Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “networked lighting”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57

All-atmospheric fabrication of Ag–Cu core–shell nanowire transparent electrodes with Haacke figure of merit >600 × 10–3 Ω−1

Abstract Transparent conducting electrodes (TCEs) are essential components in devices such as touch screens, smart windows, and photovoltaics. Metal nanowire networks are promising next-generation TCEs, but best-performing examples rely on expensive metal catalysts (palladium or platinum), vacuum processing, or transfer processes that cannot be scaled. This work demonstrates a metal nanowire TCE fabrication process that focuses on high performance and simple fabrication. Here we combined direct and plating metallization processes on electrospun nanowires. We first directly metallize silver nanowires using reactive silver ink. The silver catalyzes subsequent copper plating to produce Ag–Cu core–shell nanowires and eliminates nanowire junction resistances. The process allows for tunable transmission and sheet resistance properties by adjusting electrospinning and plating time. We demonstrate state-of-the-art, low-haze TCEs using an all-atmospheric process with sheet resistances of 0.33 Ω sq −1 and visible light transmittances of 86% (including the substrate), leading to a Haacke figure of merit of 652 × 10 –3 Ω −1 . The core–shell nanowire electrode also demonstrates high chemical and bending durability.

36 MATERIALS SCIENCE↗

Magnetic dilution in the triangular lattice antiferromagnet NaYb 1−𝑥 ⁢Lu 𝑥 ⁢O 2

The delafossitelike compound NaYbO 2 hosts a triangular lattice of Yb 3+ moments and is a promising candidate for the realization of a quantum spin liquid ground state—an exotic, quantum-disordered magnetic phase featuring long-range entanglement of spins. Tuning this system away from this quantum-disordered regime toward classical order or spin freezing is a powerful approach to shed light on the nature of the parent ground state. Here we leverage the substitution of nonmagnetic Lu 3+ onto the Yb 3+ sites to study the effects of magnetic disorder in NaYbO 2 using low-temperature ac susceptibility, heat capacity, and muon spin relaxation (𝜇⁢SR) measurements. Here, our 𝜇⁢SR measurements reveal resilient, correlated magnetic fluctuations that persist to at least 15% dilution, precluding conventional spin freezing and magnetic inhomogeneity. Heat capacity and magnetic susceptibility resolve a rapid suppression of the field-induced “up-up-down” magnetic order upon dilution and a crossover in the power-law behavior of the low-temperature magnetic excitations associated with the zero-field quantum disordered ground state. Taken together, these results support the notion of a robust network of entangled moments in NaYbO 2 and provide experimental validation of several models of a Heisenberg triangular lattice antiferromagnet in the presence of disorder.

Muon spin relaxation & rotation↗

Was early Mars warmed by ammonia?

Runoff channels and valley networks present on ancient, heavily cratered Martian terrain suggests that the climate of Mars was originally warm and wet. One explanation for the formation of these channels is that the surface was warmed by the greenhouse effect of a dense, CO2 atmosphere. However, recent work shows that this theory is not consistent for the early period of the solar system. One way to increase the surface temperature predicted is to assume that other greenhouse gases were present in Mars' atmosphere in addition to CO2 and H2O. This possible gas is ammonia, NH3. If ammonia was present in sufficient quantities, it could have raised the surface temperature to 273 K. An adequate source would have been volcanic outgassing if the NH3 produced was shielded from photolysis by an ultraviolet light absorber.

