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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Technology Directions for the 21st Century, volume 1

For several decades, semiconductor device density and performance have been doubling about every 18 months (Moore's Law). With present photolithography techniques, this rate can continue for only about another 10 years. Continued improvement will need to rely on newer technologies. Transition from the current micron range for transistor size to the nanometer range will permit Moore's Law to operate well beyond 10 years. The technologies that will enable this extension include: single-electron transistors; quantum well devices; spin transistors; and nanotechnology and molecular engineering. Continuation of Moore's Law will rely on huge capital investments for manufacture as well as on new technologies. Much will depend on the fortunes of Intel, the premier chip manufacturer, which, in turn, depend on the development of mass-market applications and volume sales for chips of higher and higher density. The technology drivers are seen by different forecasters to include video/multimedia applications, digital signal processing, and business automation. Moore's Law will affect NASA in the areas of communications and space technology by reducing size and power requirements for data processing and data fusion functions to be performed onboard spacecraft. In addition, NASA will have the opportunity to be a pioneering contributor to nanotechnology research without incurring huge expenses.

Crimi, Giles F.↗
NASA NTRS2018

Mars Planetary Network for Human Exploration Era – Potential Challenges and Solutions

During 2016-2017, a study was conducted under the sponsorship of the NASA’s Space Communications and Navigation (SCaN) Program to investigate the deep space communications capacity taking into account the needs of all the present and envisioned future missions toward 2030s. It was soon recognized that planning for human exploration to Mars would impose certain unprecedent challenges, both fiscal and technical, to the current space communications paradigm. Targeting the assumed missions concepts, i.e., Crewed Mission to Phobos (CMTP) and Mars Short Stay Mission (MSSM), a Mars Planetary Network for the human exploration era has been formulated. The activity modeling and network traffic simulation/modeling we performed gave some insight into the technical challenges in space communications for the envisioned human Mars exploration era. Chief among the potential challenges are: (1) the high demand on the deep space network (DSN) assets for achieving the high-rate links, both return and forward, from Mars farthest/farther distance (up to 2.67 AU); (2) the need for resilient, persistent communication coverage for crewed vehicles, on surface and in orbits; (3) the significant period of outage for the Mars-Earth link due to superior solar conjunction; (4) the need for on-demand, simultaneous access to the proximity link by multiple vehicles and astronauts in the exploration zone; (5) the capability of determining precise, real-time, positions of surface vehicles and astronauts by the deep space habitat and/or other tele-operations entities. Solution space to each of the above challenges has been explored and analyzed in the context of the individual problem domain and, more importantly, in conjunction with that for the other challenges. This has led to an end-to-end definition of a Mars Planetary Network that would feature: (1) the fusion of deep space Ka-band and optical communications for achieving Mars-Earth high-rate links taking advantage of the optical/RF hybrid 8m/34m antennas in DSN; (2) the integrated application of the Multiple Spacecraft Per Antenna (MSPA) technique, for return link data acquisition, and the Multiple Uplink Per Antenna (MUPA) technique, for forward link data trasnmission, to reduce the number of 34m beam-wave guide (BWG) antennas needed for the era; (3) the integration of three, arrayed, 34m beam-wave guide (BWG) antennas, to provide a high G/T aperture, with the MSPA/MUPA techniques, and a dual “trunk link”approach to cut down the needed G/T -- hence, reducing the number of 34m antennas, relative to that in the single trunk approach by 50%; (4) the deployment of two areostationary/areosynchronous Mars relay orbiters; one of them could also function as (or be served by) a notional Deep Space Habitat (DSH); (5) the opportunistic deployment of a science orbiter in a Pioneer-6 type orbit, equidistant Mars/Earth, that could also serve as an intermediary relay during the Mars superior solar conjunction perod; (6) the existence of the multi-function Mars proximity link that provides the demand-assigned, multiple access (DAMA) capability; and (7) the provision of tracking observables, by leveraging on the planned Mars orbiting and surface infrastructure, to enable the in-situ navigation for surface and orbiting vehicles. This paper provides the description of the proposed Mars Planetary Network in the human exploration era, the trade-off analysis for the various alternative architectures, and the optimal solutions to the key challenges in defining this end-to-end network.

