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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Towards developing multiscale-multiphysics models and their surrogates for digital twins of metal additive manufacturing

Artificial intelligence (AI) embedded within digital models of manufacturing processes can be used to improve process productivity and product quality significantly. The application of such advanced capabilities particularly to highly digitalized processes such as metal additive manufacturing (AM) is likely to make those processes commercially more attractive. AI capabilities will reside within Digital Twins (DTs) which are living virtual replicas of the physical processes. DTs will be empowered to operate autonomously in a diagnostic control capacity to supervise processes and can be interrogated by the practitioner to inform the optimal processing route for any given product. The utility of the information gained from the DTs would depend on the quality of the digital models and, more importantly, their faster-solving surrogates which dwell within DTs for consultation during rapid decision-making. In this article, we point out the exceptional value of DTs in AM and focus on the need to create high-fidelity multiscale-multiphysics models for AM processes to feed the AI capabilities. We identify technical hurdles for their development, including those arising from the multiscale and multiphysics characteristics of the models, the difficulties in linking models of the subprocesses across scales and physics, and the scarcity of experimental data. We discuss the need for creating surrogate models using machine learning approaches for real-time problem-solving. We further identify non-technical barriers, such as the need for standardization and difficulties in collaborating across different types of institutions. We offer potential solutions for all these challenges, after reflecting on and researching discussions held at an international symposium on the subject in 2019. Here, we argue that a collaborative approach can not only help accelerate their development compared with disparate efforts, but also enhance the quality of the models by allowing modular development and linkages that account for interactions between the various sub-processes in AM. A high-level roadmap is suggested for starting such a collaboration.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Cutaneous and local radiation injuries

The threat of a large-scale radiological or nuclear (R/N) incident looms in the present-day climate, as noted most recently in an editorial in Scientific American (March 2021). These large-scale incidents are infrequent but affect large numbers of people. Smaller-scale R/N incidents occur more often, affecting smaller numbers of people. There is more awareness of acute radiation syndrome (ARS) in the medical community; however, ionising radiation-induced injuries to the skin are much less understood. Here, this article will provide an overview of radiation-induced injuries to the skin, deeper tissues, and organs. The history and nomenclature; types and causes of injuries; pathophysiology; evaluation and diagnosis; current medical management; and current research of the evaluation and management are presented. Cutaneous radiation injuries (CRI) or local radiation injuries (LRI) may lead to cutaneous radiation syndrome, a sub-syndrome of ARS. These injuries may occur from exposure to radioactive particles suspended in the environment (air, soil, water) after a nuclear detonation or an improvised nuclear detonation (IND), a nuclear power plant incident, or an encounter with a radioactive dispersal or exposure device. These incidents may also result in a radiation-combined injury; a chemical, thermal, or traumatic injury, with radiation exposure. Skin injuries from medical diagnostic and therapeutic imaging, medical misadministration of nuclear medicine or radiotherapy, occupational exposures (including research) to radioactive sources are more common but are not the focus of this manuscript. Diagnosis and evaluation of injuries are based on the scenario, clinical picture, and dosimetry, and may be assisted through advanced imaging techniques. Research-based multidisciplinary therapies, both in the laboratory and clinical trial environments, hold promise for future medical management. Great progress is being made in recognising the extent of injuries, understanding their pathophysiology, as well as diagnosis and management; however, research gaps still exist.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2021

Analytics-at-scale of Sensor Data for Digital Monitoring in Nuclear Plants: 2nd Annual Report

For economic reasons, the nuclear industry is witnessing premature closure of nuclear power plants, despite excellent safety records. Operations and Maintenance (O&M) activities are some of the largest costs in operating legacy light-water plants. By reducing O&M costs, nuclear energy can become more economically competitive with other energy sources. This can be achieved by leveraging machine-learning and artificial intelligence technologies to develop data-driven algorithms to better diagnose potential faults within the system. Improved accuracy of the models can lead to a reduction in unnecessary maintenance, thus reducing costs associated with parts, labor, and unnecessary planned, forced, or extended outages. To address these challenges, the goal of this project is to perform research and development in the area of digital monitoring, i.e., the application of advanced sensor technologies (particularly wireless sensor technologies) and data science based analytic capabilities, to advance online monitoring and predictive maintenance in nuclear plants and improve plant performance (efficiency gain and economic competitiveness). This report summarizes the fiscal year 2020 research progress encompassing (1) different wireless vibration sensor and data indicators used to assess the health of a plant asset; (2) development of diagnostic models for fault detection; and (3) development of prognostic models for estimating the health of the system up to 7 days ahead.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Testing Instrument Extremes in the TREAT Facility