Kasting, J. F.↗

Surface Reconstruction of a Challenging Region with Permanent Shadows on the Moon

As the Earth is orbiting the Sun, there is the region a sunlight can't be reached on the Moon, a satellite of the Earth. Usually, the permanent shadows are located near a pole area and the surface reconstruction in the permanent shadows region is challenging because of the lack of sunlight.In this research, the reconstruction method containing the permanent shadows is suggested. To apply this method, the time-varying shadow region and a permanently shadowed region are needed to be separated. In the time-varying shadow region, the pixel intensity of the image can be composed of the albedo and the reflectance model. Using the light source direction from ISIS3 of USGS, the shape of the region can be extracted from the reflectance model. Though this region is visible in the camera, the change of illumination is quite large in this region, it is hard to reconstruct the shape using stereo-photogrammetry or SfS. So, it is needed of collecting more surface normal information from several pixel level-aligned images. In this process, the albedo information can be initialized and enhanced easily from many images.In the middle of permanent shadows, the high-resolution DEM is generated by LOLA DEM. The LOLA DEM is generated by interpolation between measured data point strips, the actual scene of the permanent shadows. Using the sensor like DIVINER, the Imaginary scene generation via a trained network between the sunlight sensor and other kinds of a sensor is suggested.

Moon, Sunghyun↗

An All-Ceramic, Anisotropic, and Flexible Aerogel Insulation Material

To exploit the high-temperature superinsulation potential of anisotropic thermal management materials, the incorporation of ceramic aerogel into the aligned structural networks is indispensable. Yet, the long-standing obstacle to exploring ultralight superinsulation ceramic aerogels is the inaccessibility of its mechanical elasticity, stability, and anisotropic thermal insulation. Here, we report a recoverable, flexible ceramic fiber-aerogel composite with anisotropic lamellar structure, where the interfacial cross-linking between ceramic fiber and aerogel is important in its superinsulation performance. The resulting ultralight aerogel composite exhibits a density of 0.05 g/cm 3 , large strain recovery (over 50%), and low thermal conductivity (0.0224 W m –1 K –1 ), while its hydrophobicity is achieved by in situ trichlorosilane coating with the water contact angle of 135°. The hygroscopic tests of such aerogel composites demonstrate a reversible thermal insulation. The mechanical elasticity and stability of the anisotropic composites, with its soundproof performance, shed light on the low-cost superelastic aerogel manufacturing with scalability for energy saving building applications.

36 MATERIALS SCIENCE↗

Polar algae flaunt their zinc assets

Metal ions have been at the centre of pivotal points in the evolution of extant life. Oxygen-evolving photosynthesis, which irrevocably reshaped the geochemistry and biology of our planet, has an absolute requirement for metal ions to harvest light, split water and transfer electrons. Access to abundant oxygen then led to the propagation of organisms capable of oxidative metabolism, a process that is also dependent on metal ions for electron transfer and reduction of molecular oxygen. Because of the essential links between metal ions and the proteins that require them to function, as well as changes in metal bioavailability through time, metals have shaped the trajectories that evolution can take. Iron typically steals this show, but with access to whole-genome sequences and transcriptomes, the imprint that zinc has made on biology is coming into focus. Writing in Nature Ecology & Evolution, Ye and colleagues present new insights into the complex connections between zinc bioavailability, adaptation of algae to the polar oceans and the evolution of regulatory networks. By combining field and laboratory-based analyses, the authors suggest that expanded families of zinc-binding proteins have enabled the green alga Microglena sp. YARC to flourish in the harsh conditions of the polar Southern Ocean (Fig. 1). As the waters where this alga occurs are known for their enrichment of zinc, the authors further propose that availability of this metal ion was directly responsible for successful microalgal colonization of polar oceans. To test this hypothesis, the authors compare meta-transcriptomes collected from pole-to-pole and find positive correlations between higher copy numbers for transcripts encoding putative zinc-binding proteins, higher latitudes, lower surface temperatures and dissolved zinc.

