning and computer vision applications become invaluable for sensor processing. However, these algorithms are computationally complex and unfeasible for many embedded central processing units (CPUs) and usually require external coprocessors, such as graphics processing units (GPUs) or accelerators specific to the application, including application specific integrated circuits (ASICs). In power-constrained systems, GPUs tend to consume more power than is acceptable (>40W), so lower-power accelerators have shown promise to provide the performance needed under spacecraft constraints. For radiation engineers, developing methodologies that can properly test CPUs, GPUs, and accelerators, and enable comparisons between them remains a necessary complication to solve as the devices become more complex. The methodology in this test aims to be a start in developing a baseline single-event effect (SEE) test for client-device machine learning accelerators. This category of devices do not host their own operating system. This testing campaign is a continuation of a previous 200 MeV proton test performed in January 2024. This report covers two heavy ion tests of the SAKURA-I card: one in April 2024, and one in June 2024. Additional data was needed after the April test due to ion-range issues experienced at higher linear-energy transfers (LETs). These range issues are described in more detail in Section 8. This experiment characterizes SEEs and data error susceptibility of the EdgeCortix SAKURA-I machine-learning accelerator under heavy ions. The device was monitored for single event upsets (SEUs) and single event functional interrupts (SEFIs) at the Lawrence Berkeley National Laboratory’s 88-inch cyclotron. The SAKURA-I board accelerates machine-learning inference applications on a host computer through a PCIex16 connection. For the purposes of devising an end to end automated analysis workflow for this experiment, the YOLO-V5 and SSD300 objection-detection models, and the ResNet-50, EfficientNet, and MobileNetV2 image classification models were used as a representative suite of analytical machine-learning models.

Seth S Roffe↗

DOE OSTI2025

Spatiotemporal development of expanding bacterial colonies driven by emergent mechanical constraints and nutrient gradients

Abstract Bacterial colonies growing on solid surfaces can exhibit robust expansion kinetics, with constant radial growth and saturating vertical expansion, suggesting a common developmental program. Here, we study this process forEscherichia colicells using a combination of modeling and experiments. We show that linear radial colony expansion is set by the verticalization of interior cells due to mechanical constraints rather than radial nutrient gradients as commonly assumed. In contrast, vertical expansion slows down from an initial linear regime even while radial expansion continues linearly. This vertical slowdown is due to limitation of cell growth caused by vertical nutrient gradients, exacerbated by concurrent oxygen depletion. Starvation in the colony interior results in a distinct death zone which sets in as vertical expansion slows down, with the death zone increasing in size along with the expanding colony. Thus, our study reveals complex heterogeneity within simple monoclonal bacterial colonies, especially along the vertical dimension. The intricate dynamics of such emergent behavior can be understood quantitatively from an interplay of mechanical constraints and nutrient gradients arising from obligatory metabolic processes.

Science & Technology - Other Topics↗

DOE OSTI2025

RLMolLM: Reinforcement Learning-Enhanced Language Model Framework for Inverse Molecular Design

Inverse molecular design faces significant challenges due to vast chemical space and complex property requirements. While language models show promise for molecular generation, they struggle with validity, multi-property optimization, and structural constraints. This work presents RLMolLM, a reinforcement learning framework combining Proximal Policy Optimization (PPO) with genetic algorithms to address these limitations. Our approach optimizes multiple user-specified properties including quantitative estimates of drug-likeness (QED), synthetic accessibility (SA), and ADMET (absorption, distribution, metabolism, excretion, and toxicity) endpoints without requiring complete model retraining, while maintaining capability for scaffold-constrained generation where specific substructures must be preserved. We outperform state-of-the-art methods for molecular optimization, achieving best QED scores across GDB13, Moses, and Zinc datasets with up to 31% improvement over previous methods while maintaining excellent validity, uniqueness, and novelty metrics. For simultaneous multi-property optimization, our framework achieves substantial improvements in ADMET properties including 4.5-fold reduction in hERG toxicity and enhanced Caco-2 permeability compared to Moses dataset. Under structural constraints, the framework significantly improves molecular validity while preserving scaffolds and effectively optimizing properties. In conclusion, this versatile solution advances pharmaceutical and materials molecular design through effective integration of reinforcement learning and genetic algorithms with multi-property optimization and scaffold preservation.

