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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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931 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Electromagnetic Analysis of ITER Electron Cyclotron Emission Components and Support Structures for the Preliminary Design Review

The ITER electron cyclotron emission (ECE) diagnostic system is located at Design Shield Module (DSM) 2, Equatorial Port (EP) 9 to measure electron temperature profile and electron temperature fluctuations and also to assess nonthermal electron distributions via the oblique view. Therefore, ECE has both radial and oblique views with two couples of mirrors for two different optical views. This ECE diagnostic system shall be exposed to significant power due to unabsorbed electron cyclotron heating power in the plasma. It shall also receive large electromagnetic (EM) loads up to 100 MN/m 3 force density due to the eddy currents generated by the short 16-ms transient plasma disruption. The global EM models of EP12 and EP11 with the worst case of plasma disruption Major Disruption Downward Exponential 16 ms Category III (MD_DW_EXP16MS_CATIII) have been provided by ITER. However, the support structure for these critical components, including four mirrors, is still under the design and development phase, especially during the period of preliminary design reviews (PDRs). For those small in-vessel components that are not modeled explicitly for the PDRs, we can extract the magnetic field (B) data and flux variations (dB/dt) at those locations from the global model and then use the B and dB/dt method to calculate the eddy currents, EM forces, and torques on those components in the local submodels. In conclusion, this paper will present the detailed PDR EM analysis results of the ECE components and support structures.

Electromagnetic↗
DOE OSTI2025

Design and Analysis of a Mutual Inductance Level Sensor for Liquid Metals

Here, this article describes the design and analysis of an electromagnetic level sensor for use in high-temperature liquid metal systems. The mutual inductance level sensor (MILS) described in this work was fabricated using two single-conductor mineral insulated cables wrapped in a bifilar fashion around a stainless steel tube core and was housed in an isolating thimble that preserved the pressure boundary of the test vessel. Two sensor variations were fabricated that differ only in active length, 1016 and 1778 mm. Experimental data were collected using the 1016-mm sensor (MILS-MKII-040) that demonstrated a sensitivity of 9.2 μ V/mm in a room temperature testing stand that used solid aluminum as a surrogate for liquid metal. Experimental data were collected using the 1778-mm sensor (MILS-MKII-070) that demonstrated a sensitivity of 6.9 μ V/mm in the high-temperature (300 ° C) liquid sodium environment at the mechanisms engineering test loop (METL) of Argonne National Laboratory. The sensor performance was found to be repeatable over the course of several months, with roughly ±1% deviation from nominal output. Finite element models were developed in COMSOL Multiphysics that fully describe each test setup, and the models were validated using experimental data. The validated COMSOL models were used to perform an array of analyses that examined the performance of the sensor in differing environments. Maximizing the coil diameter inside the isolating thimble was found to maximize the signal and sensitivity of the sensor. An optimal operating frequency was found near 1000 Hz using both experimental data and COMSOL. The influence of a metallic thimble surrounding the sensor and a metallic sensor core was quantified and found to be negligible at the optimal operating frequency. The sensitivity of the sensor was quantified when monitoring the level of additional liquid metals. These include lead, lead-bismuth eutectic (LBE), sodium-potassium alloy (NaK), and lithium (in addition to sodium). The sensitivities were quantified using liquid metal properties at 350 ° C and 650 ° C. The geometry of the test stand model, all material properties used in the model, and the results are presented in a manner that allows the reader can replicate the model and perform additional analyses.