59 BASIC BIOLOGICAL SCIENCES↗

Laser Heterodyne Radiometer for Sensitive Detection of CO2 and CH4

We propose to develop an inexpensive, miniaturized, passive laser heterodyne radiometer (LHR) using commercially available telecommunications laser components to measure two significant carbon cycle gases in the atmospheric column: carbon dioxide (CO2) and methane (CH4). This instrument would operate in tandem with the passive aerosol sensor currently used in AERONET (an established network of more than 450 ground aerosol monitoring instruments worldwide). Because aerosols induce a radiative effect that influences terrestrial carbon exchange, simultaneous detection of aerosols with these key carbon cycle gases offers a uniquely comprehensive measurement approach that supports the Decadal Survey. Laser heterodyne radiometry is a technique for detecting weak signals that was adapted from radio receiver technology. In a radio receiver, a weak input signal from a radio antenna is mixed with a stronger local oscillator signal. The mixed signal (beat note, or intermediate frequency) has a frequency equal to the difference between the input signal and the local oscillator. The intermediate frequency is amplified and sent to a detector that extracts the audio from the signal. In a laser heterodyne radiometer, the weak input signal is light that has undergone absorption by a trace gas. The local oscillator is a laser at a near-by frequency - in this case a low-cost distributed feedback (DFB) telecommunications laser. These two light waves are superimposed in either a beamsplitter or in a fiber coupler (as is the case in this design). The signals are mixed in the detector, and the RF beat frequency is extracted. Changes in concentration of the trace gas are realized through analyzing changes in the beat frequency amplitude. A schematic of the progression of the LHR development project is shown in the figure below. At the center (within the dashed line), light from the local oscillator is superimposed upon light that has undergone absorption by a trace gas, in a single mode fiber coupler. Superimposed light is mixed in a fast photoreceiver, and the beat signal is analyzed for changes in absorption. The left portion of the figure depicts a progression of light sources that pass through the trace gas, increasing in complexity in the downward direction. On the right side of the figure, RF signal processing progresses from a commercially available spectrum analyzer to a RF receiver, and finally to an RF filter bank to deconvolute portions of the beat frequency more heavily weighted for different altitudes.

Wilson, Emily L.↗

Multivariate Methods for Prediction of Geologic Sample Composition with Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) uses pulses of laser light to ablate a material from the surface of a sample and produce an expanding plasma. The optical emission from the plasma produces a spectrum which can be used to classify target materials and estimate their composition. The ChemCam instrument on the Mars Science Laboratory (MSL) mission will use LIBS to rapidly analyze targets remotely, allowing more resource- and time-intensive in-situ analyses to be reserved for targets of particular interest. ChemCam will also be used to analyze samples that are not reachable by the rover's in-situ instruments. Due to these tactical and scientific roles, it is important that ChemCam-derived sample compositions are as accurate as possible. We have compared the results of partial least squares (PLS), multilayer perceptron (MLP) artificial neural networks (ANNs), and cascade correlation (CC) ANNs to determine which technique yields better estimates of quantitative element abundances in rock and mineral samples. The number of hidden nodes in the MLP ANNs was optimized using a genetic algorithm. The influence of two data preprocessing techniques were also investigated: genetic algorithm feature selection and averaging the spectra for each training sample prior to training the PLS and ANN algorithms. We used a ChemCam-like laboratory stand-off LIBS system to collect spectra of 30 pressed powder geostandards and a diverse suite of 196 geologic slab samples of known bulk composition. We tested the performance of PLS and ANNs on a subset of these samples, choosing to focus on silicate rocks and minerals with a loss on ignition of less than 2 percent. This resulted in a set of 22 pressed powder geostandards and 80 geologic samples. Four of the geostandards were used as a validation set and 18 were used as the training set for the algorithms. We found that PLS typically resulted in the lowest average absolute error in its predictions, but that the optimized MLP ANN and the CC ANN often gave results comparable to PLS. Averaging the spectra for each training sample and/or using feature selection to choose a small subset of wavelengths to use for predictions gave mixed results, with degraded performance in some cases and similar or slightly improved performance in other cases. However, training time was significantly reduced for both PLS and ANN methods by implementing feature selection, making this a potentially appealing method for initial, rapid-turn-around analyses necessary for Chemcam's tactical role on MSL. Choice of training samples has a strong influence on the accuracy of predictions. We are currently investigating the use of clustering algorithms (e.g. k-means, neural gas, etc.) to identify training sets that are spectrally similar to the unknown samples that are being predicted, and therefore result in improved predictions

