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All sources NASA NTRS DOE OSTI

DOE OSTI2023

Search for High-Pressure Silicon Phases: Reaching the Extreme Conditions with High-Intensity Laser Irradiation

Controlling electronic and optical properties of semiconducting materials could substantially expand their functionality and enable new pathways for the formation of ‘smart’ materials for emerging innovative applications. An emerging new path for the synthesis of exotic silicon (Si) polymorphs is irradiation of bulk diamond-cubic Si by ultrashort laser pulses at relativistic intensity above 1019 W/cm2. Exotic polymorphs are formed due to interaction with MeV-energy electrons generated in laser-produced high-temperature plasma state. The unusual Si structures are found in the form of 5–10 nm nanoparticles confined deep in the bulk of 500-μm-thick Si samples. Raman spectroscopy, electron microscopy and X-ray diffraction studies provide an unequivocal evidence of exotic Si phase formation. A key advantage of such relativistic irradiation lies thereby in the fact that large quantities of such exotic Si is synthesised embedded within the bulk diamond-cubic Si and that further the formed Si polymorphs are stable at ambient temperature and pressure. They are thus available for further studies for electronic applications in selective band gap engineering.

Rapp, Ludovic↗

NASA NTRS2015

NASA Propulsion Sub-System Concept Studies and Risk Reduction Activities for Resource Prospector Lander

NASA's exploration roadmap is focused on developing technologies and performing precursor missions to advance the state of the art for eventual human missions to Mars. One of the key components of this roadmap is various robotic missions to Near-Earth Objects, the Moon, and Mars to fill in some of the strategic knowledge gaps. The Resource Prospector (RP) project is one of these robotic precursor activities in the roadmap. RP is a multi-center and multi-institution project to investigate the polar regions of the Moon in search of volatiles. The mission is rated Class D and is approximately 10 days, assuming a five day direct Earth to Moon transfer. Because of the mission cost constraint, a trade study of the propulsion concepts was conducted with a focus on available low-cost hardware for reducing cost in development, while technical risk, system mass, and technology advancement requirements were also taken into consideration. The propulsion system for the lander is composed of a braking stage providing a high thrust to match the lander's velocity with the lunar surface and a lander stage performing the final lunar descent. For the braking stage, liquid oxygen (LOX) and liquid methane (LCH4) propulsion systems, derived from the Morpheus experimental lander, and storable bi-propellant systems, including the 4th stage Peacekeeper (PK) propulsion components and Space Shuttle orbital maneuvering engine (OME), and a solid motor were considered for the study. For the lander stage, the trade study included miniaturized Divert Attitude Control System (DACS) thrusters (Missile Defense Agency (MDA) heritage), their enhanced thruster versions, ISE-100 and ISE-5, and commercial-off-the-shelf (COTS) hardware. The lowest cost configuration of using the solid motor and the PK components while meeting the requirements was selected. The reference concept of the lander is shown in Figure 1. In the current reference configuration, the solid stage is the primary provider of delta-V. It will generate 15,000-lbf of thrust with a single burn of ~ 80's seconds. The lander stage is a bi-propellant, pressure-regulated, pulsing liquid propulsion system to perform all other functions.

Trinh, Huu P.↗

DOE OSTI2025

Liquid Metals for Advanced Batteries: Recent Progress and Future Perspective

ABSTRACT The shift toward sustainable energy has increased the demand for efficient energy storage systems to complement renewable sources like solar and wind. While lithium‐ion batteries dominate the market, challenges such as safety concerns and limited energy density drive the search for new solutions. Liquid metals (LMs) have emerged as promising materials for advanced batteries due to their unique properties, including low melting points, high electrical conductivity, tunable surface tension, and strong alloying tendency. Enabled by the unique properties of LMs, four key scientific functions of LMs in batteries are highlighted: active materials, self‐healing, interface stabilization, and conductivity enhancement. These applications can improve battery performance, safety, and lifespan. This review also discusses current challenges and future opportunities for using LMs in next‐generation energy storage systems. image

