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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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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Crystallization of potassium-zeolites in organic-free media

A ubiquitous phenomenon in zeolite synthesis is the generation of polymorphs leading to either single or multi-phase products. The use of organic structure-directing agents (OSDAs) often ensures a high degree of phase purity for a desired zeolite; however, OSDAs can be economically and environmentally prohibitive. The use of alkali metals as inorganic structure-directing agents (ISDAs) is a common alternative, although reductions in polymorph specificity and/or purity in organic-free media are significant limitations. Developing more controlled, facile synthesis strategies without the aid of OSDAs relies on understanding how zeolite growth conditions impact polymorph selection and alter the physicochemical properties of crystalline products. Relatively few studies of organic-free syntheses have systematically explored potassium growth media. Here, in this study, we examine synthesis conditions that promote the formation of five K-zeolites: CHA, LTL, MER, EDI, and BPH frameworks. Time-resolved analyses reveal distinct trends in crystallization kinetics and interzeolite transformations for potassium compared to prior studies that have largely focused on Na-zeolites. We also highlight methods to achieve nanosized crystals and markedly reduce crystallization times for zeolites, such as chabazite, which are notoriously difficult to synthesize in organic-free media at reasonable timescales. Collectively, these findings identify routes to control K-zeolite polymorphism and provide general design strategies to tailor their crystallization.

36 MATERIALS SCIENCE↗
DOE OSTI2023

LISE$^{++}_{cute}$, the latest generation of the LISE ++ package, to simulate rare isotope production with fragment-separators

The LISE ++ software for fragment separator simulations has undergone a major update. The package, widely used at rare isotope beam facilities, can be used to predict intensities and purities of rare isotope beams and for planning and running of experiments using in-flight separators. It is especially useful for radioactive beam production as its results can be quickly compared to on-line data. The LISE ++ package has been ported to the Qt-framework in order to support modern compilers and computing methods. The benefits include 64-bit operation and LISE ++ availability on three different platforms: Windows, MacOS and Linux. In addition, the porting provides the ability to take advantage of future computational improvements. The updated package is named LISE$^{++}_{cute}$ to indicate a major step forward from the previous Borland-based versions. In addition to porting to the new platform, new main features and modifications have been added, mostly devoted to improving models and implementing other codes involved in rare isotope production at FRIB. Finally, a summary of modifications completed to improve the functionality of the code are discussed in this work, as well as future plans.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Highly active, ultra-low loading single-atom iron catalysts for catalytic transfer hydrogenation

Highly effective and selective noble metal-free catalysts attract significant attention. Here, a single-atom iron catalyst is fabricated by saturated adsorption of trace iron onto zeolitic imidazolate framework-8 (ZIF-8) followed by pyrolysis. Its performance toward catalytic transfer hydrogenation of furfural is comparable to state-of-the-art catalysts and up to four orders higher than other Fe catalysts. Isotopic labeling experiments demonstrate an intermolecular hydride transfer mechanism. First principles simulations, spectroscopic calculations and experiments, and kinetic correlations reveal that the synthesis creates pyrrolic Fe(II)-plN 3 as the active center whose flexibility manifested by being pulled out of the plane, enabled by defects, is crucial for collocating the reagents and allowing the chemistry to proceed. The catalyst catalyzes chemoselectively several substrates and possesses a unique trait whereby the chemistry is hindered for more acidic substrates than the hydrogen donors. This work paves the way toward noble-metal free single-atom catalysts for important chemical reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Development of alpha cluster structure in nuclei of the same mass number

The resonant 14 N+α particle scattering was studied in the 18 F excitation region from 6.5 to 9 MeV at Astana cyclotron using the TTIK approach. The excitation functions for the elastic 14 N+α scattering were analyzed in the framework of R-matrix approach. The observed strong alpha cluster structure in 18 F is compared with that in 18 O.