COMSOL↗
NASA NTRS2012

Mars Science Laboratory Drill

This drill (see Figure 1) is the primary sample acquisition element of the Mars Science Laboratory (MSL) that collects powdered samples from various types of rock (from clays to massive basalts) at depths up to 50 mm below the surface. A rotary-percussive sample acquisition device was developed with an emphasis on toughness and robustness to handle the harsh environment on Mars. It is the first rover-based sample acquisition device to be flight-qualified (see Figure 2). This drill features an autonomous tool change-out on a mobile robot, and novel voice-coil-based percussion. The drill comprises seven subelements. Starting at the end of the drill, there is a bit assembly that cuts the rock and collects the sample. Supporting the bit is a subassembly comprising a chuck mechanism to engage and release the new and worn bits, respectively, and a spindle mechanism to rotate the bit. Just aft of that is a percussion mechanism, which generates hammer blows to break the rock and create the dynamic environment used to flow the powdered sample. These components are mounted to a translation mechanism, which provides linear motion and senses weight-on-bit with a force sensor. There is a passive-contact sensor/stabilizer mechanism that secures the drill fs position on the rock surface, and flex harness management hardware to provide the power and signals to the translating components. The drill housing serves as the primary structure of the turret, to which the additional tools and instruments are attached. The drill bit assembly (DBA) is a passive device that is rotated and hammered in order to cut rock (i.e. science targets) and collect the cuttings (powder) in a sample chamber until ready for transfer to the CHIMRA (Collection and Handling for Interior Martian Rock Analysis). The DBA consists of a 5/8-in. (.1.6- cm) commercial hammer drill bit whose shank has been turned down and machined with deep flutes designed for aggressive cutting removal. Surrounding the shank of the bit is a thick-walled maraging steel collection tube allowing the powdered sample to be augured up the hole into the sample chamber. For robustness, the wall thickness of the DBA was maximized while still ensuring effective sample collection. There are four recesses in the bit tube that are used to retain the fresh bits in their bit box. The rotating bit is supported by a back-to-back duplex bearing pair within a housing that is connected to the outer DBA housing by two titanium diaphragms. The only bearings on the drill in the sample flow are protected by a spring-energized seal, and an integrated shield that diverts the ingested powdered sample from the moving interface. The DBA diaphragms provide radial constraint of the rotating bit and form the sample chambers. Between the diaphragms there is a sample exit tube from which the sample is transferred to the CHIMRA. To ensure that the entire collected sample is retained, no matter the orientation of the drill with respect to gravity during sampling, the pass-through from the forward to the aft chamber resides opposite to the exit tube.

Okon, Avi B.↗
DOE OSTI2024

Assessment of vertical stability for negative triangularity pilot plants

Abstract Negative triangularity (NT) tokamak configurations may be more susceptible to magneto-hydrodynamic instability, posing challenges for recent reactor designs centered around their favorable properties, such as improved confinement and operation free of edge-localized modes. In this work, we assess the vertical stability of plasmas with NT shaping and develop potential reactor solutions. When coupled with a conformal wall, NT equilibria are confirmed to be less vertically stable than equivalent positive triangularity (PT) configurations. Unlike PT, their vertical stability is degraded at higher poloidal beta. Furthermore, improvements in vertical stability at low aspect ratio do not translate to the NT geometry. NT equilibria are stabilized in PT vacuum vessels due to the increased proximity of the plasma and the wall on the outboard side, but this scenario is found to be undesirable due to reduced vertical gaps which give less spatial margin for control recovery. Instead, we demonstrate that informed positioning of passively conducting plates can lead to improved vertical stability in NT configurations on par with stability metrics expected in PT scenarios. An optimal setup for passive plates in highly elongated NT devices is presented, where plates on the outboard side of the device reduce vertical instability growth rates to 16% of their baseline value. For lower target elongations, integration of passive stabilizers with divertor concepts can lead to significant improvements in vertical stability. Plates on the inboard side of the device are also uniquely enabled in NT geometries, providing opportunity for spatial separation of vertical stability coils and passive stabilizers.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2017

Abstract - Belbas, Nicholas (EC2)

