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Acoustic modal analysis of unique fused-silica fibers for passive non-destructive structural monitoring
The goal of non-destructive acoustic sensing is to passively monitor innate structural parameters such as temperature, strain, and pressure. Intended for use in harsh structural environments, a distributed acoustic sensing system has been created using a single mode, radiation hardened, fused-silica core rod and a high-resolution acoustic sensor. This study aims to enhance the capabilities of the acoustic sensor by manipulating the fused-silica core rod, geometrically, to induce and control additional acoustic reflections. Here, two geometries are demonstrated to markedly improve upon previous fiber designs and result in a consistent acoustic profile.
Multi-Modal Machine Learning to Predict the Energy Discharge Levels from a Multi-Cell Mechanical Draft Cooling Tower
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The Urban Observatory: A Multi-Modal Imaging Platform for the Study of Dynamics in Complex Urban Systems
We describe an “Urban Observatory” facility designed for the study of complex urban systems via persistent, synoptic, and granular imaging of dynamical processes in cities. An initial deployment of the facility has been demonstrated in New York City and consists of a suite of imaging systems—both broadband and hyperspectral—sensitive to wavelengths from the visible (∼400 nm) to the infrared (∼13 micron) operating at cadences of ∼0.01–30 Hz (characteristically ∼0.1 Hz). Much like an astronomical survey, the facility generates a large imaging catalog from which we have extracted observables (e.g., time-dependent brightnesses, spectra, temperatures, chemical species, etc.), collecting them in a parallel source catalog. We have demonstrated that, in addition to the urban science of cities as systems, these data are applicable to a myriad of domain-specific scientific inquiries related to urban functioning including energy consumption and end use, environmental impacts of cities, and patterns of life and public health. We show that an Urban Observatory facility of this type has the potential to improve both a city’s operations and the quality of life of its inhabitants.
Distributed Modal Signal of Thin Paraboloidal Shells
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Fixed Base Modal Testing Using the NASA GRC Mechanical Vibration Facility
The Space Power Facility at NASA's Plum Brook Station houses the world's largest and most powerful space environment simulation facilities, including the Mechanical Vibration Facility (MVF), which offers the world's highest-capacity multi-axis spacecraft shaker system. The MVF was designed to perform sine vibration testing of a Crew Exploration Vehicle (CEV)-class spacecraft with a total mass of 75,000 pounds, center of gravity (cg) height above the table of 284 inches, diameter of 18 feet, and capability of 1.25 gravity units peak acceleration in the vertical and 1.0 gravity units peak acceleration in the lateral directions. The MVF is a six-degree-of-freedom, servo-hydraulic, sinusoidal base-shake vibration system that has the advantage of being able to perform single-axis sine vibration testing of large structures in the vertical and two lateral axes without the need to reconfigure the test article for each axis. This paper discusses efforts to extend the MVF's capabilities so that it can also be used to determine fixed base modes of its test article without the need for an expensive test-correlated facility simulation.
A Multi-Modality Mobility Concept for a Small Package Delivery UAV
This paper will discuss a different approach to the typical notional small package delivery drone concept. Most delivery drone concepts employ a point-to-point aerial delivery CONOPS (Concept of Operations) from a warehouse directly to the front or back yards of a customers residence or a commercial office space. Instead, the proposed approach is somewhat analogous to current postal deliveries: a small aerial vehicle flies from a warehouse to designated neighborhood VTOL (Vertical Take-Off and Landing) landing spots where the aerial vehicle then converts to a "roadable" (ground-mobility) vehicle that then transits on sidewalks and/or bicycle paths till it arrives to the residence/office drop-off points. This concept and associated platform or vehicle will be referred in this paper as MICHAEL (Multimodal Intra-City Hauling and Aerial-Effected Logistics) concept. It is suggested that the MICHAEL concept potentially results in a more community friendly "delivery drone" approach.
NeMO-Net - The Neural Multi-Modal Observation & Training Network for Global Coral Reef Assessment
In the past decade, coral reefs worldwide have experienced unprecedented stresses due to climate change, ocean acidification, and anthropomorphic pressures, instigating massive bleaching and die-off of these fragile and diverse ecosystems. Furthermore, remote sensing of these shallow marine habitats is hindered by ocean wave distortion, refraction and optical attenuation, leading invariably to data products that are often of low resolution and signal-to-noise (SNR) ratio. However, recent advances in UAV and Fluid Lensing technology have allowed us to capture multispectral 3D imagery of these systems at sub-cm scales from above the water surface, giving us an unprecedented view of their growth and decay. By combining spatial and spectral information from varying resolutions, we seek to augment and improve the classification accuracy of previously low-resolution datasets at large temporal scales.NeMO-Net, the first open-source deep convolutional neural network (CNN) and interactive learning and training software, currently being developed at NASA Ames, is aimed at assessing the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology. The latest iteration uses fully convolutional networks to segment and identify coral imagery taken by UAVs and satellites, including WorldView-2 and Sentinel. We present results taken from the Indian Ocean where classification accuracy has exceeded 91% for 24 geomorphological classes given ample training data. In addition, we utilize deep Laplacian Pyramid Super-Resolution Networks (LapSRN) to reconstruct high resolution information from low resolution imagery, trained from various UAV and satellite datasets. Finally, in the case of insufficient training data, we have developed an interactive online platform that allows users to easily segment and submit their classifications, which has been integrated with the current NeMO-Net workflow. Specifically, we present results from the Fiji islands in which preliminary user data has allowed for the accurate identification of 9 separate classes, despite issues such as cloud shadowing and spectral variation. The project is being supported by NASA's Earth Science Technology Office (ESTO) Advanced Information Systems Technology (AIST-16) Program.