TREAT is a transient power-shaping reactor whose primary mission is to enhance safety performance by testing nuclear fuels and materials under thermodynamic and neutronic conditions ranging from off-normal to extreme. Transient testing of nuclear fuels is analogous to car crash testing, in that the dramatic changes commonly seen when comparing the test specimens' initial and final state points necessitate in-situ measuring in order to interpret and understand the evolution of the experiment. TREAT’s experiment design strategy utilizes a highly reconfigurable and accessible reactor core that affords flexibility when installing experiment devices, thanks to the lack of a primary coolant boundary and the inclusion of multiple access points in the reactor bioshield. Within the experiment devices, the test specimens (which are integrated with their test environments), desired instrumentation diagnostics, and safety considerations are all contained in a single engineered package. The experiments encompass various types of environments (e.g., water, sodium, and gas at temperature and pressure), as well as a range of control options (e.g., static or flowing coolants). The experimental conditions are uniquely representative of advanced reactors, providing challenges to sensor performance but also affording a unique opportunity for development and qualification of sensors suited to these environments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1995

Short-range precipitation forecasts using assimilation of simulated satellite water vapor profiles and column cloud liquid water amounts

These observing system simulation experiments investigate the assimilation of satellite-observed water vapor and cloud liquid water data in the initialization of a limited-area primitive equations model with the goal of improving short-range precipitation forecasts. The assimilation procedure presented includes two aspects: specification of an initial cloud liquid water vertical distribution and diabatic initialization. The satellite data is simulated for the next generation of polar-orbiting satellite instruments, the Advanced Microwave Sounding Unit (AMSU) and the High-Resolution Infrared Sounder (HIRS), which are scheduled to be launched on the NOAA-K satellite in the mid-1990s. Based on cloud-top height and total column cloud liquid water amounts simulated for satellite data a diagnostic method is used to specify an initial cloud water vertical distribution and to modify the initial moisture distribution in cloudy areas. Using a diabatic initialization procedure, the associated latent heating profiles are directly assimilated into the numerical model. The initial heating is estimated by time averaging the latent heat release from convective and large-scale condensation during the early forecast stage after insertion of satellite-observed temperature, water vapor, and cloud water formation. The assimilation of satellite-observed moisture and cloud water, together withy three-mode diabatic initialization, significantly alleviates the model precipitation spinup problem, especially in the first 3 h of the forecast. Experimental forecasts indicate that the impact of satellite-observed temperature and water vapor profiles and cloud water alone in the initialization procedure shortens the spinup time for precipitation rates by 1-2 h and for regeneration of the areal coverage by 3 h. The diabatic initialization further reduces the precipitation spinup time (compared to adiabatic initialization) by 1 h.

Wu, Xiaohua↗

NASA NTRS2016

A Generic Modeling Process to Support Functional Fault Model Development

Functional fault models (FFMs) are qualitative representations of a system's failure space that are used to provide a diagnostic of the modeled system. An FFM simulates the failure effect propagation paths within a system between failure modes and observation points. These models contain a significant amount of information about the system including the design, operation and off nominal behavior. The development and verification of the models can be costly in both time and resources. In addition, models depicting similar components can be distinct, both in appearance and function, when created individually, because there are numerous ways of representing the failure space within each component. Generic application of FFMs has the advantages of software code reuse: reduction of time and resources in both development and verification, and a standard set of component models from which future system models can be generated with common appearance and diagnostic performance. This paper outlines the motivation to develop a generic modeling process for FFMs at the component level and the effort to implement that process through modeling conventions and a software tool. The implementation of this generic modeling process within a fault isolation demonstration for NASA's Advanced Ground System Maintenance (AGSM) Integrated Health Management (IHM) project is presented and the impact discussed.

Design Analysis↗

NASA NTRS2017

A Review of Recent Developments in X-Ray Diagnostics for Turbulent and Optically Dense Rocket Sprays

Highly efficient mixing and atomization of fuel and oxidizers is an important factor in many propulsion and power generating applications. To better quantify breakup and mixing in atomizing sprays, several diagnostic techniques have been developed to collect droplet information and spray statistics. Several optical based techniques, such as Ballistic Imaging and SLIPI have previously demonstrated qualitative measurements in optically dense sprays, however these techniques have produced limited quantitative information in the near injector region. To complement to these advances, a recent wave of developments utilizing synchrotron based x-rays have been successful been implemented facilitating the collection of quantitative measurements in optically dense sprays.