Nurmukhanbetova, Aliya↗
DOE OSTI2023

The importance of laser wavelength for driving inertial confinement fusion targets. I. Basic physics

We reinvestigate the role that laser wavelength plays in driving inertial confinement fusion (ICF) targets. Different assumptions underlie previous analytic frameworks that provide predictions for wavelength scaling of many important target parameters. These are explored and compared to radiation-hydrodynamics simulations of laser-driven targets. We are particularly interested here in lasers with wavelengths between 0.193 μm [wavelength of the Argon Flouride (ArF) excimer laser] and 0.527 μm (the frequency-doubled glass Nd:glass laser). Short-wavelength drivers have significant advantages for directly driven ICF targets, which are summarized here. We show that constraints such as providing a certain pressure or avoiding laser-plasma instability thresholds allow shorter laser wavelengths to provide energy savings, pressure enhancements, and/or higher hydrodynamic efficiencies. We also consider potential disadvantages, such as increased laser imprint or exposure to the Landau–Darrieus instability. These are shown to be either minor and/or can be easily remediated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

A fully coupled thermal–microstructural–mechanical finite element process model for directed energy deposition additive manufacturing of Ti–6Al–4V

A fully coupled thermal–microstructural–mechanical finite element modelling framework is developed to investigate the distortion and residual stresses during directed energy deposition (DED) of multi-phase Ti–6Al–4V alloy. The Johnson–Cook constitutive model is used to predict the yield strength of each phase as a function of strain, strain rate and temperature where the flow stress is calculated by a linear mixing rule based on the volumetric phase fractions. A thin-walled rectangular sample is chosen as the reference geometry and the results are compared with experimentally measured in situ thermal history and distortion data, where a reasonable agreement is achieved. The proposed modelling framework with physics-based material constitutive model provides useful information for a better understanding of process–microstructure–property relations in additive manufacturing by DED.

Tunay, Merve↗
DOE OSTI2023

Triaxiality and the nature of low-energy excitations in Ge 76

The deformation properties of the low-lying states in 76 Ge have been investigated following a safe energy Coulomb excitation measurement with the GRETINA tracking array and CHICO2 heavy-ion counter at the ATLAS accelerator facility at Argonne National Laboratory. A comprehensive set of transition and static E2 matrix elements were extracted from the measured differential Coulomb cross-sections, and compared with results of configuration interaction shell-model calculations and computations carried out within the framework of the generalized triaxial rotor model. The remarkable agreement between the calculated and experimental data supports a near-maximum triaxial deformation for the ground state of 76 Ge. Additionally, the degree of softness of the asymmetry in 76 Ge and 76 Se was investigated using rotational invariants generated from configuration interaction shell-model wave functions computed with the jj44b and JUN45 effective interactions. The resulting invariants are shown to be consistent with a stiff triaxial deformation in 76 Ge and a predominantly soft triaxial potential for 76 Se, in agreement with the conclusions of recent works by this collaboration.

59 ≤ A ≤ 89↗
DOE OSTI2024

ROSE: A reduced-order scattering emulator for optical models

A new generation of phenomenological optical potentials requires robust calibration and uncertainty quantification, motivating the use of Bayesian statistical methods. These Bayesian methods usually require calculating observables for thousands or even millions of parameter sets, making fast and accurate emulators highly desirable or even essential. Emulating scattering across different energies or with interactions such as optical potentials is challenging because of the nonaffine parameter dependence, meaning the parameters do not all factorize from individual operators. Here we introduce and demonstrate the reduced-order scattering emulator ( ROSE ) framework, a reduced basis emulator that can handle nonaffine problems. ROSE is fully extensible and works within the publicly available band framework software suite for calibration, model mixing, and experimental design. As a demonstration problem, we use ROSE to calibrate a realistic nucleon-target scattering model through the calculation of elastic cross sections. This problem shows the practical value of the ROSE framework for Bayesian uncertainty quantification with controlled trade-offs between emulator speed and accuracy as compared to high-fidelity solvers. Finally, planned extensions of ROSE are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

A Visual Designer of Layer‐wise Relevance Propagation Models

Abstract Layer‐wise Relevance Propagation (LRP) is an emerging and widely‐used method for interpreting the prediction results of convolutional neural networks (CNN). LRP developers often select and employ different relevance backpropagation rules and parameters, to compute relevance scores on input images. However, there exists no obvious solution to define a “best” LRP model. A satisfied model is highly reliant on pertinent images and designers' goals. We develop a visual model designer, named as VisLRPDesigner, to overcome the challenges in the design and use of LRP models. Various LRP rules are unified into an integrated framework with an intuitive workflow of parameter setup. VisLRPDesigner thus allows users to interactively configure and compare LRP models. It also facilitates relevance‐based visual analysis with two important functions: relevance‐based pixel flipping and neuron ablation. Several use cases illustrate the benefits of VisLRPDesigner. The usability and limitation of the visual designer is evaluated by LRP users.

