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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 289 records · Page 16

Broadband infrared binary-pattern metasurface absorbers with micro-genetic algorithm optimization

Broadband binary-pattern metasurface absorbers are designed and demonstrated in the mid-infrared wavelength range through the micro-genetic algorithm. The tungsten-based metasurface absorbers with the optimized binary-pattern nanostructures exhibit broadband near-perfect absorption due to the multiple plasmonic resonances supported within the unit cell. Furthermore, the influence of minor pixel modifications in the optimized binary-pattern nanostructures on the absorption performance is investigated in the experiment. This Letter presents a promising approach to design and optimize complex optical nanostructures with the desired properties for metamaterial and metasurface applications.

42 ENGINEERING↗

Shape optimization of disc-type flywheels

Techniques were developed for presenting an analytical and graphical means for selecting an optimum flywheel system design, based on system requirements, geometric constraints, and weight limitations. The techniques for creating an analytical solution are formulated from energy and structural principals. The resulting flywheel design relates stress and strain pattern distribution, operating speeds, geometry, and specific energy levels. The design techniques incorporate the lowest stressed flywheel for any particular application and achieve the highest specific energy per unit flywheel weight possible. Stress and strain contour mapping and sectional profile plotting reflect the results of the structural behavior manifested under rotating conditions. This approach toward flywheel design is applicable to any metal flywheel, and permits the selection of the flywheel design to be based solely on the criteria of the system requirements that must be met, those that must be optimized, and those system parameters that may be permitted to vary.

Nizza, R. S.↗

ABC -Auxetics: An Implicit Design Approach for Negative Poisson's Ratio Materials

A novel methodology is introduced for designing auxetic (negative Poisson's ratio) structures based on topological principles and is demonstrated by investigating a new class of auxetics based on two-dimensional (2D) textile weave patterns. Conventional methodology for designing auxetic materials typically involves determining a single deformable block (a unit cell) of material whose shape results in auxetic behavior. Consequently, patterning such a unit cell in a 2D (or 3D) domain results in a larger structure that exhibits overall auxetic behavior. Such an approach naturally relies on some prior intuition and experience regarding which unit cells may be auxetic. Second, tuning the properties of the resulting structures is typically limited to parametric variations of the geometry of a specific type of unit cell. Thus, most of the currently known auxetic structures belong to a selected few classes of unit cell geometries that are explicitly defined in accordance with a specified topological (i.e., grid structure). Herein, a new class of auxetic structures is demonstrated that, while periodic, can be generated implicitly, i.e., without reference to a specific unit cell design. The approach leverages weave-based parameters (A–B–C), resulting in a rich design space for auxetics that is previously unexplored.

36 MATERIALS SCIENCE↗

Scalable Nanoimprint Manufacturing of Functional Multilayer Metasurface Devices

Optical metasurfaces, consisting of subwavelength-scale meta-atom arrays, hold great promise of overcoming the fundamental limitations of conventional optics. Due to their structural complexity, metasurfaces usually require high-resolution yet slow and expensive fabrication processes. Here, using a metasurface polarimetric imaging device as an example, the photonic structures and the Nanoimprint lithography (NIL) processes are designed, creating two separate NIL molds over a patterning area of > 20 mm2 with designed Moiré alignment markers by electron-beam writing, and further subsequently integrate silicon and aluminum metasurface structures on a chip. Uniquely, the silicon and aluminum metasurfaces are fabricated by using the nanolithography and 3D pattern-transfer capabilities of NIL, respectively, achieving nanometer-scale linewidth uniformity, sub-200 nm translational overlay accuracy, and <0.017 rotational alignment error while significantly reducing fabrication complexity and surface roughness. Here, the micro-sized multilayer metasurfaces have high circular polarization extinction ratios as large as ≈20 and ≈80 in blue and red wavelengths. Further, the metasurface chip-integrated CMOS imager demonstrates high accuracy in broad-band, full Stokes parameter analysis in the visible wavelength ranges and single-shot polarimetric imaging. This novel, NIL-based, multilayered nanomanufacturing approach is applicable to the scalable production of large-area functional structures for ultra-compact optic, electronic, and quantum devices.