Cheung, Kar-Ming↗
DOE OSTI2020

Self-radiography of imploded shells on OMEGA based on additive-free multi-monochromatic continuum spectral analysis

Radiographs of pure-DT cryogenic imploding shells provide critical validation of progress toward ignition-scalable performance of inertial confinement fusion implosions. Cryogenic implosions on the OMEGA Laser System can be self-radiographed by their own core spectral emission near ≈2 keV. Utilizing the distinct spectral dependences of continuum emissivity and opacity, the projected optical-thickness distribution of imploded shells, i.e., the shell radiograph, can be distinguished from the structure of the core emission distribution in images.Importantly, this can be done without relying on spectral additives (shell dopants), as in previous applications of implosion self-radiography. Furthermore, demonstrations with simulated data show that this technique is remarkably well-suited to cryogenic implosions and can also be applied to self-radiography of imploded room-temperature CH shells at higher spectral energy (hv ≈ 3–5 keV) based on the very similar continuum spectrum of carbon. Experimental demonstration of additive-free self-radiography with warm CH shell implosions on OMEGA will provide an important proof of principle for future applications to cryogenic DT implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Primary yields of protons measured using CR-39 in laser-induced deuteron–deuteron fusion reactions

The deuteron and deuteron (DD) fusion reactions is the most crucial reaction in the nuclear astrophysics and inertial confinement fusion, which is responsible for synthesizing chemical elements, and for powering the stellar evolution. The plasma environment generated by the high-intensity laser used in a DD fusion reaction is similar to the early stage of the Big Bang. Therefore, it is important to study laser-induced DD fusion reactions. Recently, we experimentally investigated such reactions using eight laser beams with the third harmonic impact on a deuterated polyethylene target at the ShenGuang-II Upgrade facility. In this work, we focused on the application of range-filter spectrometers assembled from a 70 μm aluminum filter and two CR-39 nuclear track detectors to measure the yields of primary DD protons. Based on the track diameter calibration results of 3 MeV protons used to diagnose the tracks on the range- filter spectrometers, we measured a primary DD proton yield of approximately (8:52 ± 1:7) × 10 6 , consistent with the yields from similar laser facilities worldwide, indicating that range-filter spectrometry is an effective way to measure primary DD protons. Furthermore, using other accurate detectors may help to measure the rare events of D 3 He protons.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2004

Implementation Challenges for Ceramic Matrix Composites in High Temperature Applications

Ceramic matrix composites are leading candidate materials for a number of applications in aeronautics, space, energy, electronics, nuclear, and transportation industries. In the aeronautics and space exploration systems, these materials are being considered for applications in hot sections of jet engines such as the combustor liner, nozzle components, nose cones, leading edges of reentry vehicles and space propulsion components. Applications in the energy and environmental industries include radiant heater tubes, heat exchangers, heat recuperators, gas and diesel particulate filters (DPFs), and components for land based turbines for power generation. These materials are also being considered for use in the first wall and blanket components of fusion reactors. There are a number of critical issues and challenges related to successful implementation of composite materials. Fabrication of net and complex shape components with high density and tailorable matrix properties is quite expensive, and even then various desirable properties are not achievable. In this presentation, microstructure and thermomechanical properties of composites fabricated by two techniques (chemical vapor infiltration and melt infiltration), will be presented. In addition, critical need for robust joining and assembly technologies in successful implementation of these systems will be discussed. Other implementation issues will be discussed along with advantages and benefits of using these materials for various components in high temperature applications.