Zheng, Tianrui [Materials Science and Engineering ↗

DOE OSTI2025

Workforce planning: a review of methodologies

Workforce planning deals with determining the number of employees and associated skills necessary to meet the future operational needs of an organization. A workforce system consists of six elements: recruitment, attrition, promotion, training, retention, and scheduling. Historically, several workforce modeling and analysis methodologies have been developed to capture these elements. This paper reviews the results of workforce and manpower models published within peer-reviewed literature between 1959 and 2021 to provide an in-depth analysis of current models. The focus of this review is on analytical, simulation, and empirical models found in literature that were collected based on a citation requirement and keyword search criteria. Results demonstrate the trends in workforce modeling research and discuss the common uses of each model type and the advantages/disadvantages related to each model. Based on the common attributes of workforce systems, the discussion focuses on the most frequently used model type for each element and the best use for each model. Lastly, recommendations are made for the development of workforce models that allow the most comprehensive view of the workforce systems of the future.

42 ENGINEERING↗

NASA NTRS2016

Agile: From Software to Mission System

The Resource Prospector (RP) is an in-situ resource utilization (ISRU) technology demonstration mission, designed to search for volatiles at the Lunar South Pole. This is NASA's first near real time tele-operated rover on the Moon. The primary objective is to search for volatiles at one of the Lunar Poles. The combination of short mission duration, a solar powered rover, and the requirement to explore shadowed regions makes for an operationally challenging mission. To maximize efficiency and flexibility in Mission System design and thus to improve the performance and reliability of the resulting Mission System, we are tailoring Agile principles that we have used effectively in ground data system software development and applying those principles to the design of elements of the mission operations system.

software engineering↗

NASA NTRS2004

Lab-On-a-Chip Application Development (LOCAD): Bridging Technology Readiness for Exploration

At Marshall Space Flight Center we have established a capability to investigate the use of microfluidics for space flight. The Lab-On-a-Chip Application Development (LOCAD) team has created a program for advancing Technology Readiness Levels (TRL) of 1 and 2 to TRL 6 and 7, quickly and economically for Lab-On-a-Chip (LOC) applications. Scientists and engineers can utilize LOCAD'S process to efficiently learn about microfluidics and determine if microfluidics is applicable to their needs. Once the applicability has been determined, LOCAD can then perform tests to develop the new fluidic protocols which are different from macro-scale chemical reaction protocols. With this information new micro-fluidic devices can be created and tested. Currently, LOCAD is focused on using microfluidics for both Environmental Monitoring & Control, and Medical Systems. Eventually, handheld portable units utilizing LOC technology will perform rapid tests to determine water quality, and microbial contamination levels. Since LOC technology is drastically reduced in physical size, it thereby reduces power, weight, volume, and sample requirements, a big advantage considering the resource constraints associated with spaceflight. Another one of LOCAD's current activities is the development of a microfluidic system to aid in the search for life on Mars.

Spearing, Scott F.↗

DOE OSTI2020

A non-cooperative meta-modeling game for automated third-party calibrating, validating and falsifying constitutive laws with parallelized adversarial attacks

The evaluation of constitutive models, especially for high-risk and high-regret engineering applications, requires efficient and rigorous third-party calibration, validation and falsification. While there are numerous efforts to develop paradigms and standard procedures to validate models, difficulties may arise due to the sequential, manual, and often biased nature of the commonly adopted calibration and validation processes, thus slowing down data collections, hampering the progress towards discovering new physics, increasing expenses and possibly leading to misinterpretations of the credibility and application ranges of proposed models. This work attempts to introduce concepts from game theory and machine learning techniques to overcome many of these existing difficulties. Here, we introduce an automated meta-modeling game where two competing AI agents systematically generate experimental data to calibrate a given constitutive model and to explore its weakness such that the experiment design and model robustness can be improved through competitions. The two agents automatically search for the Nash equilibrium of the meta-modeling game in an adversarial reinforcement learning framework without human intervention. In particular, a protagonist agent seeks to find the more effective ways to generate data for model calibrations, while an adversary agent tries to find the most devastating test scenarios that expose the weaknesses of the constitutive model calibrated by the protagonist. By capturing all possible design options of the laboratory experiments into a single decision tree, we recast the design of experiments as a game of combinatorial moves that can be resolved through deep reinforcement learning by the two competing players. Our adversarial framework emulates idealized scientific collaborations and competitions among researchers to achieve a better understanding of the application range of the learned material laws and prevent misinterpretations caused by conventional AI-based third-party validation. Numerical examples are given to demonstrate the wide applicability of the proposed meta-modeling game with adversarial attacks on both human-crafted constitutive models and machine learning models.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Bayesian Optimized Deep Ensemble for Uncertainty Quantification of Deep Neural Networks: a System Safety Case Study on Sodium Fast Reactor Thermal Stratification Modeling

