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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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The View Shed library is a collection of Umbra modules that are used to calculate areas of visual coverage (view sheds). It maps high and low visibility areas and calculates sensor (camera placement for maximum coverage and performance. This assertion includes a managed C++ wrapper code (ViewShedWrapper) to enable C# applications, such as OpShed, to incorporate this library.
A Feature and Pose Constrained Extended Kalman Filter (FPC-EKF) is developed for highly dynamic computationally constrained micro aerial vehicles. Vehicle localization is achieved using only a low performance inertial measurement unit and a single camera. The FPC-EKF framework augments the vehicle's state with both previous vehicle poses and critical environmental features, including vertical edges. This filter framework efficiently incorporates measurements from hundreds of opportunistic visual features to constrain the motion estimate, while allowing navigating and sustained tracking with respect to a few persistent features. In addition, vertical features in the environment are opportunistically used to provide global attitude references. Accurate pose estimation is demonstrated on a sequence including fast traversing, where visual features enter and exit the field-of-view quickly, as well as hover and ingress maneuvers where drift free navigation is achieved with respect to the environment.
The performance and degree of efficiency of industrial transformers are directly influenced by the magnetic properties of high-permeability steel laminations (HPSLs). Industrial transformer cores are built of stacks of single HPSLs. While the insulating coating on each HPSL reduces eddy-current losses in the transformer core, the coating also induces favorable inter-granular tensile stresses that significantly influence the underlying magnetic domain structure. Here, we show that the neutron dark-field image can be used to analyze the influence of the coating on the volume and supplementary surface magnetic domain structures. To visualize the stress effect of the coating on the bulk domain formation, we used an uncoated HPSL and stepwise increased the applied external tensile stress up to 20 MPa. We imaged the domain configuration of the intermediate stress states and were able to reproduce the original domain structure of the coated state. Furthermore, we were able to visualize how the applied stresses lead to a refinement of the volume domain structure and the suppression and reoccurrence of supplementary domains.
High Quality Mobile Virtual Reality (VR) is what the incoming graphics technology era demands: users around the world, regardless of their hardware and network conditions, can all enjoy the immersive virtual experience. However, the state-of-the-art software-based mobile VR designs cannot fully satisfy the realtime performance requirements due to the highly interactive nature of user's actions and complex environmental constraints during VR execution. Inspired by the unique human visual system effects and the strong correlation between VR motion features and realtime hardware-level information, we propose Q-VR, a novel dynamic collaborative rendering solution via software-hardware co-design for enabling future low-latency high-quality mobile VR. At software-level, Q-VR provides flexible high-level tuning interface to reduce network latency while maintaining user perception. At hardware-level, Q-VR accommodates a wide spectrum of hardware and network conditions across users by effectively leveraging the computing capability of the increasingly powerful VR hardware. Extensive evaluation on real-world games demonstrates that Q-VR can achieve an average end-to-end performance speedup of 3.4x (up to 6.7x) over the traditional local rendering design in commercial VR devices, and a 4.1x frame rate improvement over the state-of-the-art static collaborative rendering.
X-ray Magnetic Circular Dichroism (XMCD) microscopy at liquid nitrogen temperature has been performed on bilayers of high-T{sub c} superconducting YBCO (YBa{sub 2}Cu{sub 3}O{sub 7-δ}) and soft-magnetic Co{sub 40}Fe{sub 40}B{sub 20}. This should allow us to map the magnetic flux density distribution in the current-carrying state of the superconductor with high spatial resolution. For that purpose the UHV scanning X-ray microscope MAXYMUS has been upgraded by a MMR Micro Miniature Joule-Thompson cryostat capable of temperatures between 75 K and 580 K. Resulting XMCD images of the magnetic flux density in the superconductor with a field of view ranging from millimeters to micrometers are presented. The microscope’s unique combination of total electron yield (TEY) measurements together with low temperatures offers novel possibilities concerning the current transport in superconductors on small length scales.
A high-speed anthropometric three dimensional measurement system using the Selcom Selspot motion tracking instrument for visual data acquisition is discussed. A three-dimensional scanning system was created which collects video, audio, and performance data on a single standard video cassette recorder. Recording rates of 1 megabit per second for periods of up to two hours are possible with the system design. A high-speed off-the-shelf motion analysis system for collecting optical information as used. The video recording adapter (VRA) is interfaced to the Selspot data acquisition system.
Time-resolved characterization of an Ar-Ti high-power impulse magnetron sputtering discharge has been performed. This paper deals with two-dimensional density mapping in the discharge volume obtained by laser-induced fluorescence imaging. The time-resolved density evolution of Ti neutrals, singly ionized Ti atoms (Ti{sup +}), and Ar metastable atoms (Ar{sup met}) in the area above the sputtered cathode is mapped for the first time in this type of discharges. The energetic characteristics of the discharge species are additionally studied by Doppler-shift laser-induced fluorescence imaging. The questions related to the propagation of both the neutral and ionized discharge particles, as well as to their spatial density distributions, are discussed.