Singh, Mrityunjay↗
DOE OSTI2020

Deep convolutional neural networks for multi-scale time-series classification and application to tokamak disruption prediction using raw, high temporal resolution diagnostic data

In this paper we discuss recent advances in deep convolutional neural networks (CNN) for sequence learning, which allow identifying long-range, multi-scale phenomena in long sequences, such as those found in fusion plasmas. We point out several benefits of these deep CNN architectures, such as not requiring experts such as physicists to hand-craft input data features, the ability to capture longer range dependencies compared to the more common sequence neural networks (recurrent neural networks like long short-term memory (LSTM) networks), and the comparative computational efficiency. We apply this neural network architecture to the popular problem of disruption prediction in fusion energy tokamaks, utilizing raw data from a single diagnostic, the Electron Cyclotron Emission imaging (ECEi) diagnostic from the DIII-D tokamak. Initial results trained on a large ECEi dataset show promise, achieving an F 1 -score of ~91% on individual time-slices using only the ECEi data. This indicates the ECEi diagnostic by itself can be sensitive to a number of pre-disruption markers useful for predicting disruptions on timescales not only for mitigation but also avoidance. Future opportunities for utilizing these deep CNN architectures with fusion data are outlined, including impact of recent upgrades to the ECEi diagnostic.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRSDate not supplied

Weldability Investigation of Crack Resistant Aluminum Filler Metals Developed for Large Scale Additive Manufacturing and Industrial Welding Applications

In this study the NASA MSFC welding and manufacturing team investigated a new-age aluminum filler wire designed for welding and additive manufacturing (AM) of high strength aluminum alloys. High strength aluminum alloys are known to exhibit hot cracking and hot tearing issues during fusion welding operations. The goal of this investigation was to determine whether this new-age family of alloys can suppress the hot cracking and hot tearing issues exhibited during welding of high strength aluminum alloys and to do an initial characterization of the mechanical performance of welds created using these filler wires. This study focuses on fusion welding of aluminum alloy 6061 and compares the weldability characteristics of five aluminum filler metals and two forms of 6061 base material. The MSFC team utilized manual gas tungsten arc welding (GTAW) to conduct all welding operations and carried out metallographic analysis accompanied with mechanical testing to evaluate the performance of the welds created during this study. During the study it was observed that the new-age filler wires facilitated grain refinement in the weld fusion zone and were capable of creating crack free welds in aluminum alloy 6061 while exhibiting properties that met or exceeded conventional off the shelf aluminum filler metals.

Welding↗
DOE OSTI2026

Automated ICRF heating surrogate modeling via machine learning

This work introduces automated machine learning workflows that address critical bottlenecks in surrogate model development for Ion Cyclotron Range of Frequencies (ICRF) heating applications. The automated framework includes data analysis tools that transform raw datasets into actionable insights in seconds, replacing weeks of manual exploratory effort and ensuring consistent, reproducible dataset characterization. By integrating advanced hyperparameter optimization (HPO) methods including Bayesian optimization via BoTorch and Tree-structured Parzen Estimators (TPE), the framework significantly reduces model development time from weeks to hours, decreasing computational cost and required expertise, while enabling high-accuracy surrogate models. Compared to traditional hyperparameter scanning (HPS) techniques such as methodical, randomized, and grid searches, HPO methods achieve superior convergence and predictive performance, even when compared to already well-tuned reference models. On NSTX High Harmonic Fast Wave (HHFW) heating datasets, both Random Forest Regressor (RFR) and neural network surrogates demonstrate improved accuracy, achieving R 2 values beyond 0.97 and 0.98, respectively. The results show that while HPO gains are modest for robust architectures like RFR, they become essential for more sensitive models such as neural networks, highlighting the trade-offs across optimization strategies. Through automated workflows that eliminate manual hyperparameter tuning and require minimal ML expertise, this work enables widespread adoption of high-fidelity surrogate models across the fusion community for real-time plasma control, uncertainty quantification, rapid experimental scenario development, and integrated system optimization.

Sanchez-Villar, Alvaro [Princeton Plasma Physics L↗
NASA NTRS1998

Friction-Stir Welding of Large Scale Cryogenic Fuel Tanks for Aerospace Applications

The Marshall Space Flight Center has established a facility for the joining of large-scale aluminum-lithium alloy 2195 cryogenic fuel tanks using the friction-stir welding process. Longitudinal welds, approximately five meters in length, were made possible by retrofitting an existing vertical fusion weld system, designed to fabricate tank barrel sections ranging from two to ten meters in diameter. The structural design requirements of the tooling, clamping and the spindle travel system will be described in this paper. Process controls and real-time data acquisition will also be described, and were critical elements contributing to successful weld operation.