Radke, Christopher↗

DOE OSTI2012

Mechanical Design of a High Energy Beam Absorber for the Advanced Superconducting Test Accelerator (ASTA) at Fermilab

A high energy beam absorber has been built for the Advanced Superconducting Test Accelerator (ASTA) at Fermilab. In the facility's initial configuration, an electron beam will be accelerated through 3 TTF-type or ILC-type SRF cryomodules to an energy of 750MeV. The electron beam will be directed to one of multiple downstream experimental and diagnostic beam lines and then deposited in one of two beam absorbers. The facility is designed to accommodate up to 6 cryomodules, which would produce a 75kW beam at 1.5GeV; this is the driving design condition for the beam absorbers. The beam absorbers consist of water-cooled graphite, aluminum and copper layers contained in a helium-filled enclosure. This paper describes the mechanical implementation of the beam absorbers, with a focus on thermal design and analysis. The potential for radiation-induced degradation of the graphite is discussed.

43 PARTICLE ACCELERATORS↗

NASA NTRS2022

Unique NISTAR-Based Climate GCM Diagnostics of the Earth’s Planetary Albedo and Spectral Absorption Through Longitudinal Data Slicing

Deep Space Climate Observatory (DSCOVR) measurements of Earth’s reflected solar and emitted thermal radiation permit a unique model/data comparison perspective that is not readily available from other satellite data. The key factor is the unique Lissajous orbital viewing geometry from the Lagrangian L1 point, which enables a continuous view of Earth’s sunlit hemisphere. The National Institute of Standards and Technology Advanced Radiometer (NISTAR) is the DSCOVR Mission energy budget instrument, which views the reflected and emitted radiation of the Earth’s sunlit hemisphere by means of single pixel active cavity full-spectrum (Band-A, 0.2–100 μm) and filtered solar wavelength (Band-B, 0.2–4.0 μm; and Band-C, 0.7–4.0 μm) radiometer measurements. An additional solar wavelength photodiode channel (0.3–1.1 μm) provides a calibration reference. The objective of this study is the assessment of climate GCM performance via direct model/data comparisons. Such comparisons are difficult due to quasi-chaotic natural variability present in real-world observational data and in climate GCM simulations. This is where the unique DSCOVR viewing geometry makes possible the longitudinal data slicing methodology for more direct model/data comparison. The key point of the longitudinal slicing approach is that data integration over the entire sunlit hemisphere eliminates the quasi-chaotic meteorological weather-scale noise, while preserving intra-seasonal and planetary-scale variability. The rotation of the Earth that retrieves this climate-style, large-scale longitudinal and seasonal variability. The hemispheric averaging is accomplished automatically in NISTAR measurements with its single-pixel view of the Earth. For climate GCMs, this requires implementing the Sunlit Hemisphere Sampling (SHS) scheme to operate on the GCM run-time output data, utilizing the DSCOVR Satellite Ephemeris data to assure precise viewing geometry between NISTAR measurements and GCM output data, while averaging out the meteorological weather noise. However, GCM generated data are radiative fluxes, while NISTAR (and EPIC) measurements are near-backscattered radiances. Conversing NISTSR measurements into radiative fluxes cannot be accomplished using NISTAR data alone, even with detailed support from conventional satellite data. But the identical viewing geometry of Earth’s sunlit hemisphere, and synergistic analyses of EPIC data make it feasible for this conversion of NISTAR near-backscatter radiances into radiative fluxes.

deep space climate observatory↗

DOE OSTI2022

Applications of machine learning to a compact magnetic spectrometer for high repetition rate, laser-driven particle acceleration

Accurately and rapidly diagnosing laser–plasma interactions is often difficult due to the time-intensive nature of the analysis and will only become more so with the rise of high repetition rate lasers and the desire to implement feedback on a commensurate timescale. Diagnostic analysis employing machine learning techniques can help address this problem while maintaining a high degree of accuracy. We report on the application of machine learning to the analysis of a scintillator-based electron spectrometer for experiments on high intensity, laser–plasma interactions at the Colorado State University Advanced Lasers and Extreme Photonics facility. Our approach utilizes a neural network trained on synthetic data and tested on experiments to extract the accelerated electron temperature. By leveraging transfer learning, we demonstrate an improvement in the neural network accuracy, decreasing the network error by 50%.