Huang, Xinyi↗
DOE OSTI2025

Black-box optimization of CT acquisition and reconstruction parameters: a reinforcement learning approach

Protocol optimization is critical in Computed Tomography (CT) for achieving desired diagnostic image quality while minimizing radiation dose. Due to the inter-effect of influencing CT parameters, traditional optimization methods rely on the testing of exhaustive combinations of these parameters. This poses a notable limitation due to the impracticality of exhaustive parameter testing. This study introduces a novel methodology leveraging Virtual Imaging Trials (VITs) and reinforcement learning to more efficiently optimize CT protocols. Computational phantoms with liver lesions were imaged using a validated CT simulator and reconstructed with a novel CT reconstruction Toolkit. The optimization parameter space included tube voltage, tube current, reconstruction kernel, slice thickness, and pixel size. The optimization process was done using a Proximal Policy Optimization (PPO) agent which was trained to maximize the Detectability Index (d’) of the liver lesion for each reconstructed image. Results showed that our reinforcement learning approach found the absolute maximum d’ across the test cases while requiring 79.7% fewer steps compared to an exhaustive search, demonstrating both accuracy and computational efficiency, offering a efficient and robust framework for CT protocol optimization. The flexibility of the proposed technique allows for use of varying image quality metrics as the objective metric to maximize for. Our findings highlight the advantages of combining VIT and reinforcement learning for CT protocol management.

Fenwick, David [Duke University Medical Center]↗
DOE OSTI2022

Observed Covariations in Boundary Layer and Cumulus Cloud Layer Processes

In this paper we examine variations in boundary-layer processes spanning the shallow to deep cumulus transition. This is accomplished by differentiating boundary layer properties on the basis of convective outcomes, ranging from shallow to deep, as observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma, USA. Doppler lidar, radar, and radiosonde data are combined to determine statistical differences in boundary layer and cloud layer properties using a large sample (236) of days with a range of convective outcomes: shallow, congestus, and deep convection. In these analyses, the radar characterizes diurnal cloud depth, the lidar quantifies updraft and downdraft properties in the subcloud layer, and daily radiosonde data provides the convective inhibition (CIN). Combined, these data are used to test the hypothesis that deep convection occurs when the strength of the boundary layer turbulence (i.e., TKE) exceeds the strength of the energy barrier (i.e., CIN) at the top of the CBL. Results show that days with deep convective clouds have significantly lower vertical velocity variance and weaker updrafts within the subcloud layer. However, CIN values are also found to be significantly lower on deep convective days, allowing for these weaker updrafts to penetrate the energy barrier and reach the level of free convection (LFC). In contrast, shallow convective outcomes occur when the updrafts are strong in an absolute sense, but are weak when compared to the strength of the energy barrier. These findings support the use of the CIN/TKE framework in parameterizing convection in coarse resolution models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Beam Non-Uniformity Characterization at the SpinQuest and DarkQuest Experiments

The SpinQuest experiment, including upgrades to SpinQuest designed to increase sensitivity to dark sector searches (commonly known as DarkQuest), utilizes the high-intensity 120 GeV proton beam delivered by the Fermilab Accelerator Complex to probe the inner structure of nucleons and search for new physics beyond the Standard Model. The SpinQuest beam is extracted from the Main Injector synchrotron at Fermilab in what is known as a slow spill . The slow spill involves a complex non-linear half-integer extraction method, which results in non-uniform beam behavior. SpinQuest observes spikes of very high intensity beam which can saturate detectors and reduce trigger efficiency, significantly impacting the experiment's sensitivity. In this project we address this challenge by developing an analysis framework to characterize the beam delivered to SpinQuest. By discovering trends within each spill and by comparing thousands of spills, we can better inform the Accelerator Division and improve the slow spill extraction. We have also begun a collaboration with the Accelerator Division in order to simulate the slow spill and improve the magnet ramp process controls which will improve the uniformity of the beam. These improvements will directly enhance the physics reach of SpinQuest/DarkQuest, increasing their sensitivity to key measurements such as the Sivers function and searches for new physics.