Morris, Richard↗

Co-expression networks in Chlamydomonas reveal significant rhythmicity in batch cultures and empower gene function discovery

The unicellular green alga Chlamydomonas reinhardtii is a choice reference system for the study of photosynthesis and chloroplast metabolism, cilium assembly and function, lipid and starch metabolism, and metal homeostasis. Despite decades of research, the functions of thousands of genes remain largely unknown, and new approaches are needed to categorically assign genes to cellular pathways. Growing collections of transcriptome and proteome data now allow a systematic approach based on integrative co-expression analysis. We used a dataset comprising 518 deep transcriptome samples derived from 58 independent experiments to identify potential co-expression relationships between genes. We visualized co-expression potential with the R package corrplot, to easily assess co-expression and anti-correlation between genes. We extracted several hundred high-confidence genes at the intersection of multiple curated lists involved in cilia, cell division, and photosynthesis, illustrating the power of our method. Surprisingly, Chlamydomonas experiments retained a significant rhythmic component across the transcriptome, suggesting an underappreciated variable during sample collection, even in samples collected in constant light. Our results therefore document substantial residual synchronization in batch cultures, contrary to assumptions of asynchrony. We provide step-by-step protocols for the analysis of co-expression across transcriptome data sets from Chlamydomonas and other species to help foster gene function discovery.

59 BASIC BIOLOGICAL SCIENCES↗

Load Profiles Data for the EVI-RoadTrip Web Tool

The dataset contains EVI-RoadTrip outputs, minute-by-minute load profiles in kW for each station in the simulation based on assumed utilization and network density. The load profiles are aggregated to lower spatial resolution (e.g., state-level, corridor-level) by summation of all station loads associated with the respective geography. This results in a load profile for each scenario that summarizes the corridor's, state's, or county's load profile in minute-level resolution.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Expression quantitative trait loci mapping identified PtrXB38 as a key hub gene in adventitious root development in Populus

Summary Plant establishment requires the formation and development of an extensive root system with architecture modulated by complex genetic networks. Here, we report the identification of the PtrXB38 gene as an expression quantitative trait loci (eQTL) hotspot, mapped using 390 leaf and 444 xylem Populus trichocarpa transcriptomes. Among predicted targets of this trans ‐eQTL were genes involved in plant hormone responses and root development. Overexpression of PtrXB38 in Populus led to significant increases in callusing and formation of both stem‐born roots and base‐born adventitious roots. Omics studies revealed that genes and proteins controlling auxin transport and signaling were involved in PtrXB38‐mediated adventitious root formation. Protein–protein interaction assays indicated that PtrXB38 interacts with components of endosomal sorting complexes required for transport machinery, implying that PtrXB38‐regulated root development may be mediated by regulating endocytosis pathway. Taken together, this work identified a crucial root development regulator and sheds light on the discovery of other plant developmental regulators through combining eQTL mapping and omics approaches.

54 ENVIRONMENTAL SCIENCES↗

Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures non-destructively. Pulsed Thermal Tomography Imaging (PTT) provides a capability for non-destructive evaluation (NDE) of subsurface defects in arbitrary size structures. The PTT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PTT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. Following initial qualification of an AM component for deployment in a nuclear reactor, a PTT system can also be used for in-service nondestructive evaluation (NDE) applications. In this report, we describe recent progress in enhancing PTT capabilities in detecting and visualizing microscopic defects in metallic specimens. The thermal tomography (TT) algorithm obtains depth reconstructions of spatial effusivity from the data cube of sequentially recorded surface temperatures. However, interpretation of TT images is non-trivial because of blurring of images with increasing depth. To address this challenge, we have developed a deep learning convolutional neural network (CNN) to classify size and orientation subsurface defects in simulated TT images. CNN is trained on a database of TT images created for a set of simulated metallic structures with elliptical subsurface voids. Test of CNN performance demonstrate the ability to classify radii and angular orientation of subsurface defects in TT images. In addition, we have shown that CNN trained on elliptical defects is capable of classifying irregular-shaped defects obtained from scanning electron microscopy (SEM) of stainless steel sections printed with LPBF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Emissivity measurements in thin metallized membrane reflectors used for microwave radiometer sensors