Genetic algorithms↗

DOE OSTI2026

Regularization via f -Divergence: An Application to Multi-Oxide Spectroscopic Analysis

In this paper, we explore the application of convolutional neural networks (CNNs) for predicting the chemical composition of complex geologic samples in a simulated Martian atmospheric environment. Specifically, we aim to characterize oxide weight percentages (wt.%) of rock samples analyzed by remote Laser-Induced Breakdown Spectroscopy (LIBS), framing the problem as a multi-target regression task . Neural networks trained on LIBS spectra are prone to overfitting due to high spectral complexity, limited labeled data, and measurement noise. While regularization is critical for improving generalization, common methods (e.g., ℓ 2 regularization) impose constraints not directly tied to data distribution properties. We propose a novel regularization method based on a specific ƒ-divergence induced by a graph-based estimator, designed to constrain the distributional discrepancy between predictions and targets. This regularizer serves a dual purpose: (a) mitigating overfitting by enforcing a constraint on the distributional difference between predictions and noisy targets, and (b) acting as an auxiliary loss that penalizes large divergences. To enable backpropagation, we develop a differentiable approximation of this particular ƒ-divergence, making the method feasible for neural networks. Experiments on ChemCam and SuperCam LIBS calibration spectra show that mathematical equation-divergence regularization outperforms or matches standard regularization methods (ℓ 1 , ℓ 2 , dropout) and the classical baseline, partial least squares (PLS). Combining ƒ-divergence regularization with standard regularization yields further performance gains, indicating that distributional regularization is useful in this context giving a promising direction for robust model training in planetary science applications. Source code is publicly available at Klein and Li (2025), https://doi.org/10.11578/dc.20250530.7.

58 GEOSCIENCES↗

DOE OSTI2025

Quantitative dissection of Agrobacterium T-DNA expression in single plant cells reveals density-dependent synergy and antagonism

Agrobacterium pathogenesis, which involves transferring T-DNA into plant cells, is the cornerstone of plant genetic engineering. As the applications that rely on Agrobacterium increase in sophistication, it becomes critical to achieve a quantitative and predictive understanding of T-DNA expression at the level of single plant cells. Here we examine if a classic Poisson model of interactions between pathogens and host cells holds true for Agrobacterium infecting Nicotiana benthamiana. Systematically challenging this model revealed antagonistic and synergistic density-dependent interactions between bacteria that do not require quorum sensing. Using various approaches, we studied the molecular basis of these interactions. To overcome the engineering constraints imposed by antagonism, we created a dual binary vector system termed ‘BiBi’, which can improve the efficiency of a reconstituted complex metabolic pathway in a predictive fashion. Our findings illustrate how combining theoretical models with quantitative experiments can reveal new principles of bacterial pathogenesis, impacting both fundamental and applied plant biology.

Alamos, Simon↗

DOE OSTI2026

A flexible and differentiable coil proxy for stellarator equilibrium optimization

Balancing plasma performance and coil cost is a significant challenge when designing a stellarator power plant. Most current stellarator designs are produced through two-stage optimization: stage-1 for the equilibrium and stage-2 for a coil design that reproduces its magnetic configuration. Because few proxies connect both stages, two-stage optimization can produce plasmas that have high-quality physical properties but overly complex coils. In recent years, single-stage optimization has increasingly been used to optimize the plasma and coils simultaneously in order to improve the plasma–coil balance. However, all existing single-stage tools are specialized for filament coils, cannot model coil systems containing permanent magnets or dipole arrays, and continue to be challenged by numerical problems. The quasi-single-stage optimization finds a middle ground by integrating a coil optimization subproblem into stage-1 optimization. We present a flexible, differentiable coil complexity proxy based on the newly developed QUADCOIL coil optimization code. QUADCOIL is fast and can target realistic coil metrics and constraints that are unavailable to codes with comparable speed. We demonstrate the effectiveness and flexibility of the QUADCOIL proxy by presenting two QSS optimization studies. The first study produces a permanent magnet solution for the MUSE stellarator with 34% fewer magnets than previous solutions. The second study produces a coil solution for the ARIES-CS stellarator with 30% reductions in both peak and root-mean-square force.

Fu, Lanke [Princeton Plasma Physics Laboratory (PP↗

NASA NTRS1989

Reflectance characteristics and surface processes in stabilized dune environments

Analysis of multitemporal TM data for three environmentally related field areas yields information on the response characteristics of stabilized dunes and desert-fringe environments. The three field sites studied include dune fields in Egypt, Mali, and Botswana, ranging in climate from hyperarid to semiarid, and may be classed as an environmental series relating surface processes under Saharan, Sahelian, and Savanna conditions. Sites were field mapped and monitored with TM data for lengths of time up to a year. The complexity of spectral response characteristics is greatest where vegetation is dense and diverse, but study of the three environments together places constraints on the importance of vegetation to spectral response as well as to mechanisms of sand transport. In both Mali and Botswana, the Sahelian and Savanna environments, contrast reversals occur on dune crests and reflectance patterns change through the dry season to resemble the response curves of the hyperarid study site in Egypt. In these analyses, overall surface brightness is controlled by sand composition, while spectral features are controlled by vegetation dynamics.