Swanson, K. K. (ORCID:0000000286880568)↗

DOE OSTI2018

Synthesis of SHAL Analogs and Metabolites Final Report CRADA No. TC02221.0

In October 2010 SHAL Technologies obtained a limited exclusive license from Lawrence Livermore National Security (LLNLS) to develop and commercialize selective high affinity ligands (SHALs) developed by its cofounders as diagnostics and therapeutics for treating B-cell lymphomas and other cancers in in pets and humans. In order to commercialize the drug candidates and technology icensed from LLNL, SHAL Technologies' current research and development is focused on completing the efficacy and toxicology studies required by the FDA to advance the SHAL SH7139 into a phase I clinical trial. SHAL Technologies was awarded a two-year Phase II SBIR grant to conduct these studies in preparation for the submission of the investigational New Drug (IND) application required to open clinical trials. This CRADA, which was funded by the grant, was a collaborative effort between Dr. Saphon Hok, a chemist at LLNL, and SHAL Technologies that focused the on the synthesis and purification of small quantities of the selective high affinity ligand (SHAL) SH7139, several modified forms of SH7139, and a set of SH7139 metabolites needed by SHAL Technologies, Inc. to complete milestones in the grant as well as the final pre-clinical testing of the drug.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2019

Features that Further Performance Limits of Nuclear Fuel Fabrication: Opportunities for Additive Manufacturing of Nuclear Fuels

One goal of the Transformational Challenge Reactor (TCR) program is to fully assess the opportunity space for additive manufacturing (AM) to overcome the material limitations restricting development and deployment of nuclear power. This report presents an initial analysis of the opportunities for using AM to significantly impact the nuclear fuel fabrication paradigm. The conventional limitations of the three basic solid fuel types are examined herein, and. possibilities for fabrication technologies to overcome these limitations are outlined. Areas that can be most significantly improved by AM are those in which conventional nuclear fuel fabrication routes are known to limit performance. For monolithic systems, one high priority area is fabrication of heterogeneous duplex and compositionally graded structures— fuel designs that bring significant benefits to fuel utilization. A critical first step in meeting this challenge is to successfully demonstrate AM’s ability to achieve representative density and microstructures for fuel materials such as UO 2 . The area with the highest potential for pairing AM methodology with the challenges of nuclear fuel deployment is advanced matrices for particle and dispersion fuels that are free from conventional processing constraints. AM has the potential to achieve packing fractions and matrix quality that are superior to those available through conventional methods. Finally, the use of digital twin data collection, which is possible through in situ build diagnostics, may greatly reduce uncertainty regarding distribution of uranium in these systems. A subsequent FY19 TCR milestone will examine the suitability of existing commercial systems to address these challenges.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS1985

Progress report - Advanced cryogenic OTV engine technology

New technologies for space-based, reusable, throttleable, cryogenic orbit transfer propulsion are being evaluated. A variable-thrust (200 to 3000 lbF), 2000 psi chamber pressure, LO2/LH2 engine has been selected to demonstrate the 20-hour, 500-restart life goal, and a specific impulse in excess of 480 lbF-sec/lbM. The results of recent vehicle-engine integration analyses and the progress in design, fabrication, and testing are provided. Emphasis is placed on the following technology areas being investigated in support of the advanced engine design: LOX hydrostatic bearings; burn-resistant materials for high-pressure GOX turbines and valves; high surface-low flux annular combustion chambers for the dual propellant expander cycle; improved cooling approaches for high-pressure combustion chambers, new concepts in integrated controls; and engine health diagnostics.

Schoenman, L.↗

NASA NTRS2007

Advances in Ground Transmitters for the NASA Deep Space Network

The Deep Space Network (DSN), managed by the Jet Propulsion Laboratory for NASA, is equipped with multiple microwave transmitters ranging in average radiated power from 200 W to 400 kW. The transmitters are used for routine or emergency communication with spacecraft, for navigation, and for radio science tasks. The latest advances in transmitter engineering were implemented in a new generation of 20-kW dual-band transmitters developed for the DSN 34-m beam waveguide antennas. Innovations include additional X-band communication capability for near Earth missions, new control algorithms, automated calibration, improved and expanded computerized monitoring and diagnostics, reduced cabling, and improved maintainability. The innovations were very beneficial for the DSN 'overload' during the Mars 2003/2004 missions and will benefit other missions throughout the next decade. This paper describes the current design of the new transmitters and possible future developments.