36 MATERIALS SCIENCE↗

Multimodal sensor fusion framework for residential building occupancy detection

For several years now, smart building energy systems have been a research area of intensive activity. In light of the increasing need for sustainable buildings and energy systems, this trend motivates an increasing need for a solution to reduce carbon dioxide emissions and improve energy efficiency. This work proposes a high-performing and transferable occupancy detection framework that combines sensor data from different data modalities, including time series environmental data (temperature, humidity, and illuminance), image data, and acoustic energy data using ensemble method. To draw out the best prediction performance in each modality, the proposed framework was developed, including various models that were designed to learn the occupancy patterns reflected in the physical data streams. To tackle the time series environmental data, we designed two variants of an occupancy detection spatiotemporal pattern network (Occ-STPN) that performs both feature level and decision level fusion, respectively. We also propose a new metric; the fading memory mean square error (FMMSE), that provides a fair evaluation and penalization of delayed occupancy predictions. Multiple open-sourced datasets, including the Electricity Consumption and Occupancy and the University of California, Irvine's (UCI) building occupancy detection dataset, along with our own real data collected from six different houses, were used to validate the algorithms' performance. The experimental results presented herein break down the performance for each sensing modality, and a detailed analysis of the performance is also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Qualifying the Instrument Thimble 11 Test Position in the Advanced Test Reactor Critical

The Advanced Test Reactor (ATR) is a versatile nuclear research reactor located at the Idaho National Laboratory (INL) in Eastern Idaho, United States of America. It is one of the most powerful and flexible research reactors in the world and is primarily used for materials testing, isotope production and basic nuclear science research. The ATR is a light-water-cooled, beryllium-moderated reactor with a nominal thermal power capacity of 250 MW utilizing specially designed fuel, arranged in a serpentine pattern to create 9 flux traps. The special design of ATR allows for the neutron flux within each of the flux traps providing flexibility for experiments, programs and allowing experiments with different dose requirements to be irradiated simultaneously. The Advance Test Reactor Critical (ATRC) is a full-scale replica of the ATR core but is housed in a pool instead of a pressure vessel. ATRC is usually operated at less than 600 watts [1]. There are 12 dry instrument thimbles located around the outside of the core tank where a variety of measurement equipment is housed to facilitate reactor operations. Currently Instrument Thimble 11 (IT-11) is not utilized in ATR or ATRC. A range of measurements is ongoing to qualify IT-11 as a test platform for nuclear instrumentation research, development and further experimentation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Initial Findings in Qualifying the Instrument Thimble 11 Position in the Advanced Test Reactor Critical

The Advanced Test Reactor (ATR) is a versatile nuclear research reactor located at the Idaho National Laboratory (INL) in Eastern Idaho, United States of America. It is one of the most powerful and flexible research reactors in the world and is primarily used for materials testing, isotope production and basic nuclear science research. The ATR is a light-water-cooled, beryllium-moderated reactor with a nominal thermal power capacity of 250 MW utilizing specially designed fuel, arranged in a serpentine pattern to create 9 flux traps. The special design of ATR allows for the neutron flux within each of the flux traps providing flexibility for experiments, programs and allowing experiments with different dose requirements to be irradiated simultaneously. The Advance Test Reactor Critical (ATRC) is a full-scale replica of the ATR core but is housed in a pool instead of a pressure vessel. ATRC is usually operated at less than 600 watts [1]. There are 12 dry instrument thimbles located around the outside of the core tank where a variety of measurement equipment is housed to facilitate reactor operations. Currently Instrument Thimble 11 (IT-11) is not utilized in ATR or ATRC. A range of measurements is ongoing to qualify IT-11 as a test platform for nuclear instrumentation research, development and further experimentation.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

Optimized metallization patterns for large-area silicon solar cells

Design criteria is presented for optimizing the front-surface metallization pattern of large-area silicon solar cells. A computer program calculates the spacing of metal fingers which minimizes resistive and shadowing losses. Finger spacing and efficiency for the optimum design are presented as a function of finger width and cell size. It is shown that quantitative evaluation of metallization pattern options can be made without cell fabrication.

