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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 1,171 records · Page 65
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Interactive Scene Analysis Module - A sensor-database fusion system for telerobotic environments

Accomplishing a task with telerobotics typically involves a combination of operator control/supervision and a 'script' of preprogrammed commands. These commands usually assume that the location of various objects in the task space conform to some internal representation (database) of that task space. The ability to quickly and accurately verify the task environment against the internal database would improve the robustness of these preprogrammed commands. In addition, the on-line initialization and maintenance of a task space database is difficult for operators using Cartesian coordinates alone. This paper describes the Interactive Scene' Analysis Module (ISAM) developed to provide taskspace database initialization and verification utilizing 3-D graphic overlay modelling, video imaging, and laser radar based range imaging. Through the fusion of taskspace database information and image sensor data, a verifiable taskspace model is generated providing location and orientation data for objects in a task space. This paper also describes applications of the ISAM in the Intelligent Systems Research Laboratory (ISRL) at NASA Langley Research Center, and discusses its performance relative to representation accuracy and operator interface efficiency.

Cooper, Eric G.↗
NASA NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗
NASA NTRSDate not supplied

Target Tracking with Distributed Sensing and Optimal Data Migration

The paper presents an Extended Kalman Filter based framework for airborne target tracking using adaptive information fusion from multi-modal multi-rate distributed sensors network. First, the tracking algorithm execution location is determined using an optimal data migration strategy, which also computes the associated delays for each sensor data to arrive at the computing location. Next, the fast (zero-delay) sensors information is dynamically fused in the filter correction procedure at the arrival instance of each valid sensor reading. Finally, the target estimation is updated based on the valid slow (delayed) data, which are grouped according to the delay-time steps before application of the Larsen's method. This approach is applied to the synthetic sensor data generated by means of the ground based radar and camera models for the simulated target flight in Reflection simulation environment.

Distributed sensing↗
DOE OSTI2026

Data-Driven Atomic Physics: Harnessing Machine Learning and High-Repetition-Rate Experiments for Laser-driven HED

High-energy-density plasma experiments are central to progress in atomic physics, fusion energy, and national security science, but they have traditionally been constrained by slow data collection and manual, time-intensive analysis. This project targeted that bottleneck by enabling high-repetition-rate experiments to produce and interpret much larger volumes of data quickly enough to guide experiments while they run.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Towards a Robust Adaptive Digital Twin for Fusion Applications

The development of a digital twin system for fusion applications is essential for enhancing the prediction, analysis, and optimization of complex plasma processes. Machine learning (ML), particularly deep learning has demonstrated strong capabilities in modeling such highly nonlinear and intricate systems. However, two critical challenges limit the deployment of deep learning-based digital twins: Uncertainty Quantification (UQ) and data drift. UQ is vital for ensuring trustworthy predictions, especially in decision-support scenarios. Additionally, data-driven models are often sensitive to changes in the underlying data distribution, such as shot-to-shot variations in fusion experiments, which can lead to performance degradation over time. To address these challenges, we are developing an uncertainty-aware, adaptive digital twin framework. Our approach incorporates deep learning models enhanced with Gaussian Process approximations for predictive uncertainty estimation, coupled with an online learning mechanism that enables continuous model adaptation to new experimental data. This adaptive capability allows the data driven models to respond effectively to evolving plasma behaviors and equipment conditions. Specifically, to mitigate the effects of shot-to-shot drift, our system updates itself incrementally as new data becomes available, improving both robustness and fidelity. Our vision is to evolve this data driven model into a self-sustaining digital twin system that leverages UQ based feedback to continuously refine itself and potentially support real-time decision making. This presentation will cover a brief background on uncertainty quantification for ML, our ongoing effort on development of UQ capabilities for ML, our data science pipeline from data collection to model development and analysis and online learning framework for modeling coil deflection at DIII-D. I will also briefly touch upon opportunities and challenges in development of digital twin framework.