Originally, I was brought into the Design and Analysis Branch in the Crew and Thermal Systems to work on administrative tasks like archiving and scheduling. However, I ended up splitting my time between secretarial tasks and a technical project. My technical project was originally meant to be a wireless sensor package for the 20ft Spacecraft Thermal Vacuum Chamber in the B7 High Bay. I would be using a miniature wifi development board and a temperature/humidity sensor along with custom 3D modeling to accomplish this. However, after some discussion with my technical mentor, the plan was changed to a mobile autonomous self-charging sensor platform. A mobile platform will allow the sensors to be moved around without depressurizing the chamber. Also, the self-charging aspect of the package allows for almost unlimited time in the chamber. If the on-board battery runs low, the robot can easily be driven to its charging dock and continue to transmit while charging. The driving base is based around a Raspberry Pi 3 board with a 12C PMW DC Motor controller and a PWM controller driving two small gear motors. The sensor transmitter itself is a RHT03 temperature and humidity sensor and Cozir CO2 sensor connected to an ESP8266 Huzzah board. The power distribution system utilizes a pair of 3.7v 3600mah lipo batteries wired to Powerboost 500 boards. Also, the self-charging mechanism utilizes two 12v-max inductive charging coils wired into the same Powerboost boards as the battery. The Raspberry pi is running Python 3.3 for the driving base and Javascript MJPEG library for transmitting live video from the onboard camera. The sensor package is running Arduino-based C++ and the program capturing the data is running PyqtGraph Python and HTML. The shell of the robot itself is a 3D printed case that will (work in progress) snap together. The photo to the left shows the two halves separated from each other. The black shell contains the power distribution boards and connectors while the white shell contains the driving base and data systems.

Belbas, Nicholas↗
DOE OSTI2021

MuSIC@Indiana: An effective tool for accurate measurement of fusion with low-intensity radioactive beams

The design, construction, and characterization of the Multi-Sampling Ionization Chamber, MuSIC@Indiana, are described. This detector provides efficient and accurate measurement of the fusion cross-section at near-barrier energies. The response of the detector to low-intensity beams of 17,18 O, 19 F, 23 Na, 24,26 Mg, 27 Al, and 28 Si at E lab 50–60MeV was examined. MuSIC@Indiana was commissioned by measuring the 18 O+ 12 C fusion excitation function for 11 < E cm < 20 MeV using CH 4 gas. Here, a simple, effective analysis cleanly distinguishes proton capture and two-body scattering events from fusion on carbon. With MuSIC@Indiana, measurement of 15 points on the excitation function for a single incident beam energy is achieved. The resulting excitation function is shown to be in good agreement with literature data.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

High-capacity rotary drum for atomic layer deposition onto powders and small mechanical parts in a hot-walled viscous flow reactor

Atomic layer deposition (ALD) is uniquely capable of providing uniform thin-film coatings on powder substrates, but powder processing has historically required an ALD reactor designed specifically for powders-e.g., a fluidized bed. Tubular hot-walled viscous-flow reactors commonly employed in laboratory-scale ALD research for coating planar substrates such as silicon have been employed previously to coat gram quantities of powder spread out in a thin layer on a tray, but larger quantities of powder introduce long diffusion pathways where reactants are unable to percolate to the bottom of the powder bed to provide uniform coating in reasonable time periods. In this work, we report a rotary drum with a capacity of 100s of grams that is compatible with conventional tubular hot-walled ALD reactors and provides uniform coatings on powders in viscous flow operation. We benchmark this system using Al 2 O 3 ALD with trimethylaluminum and water. We examine the effect of rotation speed and powder quantity on saturation time via in situ quadrupole mass spectroscopy measurements and gravimetric analysis. Finally, the rotary drum we report is able to provide homogenous coating of up to 75g of silica gel powder with a total surface area of similar to 1500m 2 in viscous flow operation with precursor utilization as high as 70%.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Achieving stationary high performance plasmas at Wendelstein 7-X

This work reports on recent results on the search for high performance plasma scenarios at the magnetically confined stellarator fusion device Wendelstein 7-X. In four new designed scenarios, the development from transient toward stationary plasmas of improved performance has been realized. In particular, a high performance duration of up to 5 s, an energy confinement time of 0.3 s, a diamagnetic energy of 1.1 MJ, a central ion temperature of 2.2 keV, and a fusion triple product of 3.4 x 10 19 m -3 ∙ keV ∙ s have been achieved, and previously observed limitations of the machine have been overcome, regarding both the performance and its duration. The two main experimental techniques for stationary high performance are neutral beam injection core fueling on the one hand and the use of a magnetic field configuration with internal islands on the other hand. Two of the developed scenarios are expected to be extendable straightforward toward a duration of several tens of seconds, making use of the long pulse operation capabilities of W7-X.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2013

