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At least 1,225 records · Page 68

Study of a Plug Nozzle for Supersonic Aircraft Concepts

A plug nozzle with a cylindrical cowl is studied. The geometry is adopted following commercial supersonic aircraft concepts considered in an ongoing NASA program. For the given cowl, the plug geometry is varied that includes shapes developed by a numerical optimization study as well as porous plugs. Experimental data on noise and flow field are discussed with an eye for minimum noise at low nozzle pressure ratios (NPR2) representing landing and takeoff (LTO) conditions. NPR up to about 4.7 is covered in the experiments. Limited thrust data with accompanying numerical simulation results are also presented. Results show that a plug designed for optimum thrust at cruise is noisier while a plug designed for optimum thrust at LTO has less noise, throughout the NPR range covered. The results also show that a plug nozzle can generate transonic tones and excess broadband noise (EBBN) at lower NPR, apart from well-known screech tones and broadband shock associated noise (BBSN) at higher NPR. A long porous plug is found to effectively suppress all these aberrant noise components while suffering less than 1% loss in thrust coefficient.

Jets↗

Study of a Plug Nozzle for Supersonic Aircraft Concepts

A plug nozzle with a cylindrical cowl is studied. The geometry is adopted following commercial supersonic aircraft concepts considered in an ongoing NASA program. For the given cowl, the plug geometry is varied that includes shapes developed by a numerical optimization study as well as porous plugs. Experimental data on noise and flow field are discussed with an eye for minimum noise at low nozzle pressure ratios (NPR2) representing landing and takeoff (LTO) conditions. NPR up to about 4.7 is covered in the experiments. Limited thrust data with accompanying numerical simulation results are also presented. Results show that a plug designed for optimum thrust at cruise is noisier while a plug designed for optimum thrust at LTO has less noise, throughout the NPR range covered. The results also show that a plug nozzle can generate transonic tones and excess broadband noise (EBBN) at lower NPR, apart from well-known screech tones and broadband shock associated noise (BBSN) at higher NPR. A long porous plug is found to effectively suppress all these aberrant noise components while suffering less than 1% loss in thrust coefficient.

Jets↗

Numerical simulation of the transonic flowfield for wing/nacelle configurations

An efficient grid-interfacing zonal algorithm has been developed for computing the three-dimensional transonic flow field about wing/nacelle multicomponent configurations. The algorithm uses the full-potential formulation and the AF2 fully-implicit approximate factorization scheme. The flow field position is computed using a component-adaptive grid approach in which separate grids are employed for the individual components in the multicomponent configuration, where each component grid is optimized for a particular geometry such as the wing or nacelle. The wing and nacelle component grids are allowed to overlap, and flow field information is transmitted from one grid to another through the overlap region using trivariate interpolation. This paper presents a discussion of the computational methods used to generate both the wing and nacelle component grids, the technique used to interface the component grids, and the method used to obtain the inviscid multicomponent flow field solution. Computed results and correlations with experiment are presented to illustrate application of the analysis.

Atta, E. H.↗

Gradient-based optimization of complex nanoparticle heterostructures enabled by deep learning on heterogeneous graphs

Applications of deep learning (DL) to design nanomaterials are hampered by a lack of suitable data representations and training data. Here, in this study, we report efforts to overcome these limitations and leverage DL to optimize the nonlinear optical properties of core–shell upconverting nanoparticles (UCNPs). UCNPs, which have applications in fields such as biosensing, super-resolution microscopy and three-dimensional printing, can emit visible and ultraviolet light from near-infrared excitations. We report a large-scale dataset of UCNP emission spectra based on accurate but expensive kinetic Monte Carlo simulations (N > 6,000) and use these data to train a heterogeneous graph neural network using a physically motivated representation of UCNP nanostructure. Applying gradient-based optimization on the trained graph neural network, we identify structures with 6.5× higher predicted emission under 800-nm illumination than any UCNP in our training set. Our work reveals design principles for UCNP heterostructures and presents a roadmap for DL-based inverse design of nanomaterials.