Time-resolved characterization of an Ar-Ti high-power impulse magnetron sputtering discharge has been performed. The present, second, paper of the study is related to the discharge characterization in terms of the absolute density of species using resonant absorption spectroscopy. The results on the time-resolved density evolution of the neutral and singly-ionized Ti ground state atoms as well as the metastable Ti and Ar atoms during the discharge on- and off-time are presented. Among the others, the questions related to the inversion of population of the Ti energy sublevels, as well as to re-normalization of the two-dimensional density maps in terms of the absolute density of species, are stressed.
At a recent press conference, NASA Administrator Dan Goldin encouraged NASA Ames Research Center to take a lead role in promoting research and development of advanced, high-performance computer technology, including nanotechnology. Manufacturers of leading-edge microprocessors currently perform large-scale simulations in the design and verification of semiconductor devices and microprocessors. Recently, the need for this intensive simulation and modeling analysis has greatly increased, due in part to the ever-increasing complexity of these devices, as well as the lessons of experiences such as the Pentium fiasco. Simulation, modeling, testing, and validation will be even more important for designing molecular computers because of the complex specification of millions of atoms, thousands of assembly steps, as well as the simulation and modeling needed to ensure reliable, robust and efficient fabrication of the molecular devices. The software for this capacity does not exist today, but it can be extrapolated from the software currently used in molecular modeling for other applications: semi-empirical methods, ab initio methods, self-consistent field methods, Hartree-Fock methods, molecular mechanics; and simulation methods for diamondoid structures. In as much as it seems clear that the application of such methods in nanotechnology will require powerful, highly powerful systems, this talk will discuss techniques and issues for performing these types of computations on parallel systems. We will describe system design issues (memory, I/O, mass storage, operating system requirements, special user interface issues, interconnects, bandwidths, and programming languages) involved in parallel methods for scalable classical, semiclassical, quantum, molecular mechanics, and continuum models; molecular nanotechnology computer-aided designs (NanoCAD) techniques; visualization using virtual reality techniques of structural models and assembly sequences; software required to control mini robotic manipulators for positional control; scalable numerical algorithms for reliability, verifications and testability. There appears no fundamental obstacle to simulating molecular compilers and molecular computers on high performance parallel computers, just as the Boeing 777 was simulated on a computer before manufacturing it.
This paper presents experimental data on the effect of carbon nano-fiber (CNF) dispersion on mechanical behavior, workability, and permeability of ultra-high-performance concrete containing CNF (UHPC-CNF). The addition of CNFs in concrete has been shown to provide improved performance. However, an inhomogeneous distribution of CNFs in the cement matrix can result in no impact or decreased mechanical performance. Due to the van der Waal's forces and hydrophobic surface properties of the CNFs, good dispersion in mix fluids and cement paste is challenging. Experimental studies of UHPC-CNF with different dispersion methods are provided. Further mixing with optimized UHPC paste allowed for the investigation of the optimal dosage of CNFs, impact on porosity, compressive strength, flexural strength, hydration rate, and slump. Scanning electron microscopy (SEM) analysis visually revealed the effect of dispersion. Our results indicate that shear mixing and subsequent ultrasonic dispersion with chemical surfactants can provide a well-dispersion liquid admixture of CNFs resulting in high mechanical performance of UHPC-CNFs composites. The water permeability and chloride resistance of optimized UHPC-CNFs composites were further evaluated with the wicking test and ponding test to reveal improved performance for these properties as well.
In lithium-sulfur (Li-S) chemistry, the electrically/ionically insulating nature of sulfur and Li 2 S leads to sluggish electron/ion transfer kinetics for sulfur species conversion. Sulfur and Li 2 S are recognized as solid at room temperature, and solid-liquid phase transitions are the limiting steps in Li-S batteries. Here, we visualize the distinct sulfur growth behaviors on Al, carbon, Ni current collectors and demonstrate that (i) liquid sulfur generated on Ni provides higher reversible capacity, faster kinetics, and better cycling life compared to solid sulfur; and (ii) Ni facilitates the phase transition (e.g., Li 2 S decomposition). Accordingly, light-weight, 3D Ni-based current collector is designed to control the deposition and catalytic conversion of sulfur species toward high-performance Li-S batteries. This work provides insights on the critical role of the current collector in determining the physical state of sulfur and elucidates the correlation between sulfur state and battery performance, which will advance electrode designs in high-energy Li-S batteries.
Accurate net-load forecasting is vital for energy planning, aiding decisions on trade and load distribution. However, assessing the performance of forecasting models across diverse input variables, like temperature and humidity, remains challenging, particularly for eliciting a high degree of trust in the model outcomes. In this context, there is a growing need for data-driven technological interventions to aid scientists in comprehending how models react to both noisy and clean input variables, thus shedding light on complex behaviors and fostering confidence in the outcomes. In this paper, we present Forte, a visual analytics-based application to explore deep probabilistic net-load forecasting models across various input variables and understand the error rates for different scenarios. With carefully designed visual interventions, this web-based interface empowers scientists to derive insights about model performance by simulating diverse scenarios, facilitating an informed decision-making process. We discuss observations made using Forte and demonstrate the effectiveness of visualization techniques to provide valuable insights into the correlation between weather inputs and net-load forecasts, ultimately advancing grid capabilities by improving trust in forecasting models.