Dolen, James William [Purdue U., Calumet] (ORCID:0↗
DOE OSTI2025

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Volumetrics of Hydrogen Storage by Physical Adsorption

Physical adsorption remains a promising method for achieving fast, reversible hydrogen storage at both ambient and cryogenic conditions. Research in this area has recently shifted to focus primarily on the volumetric (H 2 stored/delivered per volume) gains achieved within an adsorptive storage system over that of pure H 2 compression; however, the methodology for estimating a volumetric stored or delivered amount requires several assumptions related to the ultimate packing of the adsorbent material into an actual storage system volume. In this work, we critically review the different assumptions commonly employed, and thereby categorize and compare the volumetric storage and delivery across numerous different porous materials including benchmark metal-organic frameworks, porous carbons, and zeolites. In several cases, there is a significant gain in both storage and delivery by the addition of an adsorbent to the high-pressure H 2 storage system over that of pure compression, even at room temperature. Lightweight, low-density materials remain the optimal adsorbents at low temperature, while higher density, open metal-containing frameworks are necessary for high-density room temperature storage and delivery.

08 HYDROGEN↗
NASA NTRS1990

A review of nonlinear constitutive models for metals

Over the past two decades a number of thermomechanical constitutive theories have been proposed for viscoplastic metals. These models are in most cases similar in that they utilize a set of internal state variables which provide locally averaged representations of microphysical phenomena such as dislocation rearrangement and grain boundary sliding. The state of development of several of these models is now at the point where accurate theoretical solutions can be obtained for a wide variety of structural problems at elevated temperatures. The fundamentals of viscoplasticity are briefly reviewed and a general framework is outlined. Several of the more prominent models are reviewed, and predictions from models are compared to experimental results.

Allen, David H.↗
NASA NTRS2004

Selection of a Data Acquisition and Controls System Communications and Software Architecture for Johnson Space Center's Space Environment Simulation Laboratory Thermal and Vacuum Test Facilities

Upgrade of data acquisition and controls systems software at Johnson Space Center's Space Environment Simulation Laboratory (SESL) involved the definition, evaluation and selection of a system communication architecture and software components. A brief discussion of the background of the SESL and its data acquisition and controls systems provides a context for discussion of the requirements for each selection. Further framework is provided as upgrades to these systems accomplished in the 1990s and in 2003 are compared to demonstrate the role that technological advances have had in their improvement. Both of the selections were similar in their three phases; 1) definition of requirements, 2) identification of candidate products and their evaluation and testing and 3) selection by comparison of requirement fulfillment. The candidates for the communication architecture selection embraced several different methodologies which are explained and contrasted. Requirements for this selection are presented and the selection process is described. Several candidates for the software component of the data acquisition and controls system are identified, requirements for evaluation and selection are presented, and the evaluation process is described.

Jordan, Eric A.↗
DOE OSTI2021

A Decision Support Framework for Grid-Aware Electric Bus Charge Scheduling

While there are many advantages to electric public transit vehicles, they also pose new challenges for fleet operators. One key challenge is defining a charge scheduling policy that minimizes operating costs and power grid disruptions while maintaining schedule adherence. An uncoordinated policy could result in some buses running out of charge before completing their trip, while a grid agnostic policy might incur higher energy costs or cause an adverse impact on the grid’s distribution system. We present a grid aware decision-theoretic framework for electric bus charge scheduling that accounts for energy price, grid load, and bus status. The framework connects environmental models for traffic (SUMO) and the electric grid (GridLAB-D) to a planner, which evaluates bus charging decisions with regard to their long-term effect on grid reliability and cost. The framework has been evaluated on a simulation of Richland, WA’s bus and grid network, and compared to greedy methods.

EV, machine leaning, EV-Grid, Transportation, Grid↗
DOE OSTI2021

A Visual Designer of Layer-wise Relevance Propagation Models

Layer-wise Relevance Propagation (LRP) is an emerging and widely-used method for interpreting the prediction results of convolutional neural networks (CNN). LRP developers often select and employ different relevance backpropagation rules and parameters, to compute relevance scores on input images. However, there exists no obvious solution to define a "best" LRP model. A satisfied model is highly reliant on pertinent images and designers' goals. We develop a visual model designer, named as VisLRPDesigner, to overcome the challenges in the design and use of LRP models. Various LRP rules are unified into an integrated framework with an intuitive workflow of parameter setup. VisLRPDesigner thus allows users to interactively configure and compare LRP models. It also facilitates relevance-based visual analysis with two important functions: relevance-based pixel flipping and neuron ablation. Several use cases illustrate the benefits of VisLRPDesigner. The usability and limitation of the visual designer is evaluated by LRP users.

97 MATHEMATICS AND COMPUTING↗