Sivonxay, Eric [Lawrence Berkeley National Laborat↗

Impact of solenoid induced residual magnetic fields on the prototype SSR1 CM performance

A prototype cryomodule containing eight Single Spoke Resonators type-1 (SSR1) operating at 325 MHz and four superconducting focusing lenses was successfully assembled, cold tested, and accelerated beam in the framework of the PIP-II project at Fermilab. The impact of induced residual magnetic fields from the solenoids on performance of cavities is presented in this contribution. In addition, design optimizations for the production cryomodules as a result of this impact are highlighted.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗

Development of advanced silicon solar cells for Space Station Freedom

This report describes the development of large area high efficiency wrapthrough solar cells for Space Station Freedom. The goal of this contract was the development and fabrication of 8 x 8 cm coplanar back contact solar cells with a minimum output of 1.039 watts/cell. The first task in this program was a modeling study to determine the optimum configuration of the cell and to study the effects of surface passivation, substrate resistivity, and back surface field on the BOL and EOL performance. In addition, the optical stack, including the cell cover, AR coatings, and Kapton blanket, was modeled to optimize 'on orbit' operation. The second phase was a manufacturing development phase to develop high volume manufacturing processes for the reliable production of low recombination velocity boron back surface fields, techniques to produce smooth, low leakage wrapthrough holes, passivation, photoresist application methods, and metallization schemes. The final portion of this program was a pilot production phase. Seven hundred solar cells were delivered in this phase. At the end of the program, cells with average efficiencies over 13 percent were being produced with power output in excess of 1.139 watts/cell, thus substantially exceeding the program goal.

Lillington, David R.↗

A room-temperature polarization-sensitive CMOS terahertz camera based on quantum-dot-enhanced terahertz-to-visible photon upconversion

Detection of terahertz (THz) radiation has many potential applications, but presently available detectors are limited in many aspects of their performance, including sensitivity, speed, bandwidth and operating temperature. Most do not allow the characterization of THz polarization states. Recent observation of THz-driven luminescence in quantum dots offers a possible detection mechanism via field-driven interdot charge transfer. Here, we demonstrate a room-temperature complementary metal–oxide–semiconductor THz camera and polarimeter based on quantum-dot-enhanced THz-to-visible upconversion mechanism with optimized luminophore geometries and fabrication designs. Besides broadband and fast responses, the nanoslit-based sensor can detect THz pulses with peak fields as low as 10 kV cm–1. A related coaxial nanoaperture-type device shows a to-date-unexplored capability to simultaneously record the THz polarization state and field strength with similar sensitivity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Next Generation UAS Based Spectral Systems for Environmental Monitoring

This presentation provides information on the development of a small Unmanned Aerial System(UAS) with a low power, high performance Intelligent Payload Module (IPM) and a hyperspectral imager to enable intelligent gathering of science grade vegetation data over agricultural fields at about 150 ft. The IPM performs real time data processing over the image data and then enables the navigation system to move the UAS to locations where measurements are optimal for science. This is important because the small UAS typically has about 30 minutes of battery power and therefore over large agricultural fields, resource utilization efficiency is important. The key innovation is the shrinking of the IPM and the cross communication with the navigation software to allow the data processing to interact with desired way points while using Field Programmable Gate Arrays to enable high performance on large data volumes produced by the hyperspectral imager.

onboard processing↗

ExaAM: Metal additive manufacturing simulation at the fidelity of the microstructure

Additive manufacturing (AM), or 3D printing, of metals is transforming the fabrication of components, in part by dramatically expanding the design space, allowing optimization of shape and topology. However, although the physical processes involved in AM are similar to those of welding, a field with decades of experimental, modeling, simulation, and characterization experience, qualification of AM parts remains a challenge. The availability of exascale computational systems, particularly when combined with data-driven approaches such as machine learning, enables topology and shape optimization as well as accelerated qualification by providing process-aware, locally accurate microstructure and mechanical property models. We describe the physics components comprising the Exascale Additive Manufacturing simulation environment and report progress using highly resolved melt pool simulations to inform part-scale finite element thermomechanics simulations, drive microstructure evolution, and determine constitutive mechanical property relationships based on those microstructures using polycrystal plasticity. We report on implementation of these components for exascale computing architectures, as well as the multi-stage simulation workflow that provides a unique high-fidelity model of process–structure–property relationships for AM parts. In addition, we discuss verification and validation through collaboration with efforts such as AM-Bench, a set of benchmark test problems under development by a team led by the National Institute of Standards and Technology.