The DEEP2 Galaxy Redshift Survey: Design, Observations, Data Reduction, and Redshifts

We describe the design and data analysis of the DEEP2 Galaxy Redshift Survey, the densest and largest high-precision redshift survey of galaxies at z approx. 1 completed to date. The survey was designed to conduct a comprehensive census of massive galaxies, their properties, environments, and large-scale structure down to absolute magnitude MB = −20 at z approx. 1 via approx.90 nights of observation on the Keck telescope. The survey covers an area of 2.8 Sq. deg divided into four separate fields observed to a limiting apparent magnitude of R(sub AB) = 24.1. Objects with z approx. < 0.7 are readily identifiable using BRI photometry and rejected in three of the four DEEP2 fields, allowing galaxies with z > 0.7 to be targeted approx. 2.5 times more efficiently than in a purely magnitude-limited sample. Approximately 60% of eligible targets are chosen for spectroscopy, yielding nearly 53,000 spectra and more than 38,000 reliable redshift measurements. Most of the targets that fail to yield secure redshifts are blue objects that lie beyond z approx. 1.45, where the [O ii] 3727 Ang. doublet lies in the infrared. The DEIMOS 1200 line mm(exp −1) grating used for the survey delivers high spectral resolution (R approx. 6000), accurate and secure redshifts, and unique internal kinematic information. Extensive ancillary data are available in the DEEP2 fields, particularly in the Extended Groth Strip, which has evolved into one of the richest multiwavelength regions on the sky. This paper is intended as a handbook for users of the DEEP2 Data Release 4, which includes all DEEP2 spectra and redshifts, as well as for the DEEP2 DEIMOS data reduction pipelines. Extensive details are provided on object selection, mask design, biases in target selection and redshift measurements, the spec2d two-dimensional data-reduction pipeline, the spec1d automated redshift pipeline, and the zspec visual redshift verification process, along with examples of instrumental signatures or other artifacts that in some cases remain after data reduction. Redshift errors and catastrophic failure rates are assessed through more than 2000 objects with duplicate observations. Sky subtraction is essentially photon-limited even under bright OH sky lines; we describe the strategies that permitted this, based on high image stability, accurate wavelength solutions, and powerful B-spline modeling methods. We also investigate the impact of targets that appear to be single objects in ground-based targeting imaging but prove to be composite in Hubble Space Telescope data; they constitute several percent of targets at z approx. 1, approaching approx. 5%-10% at z > 1.5. Summary data are given that demonstrate the superiority of DEEP2 over other deep high-precision redshift surveys at z approx. 1 in terms of redshift accuracy, sample number density, and amount of spectral information. We also provide an overview of the scientific highlights of the DEEP2 survey thus far.

Galaxy↗
NASA NTRS1997

Validation of an Accurate Three-Dimensional Helical Slow-Wave Circuit Model

The helical slow-wave circuit embodies a helical coil of rectangular tape supported in a metal barrel by dielectric support rods. Although the helix slow-wave circuit remains the mainstay of the traveling-wave tube (TWT) industry because of its exceptionally wide bandwidth, a full helical circuit, without significant dimensional approximations, has not been successfully modeled until now. Numerous attempts have been made to analyze the helical slow-wave circuit so that the performance could be accurately predicted without actually building it, but because of its complex geometry, many geometrical approximations became necessary rendering the previous models inaccurate. In the course of this research it has been demonstrated that using the simulation code, MAFIA, the helical structure can be modeled with actual tape width and thickness, dielectric support rod geometry and materials. To demonstrate the accuracy of the MAFIA model, the cold-test parameters including dispersion, on-axis interaction impedance and attenuation have been calculated for several helical TWT slow-wave circuits with a variety of support rod geometries including rectangular and T-shaped rods, as well as various support rod materials including isotropic, anisotropic and partially metal coated dielectrics. Compared with experimentally measured results, the agreement is excellent. With the accuracy of the MAFIA helical model validated, the code was used to investigate several conventional geometric approximations in an attempt to obtain the most computationally efficient model. Several simplifications were made to a standard model including replacing the helical tape with filaments, and replacing rectangular support rods with shapes conforming to the cylindrical coordinate system with effective permittivity. The approximate models are compared with the standard model in terms of cold-test characteristics and computational time. The model was also used to determine the sensitivity of various circuit parameters including typical manufacturing dimensional tolerances and support rod permittivity. By varying the circuit parameters of an accurate model using MAFIA, these sensitivities can be computed for manufacturing concerns, and design optimization previous to fabrication, thus eliminating the need for costly experimental iterations. Several variations were made to a standard helical circuit using MAFIA to investigate the effect that variations on helical tape and support rod width, metallized loading height and support rod permittivity, have on TWT cold-test characteristics.