Matzen, W. T.↗

Cell and module formation research area

Metallization is discussed. The influence of hydrogen on the firing of base-metal pastes in reducing atmospheres is reported. A method for optimization of metallization patterns is presented. A process sequence involving an AR coating and thick-film metallization system capable of penetrating the AR coating during firing is reported. Design and construction of the NMA implantation machine is reported. Implanted back-surface fields and NMA primary (front) junctions are discussed. The use of glass beads, a wave-soldering device, and ion milling is reported. Processing through the module fabrication and environmental testing of its design are reported. Metallization patterns by mathematical optimization are assessed.

Bickler, D. B.↗

Isotopic and Fuel Lattice Parameter Trends in Extended Enrichment and Higher Burnup LWR Fuel, Volume II: BWR

Commercial light water reactor (LWR) operators and fuel vendors in the United States are pursuing changes to nuclear fuel that include extended enrichment (EE) and accident-tolerant fuel (ATF) designs to further improve reactor safety and plant economics. Extended fuel enrichments above 5% 235 U pin enrichment and up to 10% 235 U are a subset of high assay low-enriched uranium (HALEU) that may be deployed in commercial US LWRs in the near term. ATF features, such as cladding coatings or alternative cladding materials, are designed to improve fuel system performance under accident conditions. One goal of EE is to improve fuel cycle economy by enabling fuel to be depleted to higher burnup than the typical current limits (62 gigawatt-days per metric ton of uranium [GWd/MTU]). Adoption of EE, ATF, and high burnup (HBU) fuels in the US commercial fleet requires a clear understanding of the effects on core physics parameters and used fuel isotopic content, as well as confidence in the accuracy of computer code predictions over an expanded range of materials, enrichment, and burnup. A thorough understanding of the applicability and adequacy of benchmark data (e.g., criticality, decay heat, isotopic content) for computer code validation is necessary to ensure that appropriate safety margins are maintained. As part of the US Nuclear Regulatory Commission (NRC) agreement number 31310019N0008, “SCALE Code Development, Assessment and Maintenance,” the effects of EE, ATF, and HBU are being assessed for selected representative LWR fuel designs. The project is divided into phases, and this report summarizes the findings of the Phase 1 work, which focuses on lattice physics parameter and used fuel isotopic changes for a conventional GE14 10 x 10 boiling water reactor (BWR) design with GNF-2 part length rod patterns to model a modern BWR assembly design.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A preliminary attempt to use neural networks for turbulent eddy classification

This note describes an attempt to use standard neural network tools to fashion a means of detecting eddy patterns in the wall region of a turbulent flow. The research was motivated by the desire to formulate a means to use only flow parameters that can be sensed on the wall to describe the passing eddy structure. If a simple formulation can be obtained, it could conceivably be utilized to control actuators embedded in the wall. Such actuators have been developed by Jacobson and Reynolds (1993a), Blackwelder and Liu (1994), Tung et al. (1995), and others. These actuators have the common characteristics that they are small and are typically flush with the wall when not deployed. When they are activated, it is assumed that they will be able to interact constructively with the turbulent eddies near their location to either decrease the wall shear stress, enhance or reduce the mixing, etc. At present, there is only a nascent understanding of the interaction dynamics between the actuators and the eddies in the flow. Nevertheless, for such interaction to succeed, methods to couple the actuators to the oncoming flow must be obtained. General methods must be found that will detect the space and temporal location of the desired structure. In particular, it will be necessary to know when the eddies will arrive at the location of the actuator. This research attempted to use the shear stress measurements on the wall in the vicinity of an actuator location to predict when a particular eddy pattern would arrive and/or occur at the designated location. In this work the eddy pattern to be detected was identified by its velocity signature only.