Deep neural networks (DNNs) are increasingly important to scientific computing and engineering system simulations. Accurate uncertainty quantification (UQ) for DNNs is critical in safety-sensitive engineering domains. Traditional Deep Ensemble (DE) methods, while easy to implement, frequently suffer from poorly calibrated uncertainty estimates and limited predictive accuracy due to reliance on fixed architectures with varied weight initializations. To address these issues, we introduce a workflow that combines Bayesian Optimization (BO) and DE. The workflow is modular, scalable, and integrates parallel BO initialized with Sobol sequences to individually optimize the hyperparameters of each ensemble member. This method enhances ensemble diversity, improves predictive accuracy, and provides reliable uncertainty estimates. We evaluate the proposed BODE approach in a sodium fast reactor thermal stratification modeling case study, where we used a densely connected convolutional neural network to predict turbulent viscosity during the reactor transient with consideration of data noise. We benchmark its performance against several optimization approaches, including baseline deep ensemble, evolutionary algorithm-optimized ensemble, ensemble formed via random search combined with greedy selection, and a BO ensemble using random initialization. Here, our results demonstrate superior performance of the developed BODE approach. In noise-free scenarios, BODE notably reduces incorrect aleatoric uncertainty and significantly enhances predictive accuracy. Under conditions of 5% and 10% Gaussian noise, BODE adaptively quantifies uncertainty proportional to data noise, achieving up to an 80% reduction in root mean square error compared to baseline methods and producing well-calibrated prediction intervals.

Bayesian optimization↗

DOE OSTI2023

High temperature inelastic constitutive models for the ASME Section III, Division 5 Class A materials

This report describes the exploration of a universal high temperature inelastic constitutive model for use with the ASME Boiler & Pressure Vessel Code Section III, Division 5, Class A design rules. The idea, developed based on feedback from reactor vendors, is to simplify the current bespoke material models for Grade 91, 316H, and Alloy 617 and the new model for Alloy 800H into a simple, single model form. The report describes a new parallel time integration technique implemented in the pyoptmat package which allowed us to explore a wide variety of model forms, searching for a suitable common model. The report then describes preliminary work on models for monontonic deformation and then the development of a set of models suitable for capturing high temperature cyclic deformation. These models are suitable for use with the ASME design rules, except potentially for a narrow, material-specific band of temperatures at the edge of the creep regime. An incremental improvement the current models could overcome this discrepancy and provide a new, simpler set of constitutive model for all four materials.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Refinement and Modeling of a Blackbody-Based Calibration Method in the InfraBREAD Detector

The Broadband Reflector Experiment for Axion Detection (BREAD) is an ongoing experiment searching for the conversion of yet undiscovered axion-like dark matter particles to photons in the presence of a magnetic field. InfraBREAD, a sub-experiment of BREAD, uses a superconducting nanowire single photon detector (SNSPD), a high-efficiency and low-noise device, to specifically detect infrared-range photons produced by $\mathcal{O}$(eV) axion-like particles. The unique BREAD reflector setup allows for the focusing of all converted signal photons to a 1mm $\times$ 1mm SNSPD. However, when the detector is cooled to cryogenic temperatures during operation, uneven thermal contraction of reflector components may lead to a small shift in the location of the focal spot. A novel calibration method using blackbody radiation is proposed to locate the true focal spot of the detector \textit{in situ}. Through ray tracing simulations done in FRED Optical Engineering Software, this method is demonstrated to locate the focus to within 50 $\mu$m in three dimensions.