Sammuli, Brian [General Atomics]↗
DOE OSTI2025

Nonperturbative Guiding Center Model for Magnetized Plasmas

Perturbative guiding center theory adequately describes the slow drift motion of charged particles in the strongly magnetized regime characteristic of thermal particle populations in various magnetic fusion devices. However, it breaks down for particles with large-enough energy. Here, we report on a data-driven method for learning a nonperturbative guiding center model from full-orbit particle simulation data. We show the data-driven model significantly outperforms traditional asymptotic theory in magnetization regimes appropriate for fusion-born α particles in stellarators, thus opening the door to nonperturbative guiding center calculations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Developing “inverted-corona” fusion targets as high-fluence neutron sources

We present experimental studies of inverted-corona targets as neutron sources at the OMEGA Laser Facility and the National Ignition Facility (NIF). Laser beams are directed onto the inner walls of a capsule via laser-entrance holes (LEHs), heating the target interior to fusion conditions. The fusion fuel is provided either as a wall liner, e.g., deuterated plastic (CD), or as a gas fill, e.g., D 2 gas. Such targets are robust to low-mode drive asymmetries, allowing for single-sided laser drive. On OMEGA, 1.8-mm-diameter targets with either a 10-μm CD liner or up to 2 atm of D 2 -gas fill were driven with up to 18 kJ of laser energy in a 1-ns square pulse. Neutron yields of up to 1.5 × 1010 generally followed expected trends with fill pressure or laser energy, although the data imply some mix of the CH wall into the fusion fuel for either design. Comparable performance was observed with single-sided (1x LEH) or double-sided (2x LEH) drive. NIF experiments tested the platform at scaled up dimensions and energies, combining a 15-μm CD liner and a 3-atm D2-gas fill in a 4.5-mm diameter target, laser-driven with up to 330 kJ. Neutron yields up to 2.6 × 10 12 were measured, exceeding the scaled yield expectation from the OMEGA data. The observed energy scaling on the NIF implies that the neutron production is gas dominated, suggesting a performance boost from using deuterium–tritium (DT) gas. In this work, we estimate that neutron yields exceeding 10 14 should be readily achievable using a modest laser drive of ~300 kJ with a DT fill.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Qualitative and quantitative enhancement of parameter estimation for model-based diagnostics using automatic differentiation with an application to inertial fusion

Parameter estimation using observables is a fundamental concept in the experimental sciences. Mathematical models that represent the physical processes can enable reconstructions of the experimental observables and greatly assist in parameter estimation by turning it into an optimization problem which can be solved by gradient-free or gradient-based methods. In this work, the recent rise in flexible frameworks for developing differentiable scientific computing programs is leveraged in order to dramatically accelerate data analysis of a common experimental diagnostic relevant to laser–plasma and inertial fusion experiments, Thomson scattering. A differentiable Thomson-scattering data analysis tool is developed that uses reverse-mode automatic differentiation (AD) to calculate gradients. By switching from finite differencing to reverse-mode AD, three distinct outcomes are achieved. First, gradient descent is accelerated dramatically to the extent that it enables near real-time usage in laser–plasma experiments. Second, qualitatively novel quantities which require $\mathcal{O}(10^3)$ parameters can now be included in the analysis of data which enables unprecedented measurements of small-scale laser–plasma phenomena. Third, uncertainty estimation approaches that leverage the value of the Hessian become accurate and efficient because reverse-mode AD can be used for calculating the Hessian.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Preservation of Alcator C-Mod Data and Support of ITER Research Through ITPA Participation (Final Technical Report)

This grant supported two primary activities at the MIT Plasma Science and Fusion Center. First, personnel support, hardware upgrades, and software development were used to maintain the C-Mod data archive set. This highly valuable repository contains all of the data generated from operation of the Alcator C-Mod FES User Facility, covering first operation in 1992 through completion of the final experimental campaign on Sept 30, 2016. The archive, stored using the MDSplus architecture, also includes all of the data analysis, which is ongoing, and most of the results of computer modeling of the data. Second, this grant supported activities related to participation of the C-Mod team in the International Tokamak Physics Activites (ITPA), which includes analysis of C-Mod data, in conjunction with data from tokamaks operated around the world, with intense coordination of joint experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Analysis of stimulated Raman scattering using diode data at the Pecos experimental platform