Jones, Clyde S., III↗
DOE OSTI2024

Vertical instability forecasting and controllability assessment of multi-device tokamak plasmas in DECAF with data-driven optimization

Abstract Reliable vertical position control will be an essential element of any future tokamak-based fusion power plant in order to reduce disruptions and maximize performance. We investigate methods to improve vertical controllability boundary determination in plasma operational space and demonstrate a data-driven approach based on direct pseudoinversion of operational space data that is rigorously quantitative, applicable in real-time plasma control systems, and physically intuitive to interpret. Applied to historical shot data from entire run campaigns on the MAST-U, KSTAR, and NSTX tokamaks, this approach, implemented in DECAF, improves vertical displacement event identification accuracy to 98.9%–100%. Further, we explore the application of a physics-based vertical stability metric as an early warning forecaster for vertical displacement events. The development of a linear surrogate model for the plasma current density profile, with a coefficient of determination of 0.992 on the training dataset, enables potential employment of this forecaster in real-time. The application of this approach on historical data from the MAST-U MU02 campaign yields a forecaster with 62.6% accuracy, indicating promise for this method when further refined and potentially coupled with other stability metrics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

What Machine Learning Can and Cannot Do for Inertial Confinement Fusion

Machine learning methodologies have played remarkable roles in solving complex systems with large data, well-defined input–output pairs, and clearly definable goals and metrics. The methodologies are effective in image analysis, classification, and systems without long chains of logic. Recently, machine-learning methodologies have been widely applied to inertial confinement fusion (ICF) capsules and the design optimization of OMEGA (Omega Laser Facility) capsule implosion and NIF (National Ignition Facility) ignition capsules, leading to significant progress. As machine learning is being increasingly applied, concerns arise regarding its capabilities and limitations in the context of ICF. ICF is a complicated physical system that relies on physics knowledge and human judgment to guide machine learning. Additionally, the experimental database for ICF ignition is not large enough to provide credible training data. Most researchers in the field of ICF use simulations, or a mix of simulations and experimental results, instead of real data to train machine learning models and related tools. They then use the trained learning model to predict future events. This methodology can be successful, subject to a careful choice of data and simulations. However, because of the extreme sensitivity of the neutron yield to the input implosion parameters, physics-guided machine learning for ICF is extremely important and necessary, especially when the database is small, the uncertain-domain knowledge is large, and the physical capabilities of the learning models are still being developed. In this work, we identify problems in ICF that are suitable for machine learning and circumstances where machine learning is less likely to be successful. This study investigates the applications of machine learning and highlights fundamental research challenges and directions associated with machine learning in ICF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Study of the Effect of Reflections on High-Power, 110-GHz Pulsed Gyrotron Operation

The effect of reflection is studied experimentally and theoretically on a high-power 110-GHz gyrotron operating in the TE 22,6 mode in 3 μs pulses at 96 kV, 40 A. The experimental setup allows variation of the reflected power from 0 to 33% over a range of gyrotron operating conditions. The phase of the reflection is varied by translating the reflector along the axis. Operating at a higher efficiency point, at 4.40 T with 940kW of output power, reflected power exceeding 11% causes a switch from operation in the TE 22,6 to simultaneous operation in the TE 22,6 and TE 21,6 modes with a large decrease of the total gyrotron output power. This switching effect is in good agreement with simulations using the MAGY code. Operating at a more stable point, 4.44 T with 580kW of output power, when the reflection is increased, the output power remains in the TE 22,6 mode but it decreases monotonically with increasing reflection, dropping to 200kW at 33% reflection. Furthermore, at a reflection above 22%, a power modulation at 25 to 30MHz is observed, independent of the phase of the reflected wave. Such a modulated signal may be useful in spectroscopic and other applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Fast modulating electron cyclotron emission (FMECE) diagnostic for tokamaks