Modal Testing of a Flexible Wing On a Dynamically Active Test Fixture Using the Fixed Base Correction Method
No abstract available
Passive Aeroelastic Tailored Wing Modal Test Using the Fixed Base Correction Method
No abstract available
Uncertainty Quantification of Inducer Eigenvalues using Conditional Assessment of Models and Modal Test of Simpler Systems
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Efficient Updating of Model Parameters Using Modal Coordinates
Model correlation methods based on iterative modification of physical model parameters have been used with frequent success. The cost and time to perform these methods is driven mostly by the need to recompute normal modes and parameter sensitivities from the full finite element model after each adjustment.
Modal Test and Analysis Correlation of Wind Tunnel Blades for the National Transonic Facility
NASA has a significant maintenance challenge with the aging wind tunnel infrastructure across the agency . Wind tunnel blades, such as the ones in the National Transonic Facility at NASA Langley Research Center, have been subjected to damage from impacts and fatigue. Accurate analytical models of these blades are necessary to either recertify replacement blades to be built or for redesign of these blades. In this paper an upgraded finite element model of these wind tunnel blades with the capability of representing damage is presented. An eigenvalue analysis of the structural model is performed, and the boundary conditions are adjusted to simulate the natural frequencies obtained by experimental testing of a set of twenty five blades in 1992. Additional numerical studies of the effect of delamination damage on the natural frequencies of the blade are conducted using the tuned finite element model.
Modal Test and Analysis Correlation of Wind Tunnel Blades for the National Transonic Facility
NASA has a significant maintenance challenge with the aging wind tunnel infrastructure across the agency . Wind tunnel blades, such as the ones in the National Transonic Facility at NASA Langley Research Center, have been subjected to damage from impacts and fatigue. Accurate analytical models of these blades are necessary to either recertify replacement blades to be built or for redesign of these blades. In this paper an upgraded finite element model of these wind tunnel blades with the capability of representing damage is presented. An eigenvalue analysis of the structural model is performed, and the boundary conditions are adjusted to simulate the natural frequencies obtained by experimental testing of a set of twenty five blades in 1992. Additional numerical studies of the effect of delamination damage on the natural frequencies of the blade are conducted using the tuned finite element model.
A Hybrid Tour-Based Model for Energy Analysis of Multi-Modal Intra-City Freight: A Case Study of Autonomous Electric Vehicles
With the emergence of cutting-edge transportation technologies, such as electric vehicles (EVs), connected and autonomous vehicles, and drones, the adoption of multimodal freight mobility has the potential to improve efficiency and save more energy. This paper proposes a hybrid tour-based model to evaluate the energy impact of multimodal intra-city freight movement for future scenarios. The model is built based on the traveling salesman problem model and clustering techniques. A case study using autonomous electric vehicles for package delivery is evaluated. The study was conducted using data analyzed from the Columbus, Ohio, metropolitan area. The initial results show that multimodal package delivery using autonomous EVs reduced total travel time by 45% and saved total energy use by 19%, but increased total vehicle miles traveled by 15% when compared with the baseline scenario.
Standardized Irradiation Testing and Multi-Modal Characterization for Advanced Nuclear Materials
Summary of activities from NMDQi/AMMT to be presented to the annual AMMT program integration meeting
Chitosan-Gated Magnetic-Responsive Nanocarrier for Dual-Modal Optical Imaging, Switchable Drug Release, and Synergistic Therapy
In this study, we present a multifunctional yet structurally simple nanocarrier that has a high drug loading capacity, releases drug in response to onset of an AC magnetic field, and can serve as a long-term imaging contrast agent and effectively kills cancer cells by synergistic action. This nanocarrier (HMMC-NC) has a spherical shell structure with a center cavity of 80 nm in diameter. The shell is comprised of two layers: an inner layer of magnetite that exhibits superparamagnetism and an outer layer of mesoporous carbon embedded with carbon dots that exhibit photoluminescence property. Thus in addition to being a drug carrier, HMMC-NC is also a contrast agent for bioimaging. The switchable drug release is enabled by the chitosan molecules attached on the nanocarrier as the switching material which turns on or off the drug release in response to the application or withdrawal of an AC magnetic field.
Probing Heterogeneous Degradation of Catalyst in PEM Fuel Cells under Realistic Automotive Conditions with Multi-Modal Techniques
The heterogeneity of polymer electrolyte fuel cell catalyst degradation is studied under varied relative humidity and types of feed gas. Accelerated stress tests (ASTs) are performed on four membrane electrode assemblies (MEAs) under wet and dry conditions in an air or nitrogen environment for 30 000 square voltage cycles. The largest electrochemically active area loss is observed for MEA under wet conditions in a nitrogen gas environment AST due to constant upper potential limit of 0.95 V and significant water content. The mean Pt particle size is larger for the ASTs under wet conditions compared to dry conditions, and the Pt particle size under land is generally larger than under the channel. Observations from ASTs in both conditions and gas environments indicate that water content promotes Pt particle size growth. ASTs under wet conditions and an air environment show the largest difference in Pt particle size growth for inlet versus outlet and channel versus land, which can be attributed to larger water content at outlet and under land compared to inlet and under channel. From X-ray fluorescence experiments Pt particle size increase is a local phenomenon as Pt loading remains relatively uniform across the MEA.