Kory, Carol L.↗
DOE OSTI2022

Measuring characteristic differences between high- and low-performing discharges on the MegaJOuLe Neutron Imaging Radiography (MJOLNIR) DPF

A dense plasma focus (DPF) is a compact coaxial plasma gun, which completes its discharge as a Z-pinch, producing short (<100 ns) pulses of ions, x rays, and/or neutrons. Lawrence Livermore National Laboratory recently constructed and began operating a new device, the MJOLNIR (MegaJOuLe Neutron Imaging Radiography) DPF, which is designed for single-pulse flash neutron radiography. This device has achieved neutron yields of up to 4.1×10 11 neutrons/pulse at 3.3 MA peak current, and higher-current commissioning is under way. Like most DPFs, MJOLNIR exhibits variable yields in some configurations. Here, we present evidence of the role of parasitic current paths within the gun in stochastically influencing the yield. First through “conditioning shots,” where new hardware has been introduced, we show that increased run-down and run-in speeds correlate with higher yields. These observations are consistent with current being delivered to the electrodes but not to the main plasma sheath, degrading the implosion-driving force. Once nominal conditions are established, we correlate low-performing discharges with smaller current dip and associated voltage spike for a fixed machine configuration. A snow-plow model is able to recreate small-magnitude current dips through the introduction of a parasitic current path, and particle-in-cell simulations establish how parasitic current paths lower the ion beam energy available to produce neutrons. Finally, we observe an increased likelihood of shots with low yield and smaller current dip with increasing fill pressure.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Spectral Element Applications in Complex Nuclear Reactor Geometries: Tet-to-Hex Meshing

The spectral element code Nek5000 is an open-source, higher-order computational fluid dynamics code developed at Argonne National Laboratory. It is designed to solve incompressible Navier-Stokes equations, but it also has a low-Mach-number approximation feature available. Large eddy simulation is approached by explicit filtering of the velocity field (and other fields) to mimic the effect of dissipation due to the unresolved scale. The computational domain is decomposed into second-order hexahedral elements that conform to the boundaries. However, generating a high-quality pure-hexahedral mesh can be challenging for some problems. For simple geometries, traditional blocking methods can be used to decompose the domain into smaller blocks to generate a so-called structural mesh. A structural mesh can maintain good orthogonality but can have a highly skewed mesh to conform to the geometry, as well as unnecessary refinement in the far field. Moreover, for geometries with relative complexity, blocking the geometry becomes impossible. To address these issues, we adopted a let-to-hex strategy to generate a pure hexahedral mesh for Nek5000. First, we generate a pure tetrahedral mesh for the geometry; then we divide one tetrahedral element into four hexahedral elements. A pure tetrahedral mesh could be easily generated for complex geometries by using many current meshing codes. In this paper, we use the commercial codes ANSYS meshing and ANSYSICEM to generate the pure tetrahedral mesh and then convert it to a pure hexahedral mesh. Boundary layers are extruded in ANSYSICEM to maintain near-wall resolution.