Here, we discuss the development of an agent-based modelling software development kit, and the implementation and validation of a model using it that integrates dynamic simulation of travel demand, network supply and network operations. A description is given of the core utilities in the kit: a parallel discrete event engine, interprocess exchange engine, and memory allocator, as well as a number of ancillary utilities: visualization library, database IO library, and scenario manager. The overall framework emphasizes the design goals of: generality, code agility, and high performance. This framework allows the modeling of several aspects of transportation system that are typically done with separate stand-alone software applications, in a high-performance and extensible manner. The issue of integrating such models as dynamic traffic assignment and disaggregate demand models has been a long standing issue for transportation modelers. The integrated approach shows a possible way to resolve this difficulty. The simulation model built from the POLARIS framework is a single, shared-memory process for handling all aspects of the integrated urban simulation. The resulting gains in computational efficiency and performance allow planning models to be extended to include previously separate aspects of the urban system, enhancing the utility of such models from the planning perspective. Lastly, initial tests with case studies involving traffic management center impacts on various network events such as accidents, congestion and weather events, show the potential of the system.
Uncertainty visualization plays a critical role in transforming ensemble simulation data into actionable insights by effectively communicating various dimensions of uncertainty within a system. The emergence of artificial intelligence-driven surrogate models trained on multirun ensemble data offers a transformative opportunity to replace computationally intensive simulations with fast estimates, enabling users to explore data spaces with unprecedented depth and interactivity. However, integrating ensemble data and surrogate models into decision-making workflows and tools introduces novel challenges for uncertainty visualization. These include reconciling and clearly communicating the unique uncertainties associated with ensembles and their surrogate model estimates, and leveraging these approximations to inform actionable decisions. This work explores these challenges in the context of high-dimensional data visualization, bridging discrete datasets with their continuous representations and addressing the complexities of systems that support iterative navigation between input and output spaces. We evaluate the role of uncertainty visualization in fostering intuitive, actionable interactions and identify critical hurdles in advancing this frontier of computational simulation.
Visualizing the uncertainty of ensemble simulations is challenging due to the large size and multivariate and temporal features of en-semble data sets. One popular approach to studying the uncertainty of ensembles is analyzing the positional uncertainty of the level sets. Probabilistic marching cubes is a technique that performs Monte Carlo sampling of multivariate Gaussian noise distributions for positional uncertainty visualization of level sets. However, the technique suffers from high computational time, making interactive visualization and analysis impossible to achieve. This paper introduces a deep-learning-based approach to learning the level-set uncertainty for two-dimensional ensemble data with a multivariate Gaussian noise assumption. We train the model using the first few time steps from time-varying ensemble data in our workflow. We demonstrate that our trained model accurately infers uncertainty in level sets for new time steps and is up to 170X faster than that of the original probabilistic model with serial computation and 10X faster than that of the original parallel computation.
Peripheral vision displays for presenting dynamic tracking information while landing high-speed aircraft, rendezvousing spacecraft, or performing other difficult control tasks
A comprehensive analytical, numerical and experimental study of convective flow in multilayer immiscible liquids has been performed. Studies include transparent high Prandtl number of liquid as well as opaque low Prandtl metallic melts. A new radioscopic flow visualization has been developed for the latter studies.
Experiments on characterization of thin liquid films flowing over stationary and rotating disk surfaces are described. The thin liquid film was created by introducing deionized water from a flow collar at the center of an aluminum disk with a known initial film thickness and uniform radial velocity. Radial film thickness distribution was measured using a non-intrusive laser light interface reflection technique that enabled the measurement of the instantaneous film thickness over a finite segment of the disk. Experiments were performed for a range of flow rates between 3.01pm and 15.01pm, corresponding to Reynolds numbers based on the liquid inlet gap height and velocity between 238 and 1,188. The angular speed of the disk was varied from 0 rpm to 300 rpm. When the disk was stationary, a circular hydraulic jump was present in the liquid film. The liquid-film thickness in the subcritical region (down-stream of the hydraulic jump) was an order of magnitude greater than that in the supercritical region (upstream of the hydraulic jump) which was of the order of 0.3 mm. As the Reynolds number increased, the hydraulic jump migrated toward the edge of the disk. In the case of rotation, the liquid-film thickness exhibited a maximum on the disk surface. The liquid-film inertia and friction influenced the inner region where the film thickness progressively increased. The outer region where the film thickness decreased was primarily affected by the centrifugal forces. A flow visualization study of the thin film was also performed to determine the characteristics of the waves on the free surface. At high rotational speeds, spiral waves were observed on the liquid film. It was also determined that the angle of the waves which form on the liquid surface was a function of the ratio of local radial to tangential velocity.