microwaves↗

NASA NTRS2011

SPoRT's Participation in the GOES-R Proving Ground Activity

The next generation geostationary satellite, GOES-R, will carry two new instruments with unique atmospheric and surface observing capabilities, the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM), to study short-term weather processes. The ABI will bring enhanced multispectral observing capabilities with frequent refresh rates for regional and full disk coverage to geostationary orbit to address many existing and new forecast challenges. The GLM will, for the first time, provide the continuous monitoring of total lightning flashes over a hemispherical region from space. NOAA established the GOES-R Proving Ground activity several years ago to demonstrate the new capabilities of these instruments and to prepare forecasters for their day one use. Proving Ground partners work closely with algorithm developers and the end user community to develop and transition proxy data sets representing GOES-R observing capabilities. This close collaboration helps to maximize refine algorithms leading to the delivery of a product that effectively address a forecast challenge. The NASA Short-term Prediction Research and Transition (SPoRT) program has been a participant in the NOAA GOES-R Proving Ground activity by developing and disseminating selected GOES-R proxy products to collaborating WFOs and National Centers. Established in 2002 to demonstrate the weather and forecasting application of real-time EOS measurements, the SPoRT program has grown to be an end-to-end research to operations activity focused on the use of advanced NASA modeling and data assimilation approaches, nowcasting techniques, and unique high-resolution multispectral data from EOS satellites to improve short-term weather forecasts on a regional and local scale. Participation in the Proving Ground activities extends SPoRT s activities and taps its experience and expertise in diagnostic weather analysis, short-term weather forecasting, and the transition of research and experimental data to operational decision support systems like NAWIPS, AWIPS, AWIPS2, and Google Earth. Recent SPoRT Proving Ground activities supporting the development and use of a pseudo GLM total lightning product and the transition of the AWG s Convective Initiation (CI) product, both of which were available in AWIPS and AWIPS II environments, by forecasters during the Hazardous Weather Testbed (HWT) Spring Experiment. SPoRT is also providing a suite of SEVIRI and MODIS RGB image products, and a high resolution composite SST product to several National Centers for use in there ongoing demonstration activities. Additionally, SPoRT has involved numerous WFOs in the evaluation of a GOES-MODIS hybrid product which brings ABI-like data sets in front of the forecaster for everyday use. An overview of this activity will be presented at the conference.

Jedlovec, Gary↗

NASA NTRSDate not supplied

A Multi-Faceted Approach to Demonstrating Multi-Functional Integrated Medical Devices to Advance Earth-Independent Medical Operations

INTRODUCTION TO MIM DEVICES Multi-functional Integrated Medical (MIM) devices conveniently incorporate multiple medical system capabilities within one device. The NASA Exploration Medical Integrated Product Team (XM-IPT) sponsored a market survey and trade study which identified the Tempus ProTM and the LifeBot 10® as the MIM devices that best met the evaluation criteria of the trade study. The Tempus ProTM (Remote Diagnostic Technologies, Ltd., Philips Corp., Farnborough, UK) and LifeBot 10® (LifeBot Health, Chicago, IL) both provide vital sign measurements such as blood pressure, electrocardiograms, heart rate, end tidal CO2, respiration rate, pulse oximetry and temperature along with ultrasound imaging. A video laryngoscopy capability is unique to the Tempus ProTM, while the LifeBot 10® supports connectivity with a digital stethoscope, otoscope, eye exam camera, and dermatoscope. Both devices include procedural guidance capabilities and have various data transmission and report generation features. TECHNOLOGY DEMONSTRATIONS NASA’s exploration-class missions will have severe resource constraints, long return trip durations, significant communication delays, and limited resupply opportunities. The medical systems of these missions will need to fit within an Earth-Independent Medical Operations (EIMO) construct. Key features of an EIMO medical system include: 1) technologies that support the prevention, diagnosis, and treatment of spaceflight medical events; 2) components that meet mass, volume, power and crew time/training constraints; 3) consideration of the medical skill level of the astronaut caregiver; 4) collection, storage and analysis of medical data within a central data architecture; and 5) incorporation of appropriate guidance and support tools that allow crew autonomy. Evaluations are underway to determine if it will be beneficial to include MIM devices within exploration medical systems by conducting a series of planned technical demonstrations. Exploration Atmosphere Chamber studies are being performed to determine MIM functionality in a high oxygen concentration atmosphere. A side-by-side comparison of the Tempus ProTM and LifeBot 10® will be performed during ground-based demonstrations. Use of the MIM devices within an EIMO medical scenario simulation will be practiced during ground-based demonstrations in preparation for International Space Station (ISS) demonstrations of the MIM device. These various demonstrations are designed to gather evidence for or against the inclusion of MIM devices within an EIMO medical system. EXPECTED DEMONSTRATION OUTCOMES Information will be gained about the feasibility, benefits, and challenges of using a multifunctional, all-in-one, medical device for medical diagnosis. Information will also be collected about performance differences as available ground support decreases. Gaining this understanding will allow for further development of exploration medical system capabilities, which take the EIMO construct into consideration.