Jacobberger, P. A.↗

NASA NTRS1992

Optimal design of geodesically stiffened composite cylindrical shells

An optimization system based on general-purpose finite element code CSM Testbed and optimization program ADS is described. The system can be used to obtain minimum-mass designs of composite shell structures with complex stiffening arrangements. Ply thicknesses, ply orientations, and stiffener heights can be used as design variables. Buckling, displacement, and material failure constraints can be imposed on the design. The system is used to conduct a preliminary design study of geodesically stiffened shells. For comparison purposes, optimal designs of unstiffened shells, and ring and longitudinal stringer stiffened shells are also studied. Trends in the design of geodesically stiffened shells are identified. Features that enhance the capabilities and efficiency of the design system are described.

Gendron, G.↗

NASA NTRS2001

Temporal Constraint Reasoning With Preferences

A number of reasoning problems involving the manipulation of temporal information can naturally be viewed as implicitly inducing an ordering of potential local decisions involving time (specifically, associated with durations or orderings of events) on the basis of preferences. For example. a pair of events might be constrained to occur in a certain order, and, in addition. it might be preferable that the delay between them be as large, or as small, as possible. This paper explores problems in which a set of temporal constraints is specified, where each constraint is associated with preference criteria for making local decisions about the events involved in the constraint, and a reasoner must infer a complete solution to the problem such that, to the extent possible, these local preferences are met in the best way. A constraint framework for reasoning about time is generalized to allow for preferences over event distances and durations, and we study the complexity of solving problems in the resulting formalism. It is shown that while in general such problems are NP-hard, some restrictions on the shape of the preference functions, and on the structure of the preference set, can be enforced to achieve tractability. In these cases, a simple generalization of a single-source shortest path algorithm can be used to compute a globally preferred solution in polynomial time.

Khatib, Lina↗

NASA NTRS2011

System Oriented Runway Management: A Research Update

The runway configuration used by an airport has significant implications with respect to its capacity and ability to effectively manage surface and airborne traffic. Aircraft operators rely on runway configuration information because it can significantly affect an airline's operations and planning of their resources. Current practices in runway management are limited by a relatively short time horizon for reliable weather information and little assistance from automation. Wind velocity is the primary consideration when selecting a runway configuration; however when winds are below a defined threshold, discretion may be used to determine the configuration. Other considerations relevant to runway configuration selection include airport operator constraints, weather conditions (other than winds) traffic demand, user preferences, surface congestion, and navigational system outages. The future offers an increasingly complex landscape for the runway management process. Concepts and technologies that hold the potential for capacity and efficiency increases for both operations on the airport surface and in terminal and enroute airspace are currently under investigation. Complementary advances in runway management are required if capacity and efficiency increases in those areas are to be realized. The System Oriented Runway Management (SORM) concept has been developed to address this critical part of the traffic flow process. The SORM concept was developed to address all aspects of runway management for airports of varying sizes and to accommodate a myriad of traffic mixes. SORM, to date, addresses the single airport environment; however, the longer term vision is to incorporate capabilities for multiple airport (Metroplex) operations as well as to accommodate advances in capabilities resulting from ongoing research. This paper provides an update of research supporting the SORM concept including the following: a concept of overview, results of a TRCM simulation, single airport and Metroplex modeling effort and a benefits assessment.

Lohr, Gary W.↗

NASA NTRS2011

Adaptation of the Electra Radio to Support Multiple Receive Channels

Proposed future Mars missions plan communication between multiple assets (rovers). This paper presents the results of a study carried out to assess the potential adaptation of the Electra radio to a multi-channel transceiver. The basic concept is a Frequency Division multiplexing (FDM) communications scheme wherein different receiver architectures are examined. Options considered include: (1) multiple IF slices, A/D and FPGAs each programmed with an Electra baseband modem; (2) common IF but multiple A/Ds and FPGAs and (3) common IF, single A/D and single or multiple FPGAs programmed to accommodate the FDM signals. These options represent the usual tradeoff between analog and digital complexity. Given the space application, a common IF is preferable; however, multiple users present dynamic range challenges (e.g., near-far constraints) that would favor multiple IF slices (Option 1). Vice versa, with a common IF and multiple A/Ds (Option 2), individual AGC control of the A/Ds would be an important consideration. Option 3 would require a common AGC control strategy and would entail multiple digital down conversion paths within the FPGA. In this paper, both FDM parameters as well as the different Electra design options will be examined. In particular, signal channel spacing as a function of user data rates and transmit powers will be evaluated. In addition, tradeoffs between the different Electra design options will be presented with the ultimate goal of defining an augmented Electra radio architecture for potential future missions.