3D printing↗

Multigrid Optimization for Large-Scale Ptychographic Phase Retrieval

Ptychography is a popular imaging technique that combines diffractive imaging with scanning microscopy. The technique consists of a coherent beam that is scanned across an object in a series of overlapping positions, leading to reliable and improved reconstructions. Ptychographic microscopes allow for large fields to be imaged at high resolution at the cost of additional computational expense. Herein, we propose a multigrid-based optimization framework to reduce the computational burdens of large-scale ptychographic phase retrieval. Our proposed method exploits the inherent hierarchical structures in ptychography through tailored restriction and prolongation operators for the object and data domains. Our numerical results show that our proposed scheme accelerates the convergence of its underlying solver and outperforms the ptychographical iterative engine, a workhorse in the optics community.

97 MATHEMATICS AND COMPUTING↗

Development and Assessment of a New Particle Image Velocimetry System in the NASA GRC 225 cm2 Wind Tunnel

As part of an ongoing campaign to provide detailed and thorough measurements in a two-dimensional impinging shock-wave/boundary-layer interaction (SWBLI), a custom implementation of the Particle Image Velocimetry (PIV) measurement technique in the NASA Glenn 225 cm2 Wind Tunnel was constructed. The flow seeding apparatus was devised to locally seed the region of interest in the overall flowfield to avoid coating the viewing window with seed material. The ability of the PIV system to provide small particles which faithfully track the underlying gas-phase flowfield was of key importance for the success of this system to make quality measurements in the SWBLI flowfield. In order to optimize and assess the performance of the particle seeding system, PIV measurements were made across a planar oblique shock wave and particle response was analyzed to quantify the particle lag effects due to the finite inertia of the seed droplets. Video recordings from a camera placed in the wind tunnel plenum tank were also used to discern the near-field behavior of the seeded plume and guide the design evolution of the seeding apparatus. The resulting optimized seeding configuration was applied to make PIV measurements in the wind tunnel test section boundary layer to assess the seed particle spatial coverage and concentration. This sample boundary layer dataset provides an analog to the eventual boundary layer measurements to be made in the axisymmetric test section under much more challenged viewing conditions.

PIV↗

Development and Assessment of a New Particle Image Velocimetry System in the NASA GRC 225 cm2 Wind Tunnel

As part of an ongoing campaign to provide detailed and thorough measurements in a two-dimensional impinging shock-wave/boundary-layer interaction (SWBLI), a custom implementation of the Particle Image Velocimetry (PIV) measurement technique in the NASA Glenn 225 cm2 Wind Tunnel was constructed. The flow seeding apparatus was devised to locally seed the region of interest in the overall flowfield to avoid coating the viewing window with seed material. The ability of the PIV system to provide small particles which faithfully track the underlying gas-phase flowfield was of key importance for the success of this system to make quality measurements in the SWBLI flowfield. In order to optimize and assess the performance of the particle seeding system, PIV measurements were made across a planar oblique shock wave and particle response was analyzed to quantify the particle lag effects due to the finite inertia of the seed droplets. Video recordings from a camera placed in the wind tunnel plenum tank were also used to discern the near-field behavior of the seeded plume and guide the design evolution of the seeding apparatus. The resulting optimized seeding configuration was applied to make PIV measurements in the wind tunnel test section boundary layer to assess the seed particle spatial coverage and concentration. This sample boundary layer dataset provides an analog to the eventual boundary layer measurements to be made in the axisymmetric test section under much more challenged viewing conditions.