B. E. Lewandowski↗

DOE OSTI2019

Performance of a machine learning-based decision model to help clinicians decide the extent of lymphadenectomy (D1 vs. D2) in gastric cancer before surgical resection

Background: Controversy still exists on the optimal surgical resection for potentially curable gastric cancer (GC). Use of radiologic evaluation and machine learning algorithms might predict extent of lymphadenectomy to limit unnecessary surgical treatment. We purposed to design a machine learning-based clinical decision-support model for predicting extent of lymphadenectomy (D1 vs. D2) in local advanced GC. Methods: Clinicoradiologic features available from routine clinical assignments in 557 patients with GCs were retrospectively interpreted by an expert panel blinded to all histopathologic information. All patients underwent surgery using standard D2 resection. Decision models were developed with a logistic regression (LR), support vector machine (SVM) and auto-encoder (AE) algorithm in 371 training and tested in 186 test data, respectively. The primary end point was to measure diagnostic performance of decision model and a Japanese gastric cancer treatment guideline version 4th (JPN 4th) criteria for discriminate D1 (pT1 + pN0) versus D2 (≥ pT1 + ≥ pN1) lymphadenectomy. Results: The decision model with AE analysis produced highest area under ROC curve (train: 0.965, 95% confidence interval (CI) 0.948–0.978; test: 0.946, 95% CI 0.925–0.978), followed by SVM (train: 0.925, 95% CI 0.902–0.944; test: 0.942, 95% CI 0.922–0.973) and LR (train: 0.886, 95% CI 0.858–0.910; test: 0.891, 95% CI 0.891–0.952). By this improvement, overtreatment was reduced from 21.7% (121/557) by treat-all pattern, to 15.1% (84/557) by JPN 4th criteria, and to 0.7–0.9% (4–5/557) by the new approach. Conclusions: The decision model with machine learning analysis demonstrates high accuracy for identifying patients who are candidates for D1 versus D2 resection. Its approximate 14–20% improvements in overtreatment compared to treat-all pattern and JPN 4th criteria potentially increase the number of patients with local advanced GCs who can safely avoid unnecessary lymphadenectomy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2016

How does a probe inserted into the discharge influence the plasma structure?

Shielding the bias applied to the probe by the sheath formed around it and determination of parameters of unperturbed plasmas are in the basis of the probe diagnostics. The results from a two-dimensional model of a discharge with a probe inserted in it show that the probe influences the spatial distribution of the plasma parameters in the entire discharge. The increase (although slight) in the electron temperature, due to the increased losses of charged particles on the additional wall in the discharge (mainly the probe holder), leads to redistribution of the plasma density and plasma potential, as shown by the results obtained at the floating potential of the probe. The deviations due to the bias applied to the probe tip are stronger in the ion saturation region of the probe characteristics. The pattern of the spatial redistribution of the plasma parameters advances together with the movement of the probe deeper in the discharge. Although probe sheaths and probe characteristics resulting from the model are shown, the study does not aim at discussions on the theories for determination of the plasma density from the ion saturation current. Regardless of the modifications in the plasma behavior in the entire discharge, the deviations of the plasma parameters at the position of the probe tip and, respectively, the uncertainty which should be added as an error when the accuracy of the probe diagnostics is estimated do not exceed 10%. Consequently, the electron density and temperature obtained, respectively, at the position of the plasma potential on the probe characteristics and from its transition region are in reasonable agreement with the results from the model of the discharge without a probe. Being in the scope of research on a source of negative hydrogen ions with the design of a matrix of small radius inductive discharges, the model is specified for a low-pressure hydrogen discharge sustained in a small-radius tube.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