Blackwelder, Ron F.↗

A Compact Dual-Band Bowtie Antenna for RF and ISM bands Operation

Traditionally, bowtie antennas have been known to exhibit wide impedance characteristics, omnidirectional radiation patterns, and linear polarization. There is a broad range of applications from medical imaging, archaeological survey, and Ground Penetrating Radar (GPR) to trackers and sensor networks where wideband bowtie antenna designs are required for their operations. Broadening the bandwidth of bowtie antenna requires widening the flare angle of the bowtie arms, which consequently results in a large surface area that may not be suitable for space-constrained applications. Moreover, drawback attributes of the wideband bowtie designs feature inconsistent radiation pattern across the bandwidth and low signal-to-noise (SNR) ratios. As it is known, the SNR would be improved in dual- or multi-band antennas due to their reduced bandwidth. To this end, dual-band/multi-band antennas are preferred over wideband antennas in applications where more than a single frequency of interest is present. Previously, a two-port double-dipole elements was reported, whose arms were orthogonally interleaved to facilitate operation in both the standard WLAN frequency bands (J. M. Steyn and et. al, Progress in Electromagnetic Research, Vol. – 10 pp. 151-161). Even though the antenna is not very compact it does exhibit good cross-polarization, moderate gain in both frequency bands. Another dual-band bowtie antenna which excites two bands using a single transmission line was reported (Wen Chao Zheng and et. al, IEEE Trans. Antennas propag., 2014). The design was compact and did not need multi-port feeding network. In this paper, a dual-band compact bowtie antenna operating at 900 MHz (RF band) and 2.45 GHz (ISM band) using a single excitation port is introduced. It is printed on a 1.54mm thick dielectric substrate (εr = 3.38). The antenna consists of two sets of bowtie arms, a microstrip transmission line to feed the bowtie arms, and a ground plane acting as a reflector to partially reduce the back radiation. One of the bowtie arms of each frequency is printed on the top layer and the other arm, which is mirror imaged, is printed on the bottom layer of the substrate. The length of the bowtie controls the resonance frequency of the antenna and the flare angle controls the bandwidth of the antenna. The microstrip transmission line, connected to a 50 Ω SMA probe, feeds the bowtie antenna. The compact antenna can be used for both RF and ISM band applications. The bowtie arms at the lower frequency band are miniaturized by elongating their electrical lengths. The influence of miniaturizing the bowtie arms and the supporting partial ground plane is observed in the reduced peak gain and degraded front-to-back ratio. These are partly neutralized using four quarter-wave choke-slots in the ground plane with two on each side of the feeding transmission line. The proposed antenna is numerically investigated and finalized by the finite-element based full-wave EM solver, ANSYS HFSS. The miniaturization has reduced the ground plane size by ~45% and the arms size by ~41%. In addition to the size reduction benefits, the antenna shows reasonable peak gain and front-to-back ratio in both the bands. The corresponding results will be presented and discussed at the conference.

Saininad Naik↗

Direct Wavelength-Selective Optical and Electron-Beam Lithography of Functional Inorganic Nanomaterials

Direct optical lithography of functional inorganic nanomaterials (DOLFIN) is a photoresist-free method for highresolution patterning of inorganic nanocrystals (NCs) that has been demonstrated using deep UV (DUV, 254 nm) photons.In this work, we expand the versatility of DOLFIN by designing a series of photochemically active NC surface ligands for direct patterning using various photon energies including DUV, near-UV (i-line, 365 nm), blue (h-line, 405 nm), and visible (450 nm) light. We show that the exposure dose for DOLFIN can be similar to 30 mJ/cm 2 , which is small compared to most commercial photopolymer resists. Patterned nanomaterials can serve as highly robust optical diffraction gratings. We also introduce a general approach for resist-free direct electron-beam lithography of functional inorganic nanomaterials (DELFIN) which enables all-inorganic NC patterns with feature size down to 30 mu, while preserving the optical and electronic properties of patterned NCs. The designed ligand chemistries and patterning techniques offer a versatile platform for nano- and micron-scale additive manufacturing, complementing the existing toolbox for device fabrication.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Simulations of Beam Chopping for Potential Upgrades of the SNS LEBT Chopper