Utilizing variable-frequency channels, e.g., yttrium iron garnet (YIG) bandpass filters, in the intermediate frequency (IF) section of an electron cyclotron emission (ECE) radiometer facilitates flexibility in the volume viewed by the ECE channels as well as high resolution electron temperature and temperature fluctuation measurements in tokamaks. Fast modulating electron cyclotron emission (FMECE), a stand-alone IF section with eight channels, is a novel application of YIG filters for real-time electron temperature gradient and gradient scale length measurements. Key to FMECE is a simultaneous input/output data acquisition unit, as well as a modified type of YIG filters, which is capable of fast switching of their center (set) frequencies with a frequency slew rate of 600 μs/GHz. A new FMECE has been implemented and tested on the DIII-D tokamak, demonstrating its capability in real-time gradient measurements. Here, the data presented here shows that FMECE can identify flattening in the electron temperature profile; the latter can be used as a sensor for real time monitoring and control of plasma instabilities. Implementation and application are planned for the EAST tokamak.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Tunnel ionization within a one-dimensional, undriven plasma sheath

In high density, high temperature plasmas, the plasma sheath that develops can result in extremely high electric fields, on the order of tens to hundreds of V/nm. Under the right conditions, these electric fields can reach magnitudes that can increase the probability of electron tunneling ionization to occur, resulting in one or more electron-ion pairs. The presence of tunneling ionization can then modify the development of the plasma sheath, as well as properties such as the ion and electron densities and plasma potential. The tunnel ionization process for hydrogen atoms is demonstrated, in this work, as implemented in a Sandia National Laboratories, particle-in-cell code Aleph. Results are presented for the application of the tunnel ionization process to a one-dimensional, undriven plasma sheath. Additional results for cases that consider warm ions and neutrals, the inclusion of electron–neutral collisions, and the injection of neutral particles, as well as the application to various plasma devices, will be discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Polarization and phase control of electron injection and acceleration in the plasma by a self-steepening laser pulse

Abstract We describe an interplay between two injection mechanism of background electrons into an evolving plasma bubble behind an intense laser pulse: one due to the overall bubble expansion, and another due to its periodic undulation. The two mechanisms occur simultaneously when an intense laser pulse propagating inside a plasma forms a shock-like steepened front. Periodic undulations of the plasma bubble along the laser propagation path can either inhibit or conspire with electron injection due to bubble expansion. We show that carrier-envelope-phase (CEP) controlled plasma bubble undulation induced by the self-steepening laser pulse produces a unique electron injector—expanding phase-controlled undulating bubble (EPUB). The longitudinal structure of the electron bunch injected by the EPUB can be controlled by laser polarization and power, resulting in high-charge (multiple nano-Coulombs) high-current (tens of kilo-amperes) electron beams with ultra-short (femtosecond-scale) temporal structure. Generation of high-energy betatron radiation with polarization- and CEP-controlled energy spectrum and angular distribution is analyzed as a promising application of EPUB-produced beams.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1990

An approach to space power

Fusion offers the potential for a very high specific power, providing a large specific impulse that can be traded-off with thrust for mission optimization. Thus fusion is a leading candidate for missions beyond the moon. A new approach is discussed for space fusion power, namely Inertial Electrostatic Confinement (IEC). This method offers a high power density in a relatively small, simple device. It appears capable of burning aneutronic fuels which are most desirable for space applications and is well suited for direct conversion. An experimental device to test the concept is described.

Miley, G. H.↗
NASA NTRS2014

Firing Room Remote Application Software Development

The Engineering and Technology Directorate (NE) at National Aeronautics and Space Administration (NASA) Kennedy Space Center (KSC) is designing a new command and control system for the checkout and launch of Space Launch System (SLS) and future rockets. The purposes of the semester long internship as a remote application software developer include the design, development, integration, and verification of the software and hardware in the firing rooms, in particular with the Mobile Launcher (ML) Launch Accessories subsystem. In addition, a Conversion Fusion project was created to show specific approved checkout and launch engineering data for public-friendly display purposes.

Pathways↗