Rao, Shardul↗

DOE OSTI2024

Modeling and Proof-of-Concept of a Blackbody-Based Calibration Method in the InfraBREAD Detector

The Broadband Reflector Experiment for Axion Detection (BREAD) is an ongoing collaboration searching for the conversion of yet undiscovered axion-like dark matter particles to photons in the presence of a magnetic field. InfraBREAD, a pilot experiment realization of BREAD, uses a superconducting nanowire single photon detector (SNSPD), a high-efficiency and low-noise device, to specifically detect infrared-range photons produced by $\mathcal{O}$(eV) axion-like particles. The unique BREAD coaxial reflector setup allows for the focusing of converted signal photons to a 1mm $\times$ 1mm SNSPD. However, when the detector is cooled to cryogenic temperatures during operation, uneven thermal contraction of reflector components may lead to a small shift in the location of the focal spot. A novel calibration method using blackbody radiation is proposed to locate the true focal spot of the detector \textit{in situ}. Through ray tracing simulations done in FRED Optical Engineering Software, this method is demonstrated to locate the focus to within $\SI{50}{\micro\metre}$ in the axial dimension. Additionally, it is demonstrated that the blackbody photon source used in this calibration must be at a temperature of at least $\SI{15}{\kelvin}$ to $\SI{40}{\kelvin}$, depending on the sensitivity of the SNSPD.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Targeted materials discovery using Bayesian algorithm execution

Rapid discovery and synthesis of future materials requires intelligent data acquisition strategies to navigate large design spaces. A popular strategy is Bayesian optimization, which aims to find candidates that maximize material properties; however, materials design often requires finding specific subsets of the design space which meet more complex or specialized goals. We present a framework that captures experimental goals through straightforward user-defined filtering algorithms. These algorithms are automatically translated into one of three intelligent, parameter-free, sequential data collection strategies (SwitchBAX, InfoBAX, and MeanBAX), bypassing the time-consuming and difficult process of task-specific acquisition function design. Our framework is tailored for typical discrete search spaces involving multiple measured physical properties and short time-horizon decision making. We demonstrate this approach on datasets for TiO 2 nanoparticle synthesis and magnetic materials characterization, and show that our methods are significantly more efficient than state-of-the-art approaches. Overall, our framework provides a practical solution for navigating the complexities of materials design, and helps lay groundwork for the accelerated development of advanced materials.

42 ENGINEERING↗

NASA NTRS2000

A Parallel Genetic Algorithm for Automated Electronic Circuit Design

Parallelized versions of genetic algorithms (GAs) are popular primarily for three reasons: the GA is an inherently parallel algorithm, typical GA applications are very compute intensive, and powerful computing platforms, especially Beowulf-style computing clusters, are becoming more affordable and easier to implement. In addition, the low communication bandwidth required allows the use of inexpensive networking hardware such as standard office ethernet. In this paper we describe a parallel GA and its use in automated high-level circuit design. Genetic algorithms are a type of trial-and-error search technique that are guided by principles of Darwinian evolution. Just as the genetic material of two living organisms can intermix to produce offspring that are better adapted to their environment, GAs expose genetic material, frequently strings of 1s and Os, to the forces of artificial evolution: selection, mutation, recombination, etc. GAs start with a pool of randomly-generated candidate solutions which are then tested and scored with respect to their utility. Solutions are then bred by probabilistically selecting high quality parents and recombining their genetic representations to produce offspring solutions. Offspring are typically subjected to a small amount of random mutation. After a pool of offspring is produced, this process iterates until a satisfactory solution is found or an iteration limit is reached. Genetic algorithms have been applied to a wide variety of problems in many fields, including chemistry, biology, and many engineering disciplines. There are many styles of parallelism used in implementing parallel GAs. One such method is called the master-slave or processor farm approach. In this technique, slave nodes are used solely to compute fitness evaluations (the most time consuming part). The master processor collects fitness scores from the nodes and performs the genetic operators (selection, reproduction, variation, etc.). Because of dependency issues in the GA, it is possible to have idle processors. However, as long as the load at each processing node is similar, the processors are kept busy nearly all of the time. In applying GAs to circuit design, a suitable genetic representation 'is that of a circuit-construction program. We discuss one such circuit-construction programming language and show how evolution can generate useful analog circuit designs. This language has the desirable property that virtually all sets of combinations of primitives result in valid circuit graphs. Our system allows circuit size (number of devices), circuit topology, and device values to be evolved. Using a parallel genetic algorithm and circuit simulation software, we present experimental results as applied to three analog filter and two amplifier design tasks. For example, a figure shows an 85 dB amplifier design evolved by our system, and another figure shows the performance of that circuit (gain and frequency response). In all tasks, our system is able to generate circuits that achieve the target specifications.