In order to increase neutron yield in fusion experiments on the Magnetized Linear Inertial Fusion (MagLIF) platform, it is important to maximize the energy coupled to the fuel during the laser-preheat stage. However, laser-energy coupling is limited by laser—plasma instabilities (LPI). In this regard, the Pecos facility at Sandia National Laboratories uses the Z-beamlet laser to test and study the effects of LPI on MagLIF-relevant targets. In particular, stimulated Raman scattering (SRS) is measured in Pecos by using two photo-diodes and a near-beam imager. The measurements from the photo-diodes are processed using a synthetic spectrum based on a Gaussian model. With this relatively simple model, the mean wavelength and intensity of backscattered light can be deduced. Our measurements show similar trends as those given by time-resolved spectrometer data. Hence, this model provides a simple way to approximate time-resolved spectra for scattered light by SRS.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2016

Plasma diagnostics in spherical tokamaks with silicon charged-particle detectors

Detection of charged fusion products, such as protons and tritons resulting from D(d, p) t reactions, can be used to determine the position and time dependent fusion reaction rate profile in spherical tokamak plasmas with neutral beam heating. We have developed a prototype instrument consisting of 6 ion-implanted-silicon surface barrier detectors combined with collimators in such a way that each detector can accept 3 MeV protons and 1 MeV tritons and thus provides a curved view across the plasma cross section. The combination of the results from all six detectors will provide information on the spatial distribution of the fusion reaction rate. The expected time resolution of about 1 ms makes it possible to study changes in the reaction rate due to slow variations in the neutral beam density profile, as well as rapid changes resulting from MHD instabilities. Details of the new instrument, its data acquisition system, simulation results, and electrical noise testing results are discussed in this paper. First experimental data are expected to be taken during the current experimental campaign at NSTX-U.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

Thermal conductivity measurements of proton-heated warm dense aluminum

Thermal conductivity is one of the most crucial physical properties of matter when it comes to understanding heat transport, hydrodynamic evolution, and energy balance in systems ranging from astrophysical objects to fusion plasmas. In the warm dense matter regime, experimental data are very scarce so that many theoretical models remain untested. Here we present the first thermal conductivity measurements of aluminum at 0.5–2.7 g/cc and 2–10 eV, using a recently developed platform of differential heating. A temperature gradient is induced in a Au/Al dual-layer target by proton heating, and subsequent heat flow from the hotter Au to the Al rear surface is detected by two simultaneous time-resolved diagnostics. A systematic data set allows for constraining both thermal conductivity and equation-of-state models. Simulations using Purgatorio model or Sesame S27314 for Al thermal conductivity and LEOS for Au/Al release equation-of-state show good agreement with data after 15 ps. Discrepancy still exists at early time 0–15 ps, likely due to non-equilibrium conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2015

Desensitized Optimal Filtering and Sensor Fusion Toolkit

Analytical Mechanics Associates, Inc., has developed a software toolkit that filters and processes navigational data from multiple sensor sources. A key component of the toolkit is a trajectory optimization technique that reduces the sensitivity of Kalman filters with respect to model parameter uncertainties. The sensor fusion toolkit also integrates recent advances in adaptive Kalman and sigma-point filters for non-Gaussian problems with error statistics. This Phase II effort provides new filtering and sensor fusion techniques in a convenient package that can be used as a stand-alone application for ground support and/or onboard use. Its modular architecture enables ready integration with existing tools. A suite of sensor models and noise distribution as well as Monte Carlo analysis capability are included to enable statistical performance evaluations.

Karlgaard, Christopher D.↗
DOE OSTI2018

TENDL-2017: the making of multi-faceted technological nuclear data library - 25340

Multi-purpose methodical nuclear data libraries generated by TALYS/T6 as Evaluated Nuclear Data Library TENDL have been released regularly since 2008. Considerable experience has been acquired during those early production of such unique, truly multi-faceted, multi-particle nuclear data libraries based on the feedback from the developers, evaluators, processing experts and, most importantly, users. The backbone of this achievement is simple and robust: completeness, quality, upgradability and, most of all, reproducibility and methodology. Since TENDL has been seamlessly adopted by many different applications (accelerator, astrophysics, fusion, fission, medical) that require multi-faceted nuclear reaction data forms for shielding, radio-protection, transmutation, materials or earth sciences, it is felt necessary to understand its strengths and remaining weaknesses. The essential knowledge is not the TENDL library itself, but rather the necessary methods, processes, codes, tools and know-how that go into the making of every evaluations of such a library. Current efforts are focused on a proper evaluation of the underlying physics and incorporation of information and metrics into the scientific TALYS/T6 system. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Understanding the fusion yield dependencies in OMEGA DT-layered implosion experiments using a physics-based statistical mapping model