PIV↗

Control of Mixing and Reactive Flow Processes

The interdisciplinary field of reactive flow control is one that holds a great deal of promise for the optimization of complex phenomena occurring in many practical systems, ranging from automobile and gas turbine engines to environmental thermal destruction systems. The fundamental underpinnings of combustion control, however, require a detailed level of understanding of complex reactive flow phenomena, and, in the case of closed-loop active control, require the ability to sense (monitor) and actuate (manipulate) flow processes in a spatially distributed manner in "near real time". Hence the ultimate growth and success of the field of reactive flow control is intimately linked: 1) to advances in the understanding, simulation, and model reduction for complex reactive flows, 2) to the development of experimental diagnostic techniques, in particular, to the development of physically robust sensors, and 3) to the development of a framework or frameworks for generation of closed loop control algorithms suitable for unsteady, nonlinear reactive flow systems. The present paper seeks to outline the potential benefits and technical challenges that exist for mixing and combustion control in fundamental as well as practical systems and to identify promising research directions that could help meet these challenges.

Karagozian, A. R.↗

HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017) (and subsequently titled) Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020) (Final Technical Report)

This is the Final Technical Report for the DoE Measurement Innovation (previously Diagnostic Development) grant DE-SC0006077 titled HIBP Applications to Advance Understanding of Plasma Transport Physics (2011-2017), and subsequently titled Development of Beam Measurements to Advance Understanding of Transients and Improve Validation (2017-2020). The grant was funded by the Office of Fusion Energy Sciences (FES) for the period 1 May 2011–17 July 2020. Work performed through the grant has resulted in diagnostic innovations and new measurement capabilities that will improve understanding of transport, magnetic equilibrium, and electric fields in magnetically confined plasmas. We have developed novel hardware and advanced techniques to expand beam-based diagnostic capabilities, and extend measurements to new operating regimes. Some have been realized using a Heavy Ion Beam Probe (HIBP) having traditional features, while other applications have joined our innovations with subsets of advantageous HIBP features. This work has established smaller, more economical detection systems and, in doing so, may enable substantial extension of scenarios in which beam-based diagnostics are deployed. Key Measurement Innovations include: Computer Models and Simulations of HIBP Applications-Computer modeling and simulating of HIBP applications is central to predicting interaction of beam particles with plasmas, designing diagnostic systems, and anticipating measurement characteristics. We have extended the capability and improved measurement fidelity of the HIBP diagnostic on the Madison Symmetric Torus (MST) reversed field pinch (RFP); simulated feasibility of HIBP operation in the Helically Symmetric eXperiment (HSX) optimized stellarator; and investigated the plausibility of HIBP measurements in the ASDEX Upgrade tokamak. We have also developed a new technique that uses ion optics to model a finite phase-space beam. It yields more realistic (than traditional method) estimates of sample volume characteristics, which influence measurement resolution and sensitivity. Extension of Diagnostic Capabilities and Measurements on the MST RFP-Capabilities have been extended using the first and only HIBP installation on an RFP. Challenges associated with operation of the diagnostic on MST include the three-dimensional nature of particle trajectories, temporal topology and amplitude changes in the plasma equilibrium, and strong particle and radiative emission from the plasma. We have addressed these challenges through development of detailed and higher precision diagnostic simulations, calibrated subtraction of noise to resolve secondary ion signals, and implementation of hardware that enables higher fidelity measurement of plasma fluctuations. Development of New Hardware and Measurement Techniques - We have advanced beam-based measurement capabilities via development of new detectors and techniques to determine the poloidal magnetic flux ψ in the plasma, and enable placement of detectors close to the plasma and thus allow a smaller and less expensive diagnostic. We have demonstrated measurement of ψ, an ability that was made possible by development of highly effective noise reduction techniques. We also modeled the effect of non-ideal and instrumentation effects by developing a virtual (simulated) diagnostic. Application of beam-based diagnostics on various devices and multiple magnetic configurations (e.g. stellarator, tokamak, and reversed field pinch) enables investigation of critical physics issues and measurements resulting in the broad parameter space data needed to test and validate theory & modeling.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