Long, Jason D.↗

NASA NTRS1988

Issues and opportunities in space photovoltaics

Space power sources are becoming a central focus for determining man's potential and schedule for exploring and utilizing the benefits of space. The ability to search, probe, survey, and communicate throughout the universe will depend on providing adequate power to the instruments to do these jobs. Power requirements for space platforms are increasing and will continue to increase into the 21st century. Photovoltaics have been a dependable power source for space for the last 30 years and have served as the primary source of power on virtually all DOD and NASA satellites. The performance of silicon (Si) solar cells has increased from 10 percent air mass zero (AM0) solar energy conversion efficiency in the early 60's to almost 15 percent on today's spacecraft. Some technologists even think that the potential for solar photovoltaics has reached a plateau. However, present and near-future Air Force and NASA requirements show needs that, if the problems are looked upon as opportunities, can elevate the photovoltaic power source scientist and array structure engineer into the next technological photovoltaic growth curve.

Francis, Robert W.↗

NASA NTRS1988

Issues and opportunities in space photovoltaics

Francis, Robert W.↗

DOE OSTI2024

An open-source framework for balancing computational speed and fidelity in production cost models

Studies of bulk power system operations need to incorporate uncertainty and sensitivity analyses, especially around exposure to weather and climate variability and extremes, but this remains a computational modeling challenge. Commercial production cost models (PCMs) have shorter runtimes, but also important limitations (opacity, license restrictions) that do not fully support stochastic simulation. Open-source PCMs represent a potential solution. They allow for multiple, simultaneous runs in high-performance computing environments and offer flexibility in model parameterization. Yet, developers must balance computational speed (i.e. runtime) with model fidelity (i.e. accuracy). In this paper, we present Grid Operations (GO), a framework for instantiating open-source, scale-adaptive PCMs. GO allows users to search across parameter spaces to identify model versions that appropriately balance computational speed and fidelity based on experimental needs and resource limits. Results provide generalizable insights on how to navigate the fidelity and computational speed tradeoff through parameter selection. We show that models with coarser network topologies can accurately mimic market operations, sometimes better than higher-resolution models. It is thus possible to conduct large simulation experiments that characterize operational risks related to climate and weather extremes while maintaining sufficient model accuracy.

42 ENGINEERING↗

NASA NTRS1989

A Boltzmann machine for the organization of intelligent machines

In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved to converge to the minimum of a cost function. Finally, simulations will show the effectiveness of a variety of search techniques for the intelligent machine.

Moed, Michael C.↗

NASA NTRS2004

Systems engingeering for the Kepler Mission : a search for terrestrial planets

The Kepler mission will launch in 2007 and determine the distribution of earth-size planets (0.5 to 10 earth masses) in the habitable zones (HZs) of solar-like stars. The mission will monitor > 100,000 dwarf stars simultaneously for at least 4 years. Precision differential photometry will be used to detect the periodic signals of transiting planets. Kepler will also support asteroseismology by measuring the pressure-mode (p-mode) oscillations of selected stars. Key mission elements include a spacecraft bus and 0.95 meter, wide-field, CCD-based photometer injected into an earth-trailing heliocentric orbit by a 3-stage Delta II launch vehicle as well as a distributed Ground Segment and Follow-up Observing Program. The project is currently preparing for Preliminary Design Review (October 2004) and is proceeding with detailed design and procurement of long-lead components. In order to meet the unprecedented photometric precision requirement and to ensure a statistically significant result, the Kepler mission involves technical challenges in the areas of photometric noise and systematic error reduction, stability, and false-positive rejection. Programmatic and logistical challenges include the collaborative design, modeling, integration, test, and operation of a geographically and functionally distributed project. A very rigorous systems engineering program has evolved to address these challenges. This paper provides an overview of the Kepler systems engineering program, including some examples of our processes and techniques in areas such as requirements synthesis, validation & verification, system robustness design, and end-to-end performance modeling.

systems engineering↗