The LEBT chopper is a critical element of the SNS accelerator system. In this work, the benefit of increasing the chopping voltage amplitude for the present chopping pattern is shown with beam simulations, and an ongoing hardware upgrade of the chopper pulser units is discussed. In addition, with the prospect of higher voltage capability of the new pulser design, two alternative chopping patterns which reduce the switching frequency of the chopper pulsers down to 1/2 or 1/4 of the present chopping pattern, are also explored with beam simulations.

Han, Baoxi↗

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Preliminary work into this field was promising but given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation (CoCEI) and an execution crowdsourcing platform partner to solicit machine learning framework developments from external contenders. NASA provided contenders with images and video clips of spacesuits with simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, the top five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The weighted scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy. Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA environments such as the NASA Active Response Gravity Offload System (ARGOS). After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗

Machine-learning Solution for Automatic Spacesuit Motion Recognition and Measurement from Conventional Video

Extravehicular Activity (EVA) spacesuits exhibit unique movement patterns due to their design characteristics. Mobility assessments using traditional motion capture systems are cost prohibitive and not feasible for some training conditions (e.g., simulated lunar outdoor terrain). This paper aims to present the ongoing development of machine learning solutions to quantify suit motions from conventional videos without special sensors or hardware. Given the fast growth in deep/machine learning technologies, external expertise was sought from open-source communities. This was expected to accelerate development and provide more cost-effective, time-saving solutions. This work was selected for a NASA Crowdsourcing project through an agency-wide solicitation. Partnerships were formed with the NASA JSC Center of Excellence for Collaborative Innovation and an execution crowdsourcing platform partner to solicit framework developments from external contenders. NASA provided contenders with video clips of spacesuits and simultaneously measured motion capture data during EVA simulation tasks. The contenders used this data to train and develop generalized algorithms to predict motions. At the end of the crowdsourcing event, five solutions were selected from 250 submissions. Each submission was tested and scored using video clips not previously disclosed to the contenders. The scoring metrics measured how well the algorithm detected the suit shape, the 2D suit joint detection accuracy, and 3D joint detection accuracy. The winning solution was able to achieve roughly 85% prediction accuracy (weighted combination of scoring metrics). Overall, the algorithms could efficiently detect various types of spacesuits and motions across different EVA simulation environments such as the Neutral Buoyancy Lab (NBL). However, 3D joint identification is less reliable when parts of the suit were obstructed in the image. After continued improvements and validation, the fully developed system will enable EVA stakeholders to quantify suit kinematic patterns, which can help optimize suit, hardware, and task designs.

Linh Vu↗

Multielement suppressor nozzles for thrust augmentation systems.

The noise reduction and nozzle performance characteristics of large-scale, high-aspect-ratio multielement nozzle arrays operated at low velocities were determined by test. The nozzles are selected for application to high-aspect-ratio augmentor suppressors to be used for augmentor wing airplanes. Significant improvements in noise characteristics for multielement nozzles over those of round or high-aspect-ratio slot nozzles are obtained. Elliptical noise patterns typical of slot nozzles are presented for high-aspect-ratio multielement nozzle arrays. Additional advantages are available in OASPL noise reduction from the element size and spacing. Augmentor-suppressor systems can be designed for maximum beam pattern directivity and frequency spectrum shaping advantages. Measurements of the nozzle wakes show a correlation with noise level data and frequency spectrum peaks. The noise and jet wake results are compared with existing prediction procedures based on empirical jet flow equations, Lighthill relationships, Strouhal number, and empirical shock-induced screech noise effects.

Lawrence, R. L.↗