This paper is concerned with electromagnetic losses in metallized films used for inflatable reflectors. An inflatable membrane is made of tough elastic material such as Kapton, and it is not electromagnetically reflective by design. A film of conducting metal is added to the membrane to enhance its reflective properties. Since the impetus for use of inflatables for spacecraft is the light weight and compact packaging, it is important that the metal film be as thin as possible. However, if the material is not conductive or thick enough, the radiation due to the emissivity of the reflector could be a significant part of the radiation gathered by the radiometer. The emissivity would be of little consequence to a radar or solar collector; but for a radiometer whose signal is composed of thermal radiation, this contribution could be severe. Bulk properties of the metal film cannot be used to predict its loss. For this reason, a program of analysis and measurement was undertaken to determine the emissivities of a number of candidate metallized film reflectors. This paper describes the three types of measurements which were performed on the metallized thin films: (1) a network analyzer system with an L-band waveguide; (2) an S-band radiometer; and (3) a network analyzer system with a C-band antenna free-space transmission system.

Schroeder, Lyle C.↗

Charge transfer driven by ultrafast spin transition in a CoFe Prussian blue analogue

Photoinduced charge-transfer is an important process in nature and technology and is responsible for the emergence of exotic functionalities, such as magnetic order for cyanide-bridged bimetallic coordination networks. Despite its broad interest and intensive developments in chemistry and material sciences, the atomic-scale description of the initial photoinduced process, which couples intermetallic charge-transfer and spin transition, has been debated for decades; it has been beyond reach due to its extreme speed. In this work we study this process in a prototype cyanide-bridged CoFe system by femtosecond X-ray and optical absorption spectroscopies, enabling the disentanglement of ultrafast electronic and structural dynamics. Our results demonstrate that it is the spin transition that occurs first on the Co site within ~50 fs, and it is this that drives the subsequent Fe-to-Co charge-transfer within ~200 fs. This study represents a step towards understanding and controlling charge-transfer-based functions using light.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Light-Level Geolocation of the LANL Population of Western Bluebirds

Options for tracking and reconstructing animal movement are increasingly accessible due to rapidly decreasing costs, smaller sizes, and a proliferation of analytical inference techniques (Rutz and Hays, 2009; Wikelski et al., 2007). A wide variety of options exists for determining movement patterns of animals—from high-resolution pinpoint ARGOS satellite tags to time-consuming and logistically challenging radio telemetry. One option, light-level geolocation, offers small, affordable devices with long battery lives known as global location sensors (GLS), making them ideal for gathering preliminary migratory data. Geolocation works by inferring patterns of animal movement from light-level transitions between day and night (Hill and Braun, 2001). The recent advances in tracking technologies allow biologists to zoom in on migratory behavior, delineating heretofore-unidentified intraspecific migratory behavior (Delmore et al., 2012). The ubiquity of migratory divides (populations within a species that exhibit different migratory patterns) remains largely unknown, but their existence can lead to favorable demographic metrics (e.g., genetic diversity) in conservation contexts (Møller et al., 2011) and necessitate the development of population-specific conservation plans (Delmore et al., 2012). Delimiting the populations within a species that migrate and the extent of their migrations relative to individuals that remain resident across a species’ range has important evolutionary, ecological, and conservation implications. Within this context, Los Alamos National Laboratory (LANL) biologists have leveraged the local Avian Nestbox Network (ANN; Fair and Myers, 2002) to evaluate the migratory behaviors of a common local bird species, the Western Bluebird (Sialia mexicana).