Improving the performance of inertial confinement fusion implosions requires physics models that can accurately predict the response to changes in the experimental inputs. Good predictive capability has been demonstrated for the fusion yield using a statistical mapping of simulated outcomes to experimental data [Gopalaswamy et al., Nature 565(771), 581–586 (2019)]. In this paper, a physics-based statistical mapping approach is used to extract and quantify all the major sources of degradation of fusion yield for direct-drive implosions on the OMEGA laser. Here, the yield is found to be dependent on the age of the deuterium tritium fill, the ℓ = 1 asymmetry in the implosion core, the laser beam-to-target size ratio, and parameters related to the hydrodynamic stability. A controlled set of experiments were carried out where only the target fill age was varied while keeping all other parameters constant. The measurements were found to be in excellent agreement with the fill age dependency inferred using the mapping model. In addition, a new implosion design was created, guided by the statistical mapping model by optimizing the trade-offs between increased laser energy coupling at larger target size and the degradations caused by the laser beam-to-target size ratio and hydrodynamic instabilities. When experimentally performed, an increased fusion yield was demonstrated in targets with larger diameters.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Understanding and Modeling Lossy Compression Schemes on HPC Scientific Data

Scientific simulations generate large amounts of floating-point data, which are often not very compressible using the traditional reduction schemes, such as deduplication or lossless compression. The emergence of lossy floating-point compression holds promise to satisfy the data reduction demand from HPC applications; however, lossy compression has not been widely adopted in science production. We believe a fundamental reason is that there is a lack of understanding of the benefits, pitfalls, and performance of lossy compression on scientific data. In this paper, we conduct a comprehensive study on state-of-the-art lossy compression, including ZFP, SZ, and ISABELA, using real and representative HPC datasets. Our evaluation reveals the complex interplay between compressor design, data features and compression performance. The impact of reduced accuracy on data analytics is also examined through a case study of fusion blob detection, offering domain scientists with the insights of what to expect from fidelity loss. Furthermore, the trial and error approach to understanding compression performance involves substantial compute and storage overhead. To this end, we propose a sampling based estimation method that extrapolates the reduction ratio from data samples, to guide domain scientists to make more informed data reduction decisions.

Lu, Tao↗
DOE OSTI2023

Characterization of boundary precipitation in a heavy ion irradiated tungsten heavy alloy under the simulated fusion environment

In the concerted effort to identify materials capable of surviving the adverse environment of a fusion reactor interior, tungsten heavy alloys have been put forth as leading candidates. Experimental trials and behavioral studies have yielded positive results for their adoption by taking advantage of the alloy’s unique balance of inherently high fracture toughness and low sputter yields; yet due to their relative novelty in the fusion community, there remains a lack of understanding on the response of these materials to the extended high temperature irradiation environment of the reactor interior. Further, to alleviate this issue and provide the necessary data on the behavior of tungsten heavy alloys to the simulated fusion environment, a 90W-7Ni-3Fe alloy has been subjected to elevated temperature sequential Ni + and He + ion irradiations to mimic the expected displacement damage and gas production expected after five years of service as a plasma facing material component. Atomic-scale structural analyses and nanoscale chemical mapping have identified the formation of two distinct precipitation structures, a surface localized η-carbide and an a-W 2 C type tungsten carbide, both of which appear to originate at the bi-phase interface between W and the ductile phase. This irradiation assisted and induced precipitate formation respectively is anticipated to adversely affect these materials by selective embrittlement at bi-phase interfaces leading to a reduction in the material’s overall fracture toughness during prolonged high temperature irradiation. It is asserted that any potential exposure to C during fusion reactor operational service should be minimized as to prevent the formation of these phases.

36 MATERIALS SCIENCE↗