Time Division multiplexing↗

NASA NTRS2016

The Quality Control Algorithms Used in the Process of Creating the NASA Kennedy Space Center Lightning Protection System Towers Meteorological Database

The methodology and the results of the quality control (QC) process of the meteorological data from the Lightning Protection System (LPS) towers located at Kennedy Space Center (KSC) launch complex 39B (LC-39B) are documented in this paper. Meteorological data are used to design a launch vehicle, determine operational constraints, and to apply defined constraints on day-of-launch (DOL). In order to properly accomplish these tasks, a representative climatological database of meteorological records is needed because the database needs to represent the climate the vehicle will encounter. Numerous meteorological measurement towers exist at KSC; however, the engineering tasks need measurements at specific heights, some of which can only be provided by a few towers. Other than the LPS towers, Tower 313 is the only tower that provides observations up to 150 m. This tower is located approximately 3.5 km from LC-39B. In addition, data need to be QC'ed to remove erroneous reports that could pollute the results of an engineering analysis, mislead the development of operational constraints, or provide a false image of the atmosphere at the tower's location.

Orcutt, John M.↗

NASA NTRS2019

Improvements to the Copernicus Trajectory Design and Optimization System for Complex Space Trajectories

The purpose of this assessment was to develop updates and new features for the NASA Copernicus Spacecraft Trajectory Design and Optimization analysis tool (version 5.0) for application to NASA programs and projects. These updates will significantly improve the ability to design and optimize complex trajectories over multiple trajectory phases; will allow the use of unique vehicle-specific guidance, control, and trajectory strategies and constraints; and the creation of an almost unlimited number of unique user-defined capabilities. The primary stakeholders for this assessment are the trajectory design and optimization analysts and engineers, and the chief engineers and project managers for existing programs, projects, and/or tasks that involve impulsive, finite burn, and/or continuous thrust trajectories (e.g., Sun, planet, comet, asteroid, halo orbit, Lagrange point, and distant retrograde orbit). The breadth of application spans the preliminary engineering and mission design concepts and optimization, to the development of candidate reference missions and integrated mission design for vehicle system design and operation, to the design and development of flight trajectories and associated propulsive maneuvers for real-time operations.

Murri, Daniel G.↗

NASA NTRSDate not supplied

Verification and Validation of Safety-Critical Aircraft Systems Operating under Off-Nominal, Contingency, and Emergency Conditions

Verification and validation (V&V) of safety-critical technologies developed for loss of control (LOC) prevention and recovery and other aviation safety concerns pose significant challenges. Aircraft LOC can result from a wide spectrum of hazards, often occurring in combination, which cannot be fully replicated during evaluation. Technologies developed for LOC prevention and recovery must therefore be effective under a wide variety of hazardous and uncertain conditions, and the verification and validation of these technologies must provide some measure of assurance that the new vehicle safety technologies do no harm (i.e., that they themselves do not introduce new safety risks). V&V technologies must also enable the identification of system limitations and constraints, as well as enable the identification of safe and unsafe operating conditions (and their boundaries). Additionally, the V&V of complex, increasingly autonomous systems is a fundamental concern. Scalable, reproducible and cost-effective techniques for the assurance of safety critical systems during their design and operation is a key barrier to fielding new systems or updating current systems. Moreover, these techniques need to provide artifacts that enable a comprehensive evidence-based approach to certification. This briefing summarizes research performed under NASA’s Aviation Safety Program and follow-on research for the V&V of safety-critical aircraft system technologies developed for LOC prevention and recovery and increasingly autonomous systems, and for a broad assurance capability in both current and emerging aviation applications. Note that, in this briefing, the term “validation” refers to a confirmation that the system implementation (e.g., algorithms etc.) is performing the intended function(s), as well as an affirmation of effectiveness in these functions. “Verification” refers to a confirmation that the system implementation in the software and hardware meets its (hopefully validated) specifications (e.g., correctly executes algorithms as designed).

Validation↗