47 OTHER INSTRUMENTATION↗

Estimating Watershed Subsurface Permeability From Stream Discharge Data Using Deep Neural Networks

Subsurface permeability is a key parameter in watershed models that controls the contribution from the subsurface flow to stream flows. Since the permeability is difficult and expensive to measure directly at the spatial extent and resolution required by fully distributed watershed models, estimation through inverse modeling has had a long history in subsurface hydrology. The wide availability of stream surface flow data, compared to groundwater monitoring data, provides a new data source to infer soil and geologic properties using integrated surface and subsurface hydrologic models. As most of the existing methods have shown difficulty in dealing with highly nonlinear inverse problems, we explore the use of deep neural networks for inversion owing to their successes in mapping complex, highly nonlinear relationships. We train various deep neural network (DNN) models with different architectures to predict subsurface permeability from stream discharge hydrograph at the watershed outlet. The training data are obtained from ensemble simulations of hydrographs corresponding to an permeability ensemble using a fully-distributed, integrated surface-subsurface hydrologic model. The trained model is then applied to estimate the permeability of the real watershed using its observed hydrograph at the outlet. Our study demonstrates that the permeabilities of the soil and geologic facies that make significant contributions to the outlet discharge can be more accurately estimated from the discharge data. Their estimations are also more robust with observation errors. Compared to the traditional ensemble smoother method, DNNs show stronger performance in capturing the nonlinear relationship between permeability and stream hydrograph to accurately estimate permeability. Our study sheds new light on the value of the emerging deep learning methods in assisting integrated watershed modeling by improving parameter estimation, which will eventually reduce the uncertainty in predictive watershed models.

54 ENVIRONMENTAL SCIENCES↗

Considerations for Isochronous Data Services over the Proximity-1 Space Link

Future mission concepts for robotic and human explorations will involve a high level of real time control/monitoring operations such as tele-operation for spacecraft rendezvous and surface mobile platforms carrying life-support equipments. The timely dissemination of voice, command, and real-time telemetry for monitoring and coordination purposes is critical for mission success. It is envisioned that future missions will require a network infrastructure capable of supporting isochronous data services. The CCSDS Proximity-1 Space Link Protocol1 could be used to carry isochronous traffic. This paper we will focus on the data link layer portion of the Proximity-1 protocol specification and analyze its jitter and performance for supporting isochronous applications. In particular we will focus on constrained scenarios where the protocol operates in full-duplex mode, carrying isochronous traffic in one direction and error-controlled traffic in the other direction. We analyze the impact of the strict priority scheme in Proximity-1 used to arbitrate channel access on the latency jitter of the isochronous traffic and the efficiency of the reliable data transfer. In general, jitter performance is driven by the loading of the acknowledgement traffic on the forward link. Under light loading condition, the upper-bound of the delay jitter is the transmission duration of an acknowledgement frame on the forward link; for higher loading scenarios, the maximum jitter is scaled up by the inverse of the residual bandwidth, i.e., the spare capacity available in the forward link after accounting for the acknowledgement traffic. We derive analytical expression on the maximum jitter and discuss its performance.

space link↗

Development of a Scalable Risk-informed Predictive Maintenance Cloud-based Strategy at Nuclear Power Plants

The fact that light-water reactor operation and maintenance costs are prohibitively expensive and contribute to the premature decommissioning of nuclear power plants is partly due to how the equipment is monitored. In recent years, cloud computing has emerged as a dominant technology, as its low cost, computing and storage adaptability, and ability to host applications across numerous virtual infrastructures potentially make it a cost-effective alternative to onsite storage and diagnostics. In this paper, a technological assessment is carried out on a provisional cloud deployment architecture for a nuclear power plant predictive monitoring system. This cloud-based monitoring system would enable maintenance and diagnostic analysts and other authorized plant users to remotely monitor equipment functionality, thus enabling early fault detection and effective predictive maintenance practices. To provide data processing and storage, sensor device networking, and database management, the Microsoft Azure cloud platform is utilized as part of the proposed cloud architecture; however, this analysis could be extended to other cloud computing service providers as well. The focus of this paper is on application of cloud resources for enabling predictive maintenance, identification of technological hurdles associated with moving to a cloud-computing-based architecture, and potential benefits from moving to a centralized cloud system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