ANSYS ICEM↗
DOE OSTI2024

Multi-Source Machine Learning and Thermoplastics Enhanced Aerostructure Manufacturing (mTEAM)

RTX Technology Research Center (RTRC), together with Collins Aerospace (Collins) and Oak Ridge National Laboratory (ORNL) has developed an Artificial Intelligence (AI) / Machine Learning (ML) guided solution to advance the manufacturing and assembly of high performance and lightweight thermoplastic composite (TPC) aerospace products. The solution aims to lower risk, cost and lead time for induction heating based welding and consolidation processes for TPC structure. The cost and lead time of part and material specific process development for induction welding (IW) and induction consolidation will be reduced by replacing traditional empirical methods with optimization methods that merge AI/ML and physics-based process simulations and process experiments with sensing and controls. TPC-IW process development is empirical in nature, and uncertainties in material & process behavior exist near & far from the induction coil. Physics-based simulations can be leveraged directly for process optimization but can be too computationally expensive to run in high fidelity and real time to do robust process optimization. The key impact of successful TPC induction consolidation and welding is cost & lead time reduction for part & material specific consolidation and welding recipes. This is an enabler for more rapid deployment of TPC structures via joining assembly, which can reduce energy & cost intensive usage of autoclaves & ovens. The solution aimed to advance the U.S. Department of Energy’s interests in using thermoplastics and automation in composite manufacturing for improvement of products for existing markets via increased production speeds, reduced costs, and lowered use of energy. Welded TPC structures can offer significant weight & energy savings for high-value commercial aerospace & industrial applications compared to metal & thermoset composite structures assembled by mechanical fastening and/or adhesive bonding. The project was organized into two Budget Periods. Budget Period 1 (BP1) was 15 months and its goal was to perform ML process optimization framework development & deployment on lab-coupon aerostructure components. A Go/No-Go Review was performed at the end of BP1 to verify fulfilment of key tasks & milestones to justify a Go Decision to move into the next Budget Period. Budget Period 2 (BP2) was 12 months and its goal was the deployment of the ML framework for ML process optimization of pilot industrial scale aerostructure components. The overall project aim was to develop & demonstrate ML-enhanced modeling framework that learns process-property mapping from multiple data sources at different fidelities. During BP1, the team accomplished key tasks & milestones to demonstrate the concept of multi-source ML for TPC aerostructure consolidation and assembly. First, the team completed documentation of induction based TPC heating requirements including baseline metrics to compare measured results against. Next the team completed demonstration of data generation from physics-based simulations for ML surrogate model generation and demonstrated the integration of physics-based simulation data into multi-source AI/ML algorithms. In parallel, the team established the lab-coupon scale induction welding system and completed a process to label and reduce generated data from physics-based simulation and experiments for ML surrogate models to enable multi-source ML model training & testing. To complete BP1, the team integrated physics-based simulation data and experimental data into multi-source ML algorithms. This was based on the team completing ML deployment of the induction welding on a lab system at RTRC and AI/ML deployment on existing induction welding line at Collins. ORNL visited both Collins and RTRC sites to witness the TPC induction welding process. Then, ORNL designed and constructed a new version of their vision-based sensing system better adapted to acquire process signals of the TPC induction welding process for process anomaly and defect detection. In BP2, the team accomplished key tasks & milestones to scale up multi-source ML for TPC aerostructure consolidation and assembly from the lab-coupon scale to the pilot-industrial scale. In BP2, the team demonstrated real time anomaly & defect detection via experiments performed by ORNL & RTRC. The team completed ML-optimization heating trials for TPC induction consolidation at Collins, and the team confirmed pilot industrial scale experimental data from Collins was compatible with the developed ML pipeline from RTRC. The team completed sub-element scale ML process optimization demonstration at RTRC, where the team leveraged RTRC’s robotic TPC welding setup to de-risk the ML process optimization by performing ML analysis of recorded temperatures to account for complex part features. Then, the team applied its ML-derived control strategies and ML process optimization framework at Collins to the pilot-industrial scale on a demo skin-stiffener part representative of a nacelle aerostructure fan cowl section. The key innovation is the AI/ML framework enabling effective process development of high performance, lightweight, energy efficient TPCs for composite aircraft structures.

36 MATERIALS SCIENCE↗