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A student design contest was held between four universities. The project was to improve the flexibility of the NASA extra-vehicular activities (EVA) glove with the internal pressure increased from 4 psi to 8 psi. The Kansas State University team used an experimental design methodology and an industrial management scheme. This approach succeeded in making Kansas State University the winner of the competition.
Realistic simulation of satellite communication systems and evaluation of satellite networking schemes require emulation of the systems's users. A laboratory model of a Ka-band satellite-switched time-division multiple-access (SS-TDMA) communication network, referred to as the System Integration, Test, and Evaluation (SITE) project, uses special bit-error-rate (BER) test sets to simulate the transmitting and receiving users of a communication network. The bit-error-rate test sets contain circuit boards that can be modified to create a variety of interfaces to satellite system ground terminals.
A computational simulation of reacting 2-D and 3-D flowfields in a model inlet section of a Pre-Mixed, Shock-Induced Combustion (PM/SIC) engine concept was performed. LARCK, a multi-dimensional Navier-Stokes code with finite-rate kinetics chemistry developed at NASA LaRC by J.A. White, was adapted for this simulation. The flow conditions in the simulation match those envisioned for the PM/SIC engine experiments currently planned at LaRC. The reacting flowfields were Mach 6.3 freestream air and Mach 2 hydrogen at various pressure and temperature conditions injected through a slot injector at the base of the inlet section. In the PM/SIC engine, fuel is injected at the inlet section upstream of the combustor, and reaction is initiated by the shock wave at the inlet which increases the gas temperature and pressure beyond the kinetic limits for reaction. Many challenges exist prior to establishing shock-controlled combustion as a practical engine concept. These challenges include fuel injection schemes that can provide proper fuel-air mixing without creating large losses in the inlet section, and control of the combustion process so that early ignition or combustion propagation through the inlet boundary layer does not occur. For this project, a parametrics study was carried out to model the fuel injection of hydrogen at different flow conditions. It was found that, as the fuel temperature and pressure were increased, the potential for pre-ignition was high at a short distance downstream of the slot injector. The next stage of this work will investigate injection techniques for enhancing mixing of fuel and air in a manner that prevents or reduces the potential for premature ignition observed numerically.
The primary effort of this research project was focused the development of analytical methods for the accurate prediction of structural acoustic noise and response. Of particular interest was the development of curved frame and shell spectral elements for the efficient computational of structural response and of schemes to match this to the surrounding fluid.
NASA currently projects ending the ISS mission in approximately 2016, due primarily to the expense of re-boost and re-supply. Lunar outposts are expected to be in place in the same timeframe. In support of these mission goals, a scheme to reuse ISS modules on the moon has been identified. These modules could function as pressurized volumes for human habitation in a lunar vacuum as they have done in low-earth orbit. The ISS hull is structurally capable of withstanding a lunar landing because there is no atmospheric turbulence or friction. A compelling reason to send ISS modules to the moon is their large mass; a large portion of the ISS would survive re-entry if allowed to de-orbit to Earth. ISS debris could pose a serious risk to people or structures on Earth unless a controlled re-entry is performed. If a propulsive unit is devised to be attached to the ISS and control re-entry, a propulsion system could be used to propel the modules to the moon and land them there. ISS modules on the lunar surface would not require re-boost. Radiation protection can be attained by burying the module in lunar regolith. Power and a heat removal system would be required for the lunar modules which would need little support structure other than the lunar surface. With planetary mass surrounding the module, heat flux may be controlled by conductance. The remaining requirement is the re-supply of life-support expendables. There are raw materials on the moon to supplement these vital resources. The lunar maria is known to contain approximately 40% oxygen by mass in inorganic mineral compounds. Chemical conversion of moon rocks to release gaseous oxygen is known science. Recycling and cleaning of air and water are currently planned to be accomplished with ISS Environmental Control & Life Support Systems (ECLSS). By developing a Propulsion and Landing Module (PLM) to dock to the Common Berthing Mechanism (CBM), several identical PLMs could be produced to rescue and transfer the ISS modules to the lunar surface, one by one. The propulsion does not need to be as swift as Apollo, nor would the modules need to be manned during transportation to the moon. The trajectory from low-Earth to lunar orbit would avoid or quickly pass through the Van Allen belts to minimize radiation exposure to electronics onboard. A landing technology similar to Apollo's could be utilized to land an ISS module on the moon. Since the mission will be unmanned, system redundancy could be minimized to keep the cost down. If the mission failed and a module crashed landed on the moon, the risk of debris landing on Earth would be avoided and the raw materials could be used in future lunar missions.
Microwave-based retrievals of snow parameters from satellite observations have a long heritage and have so far been generated primarily by regression-based empirical "inversion" methods based on snapshots in time. Direct assimilation of microwave radiance into physical land surface models can be used to avoid errors associated with such retrieval/inversion methods, instead utilizing more straightforward forward models and temporal information. This approach has been used for years for atmospheric parameters by the operational weather forecasting community with great success. Recent developments in forward radiative transfer modeling, physical land surface modeling, and land data assimilation are converging to allow the assembly of an integrated framework for snow/cold lands modeling and radiance assimilation. The objective of the Goddard snow radiance assimilation project is to develop such a framework and explore its capabilities. The key elements of this framework include: a forward radiative transfer model (FRTM) for snow, a snowpack physical model, a land surface water/energy cycle model, and a data assimilation scheme. In fact, multiple models are available for each element enabling optimization to match the needs of a particular study. Together these form a modular and flexible framework for self-consistent, physically-based remote sensing and water/energy cycle studies. In this paper we will describe the elements and the integration plan. All modules will operate within the framework of the Land Information System (LIS), a land surface modeling framework with data assimilation capabilities running on a parallel-node computing cluster. Capabilities for assimilation of snow retrieval products are already under development for LIS. We will describe plans to add radiance-based assimilation capabilities. Plans for validation activities using field measurements will also be discussed.
The Global Solar Insolation Project (GSIP) is an operational physical model from the National Oceanic and Atmospheric Administration (NOAA) that computes global horizontal radiation (GHI) using the visible and infrared channel measurements from geostationary operational environmental satellites (GOES). GSIP uses a two-stage scheme that retrieves cloud properties and uses those properties in the Satellite Algorithm for Surface Radiation Budget (SASRAB) model to calculate surface radiation. The National Renewable Energy Laboratory, University of Wisconsin, and NOAA have recently collaborated to adapt GSIP to create a high-temporal and spatial resolution data set. The data sets are currently being incorporated into the widely used National Solar Radiation Data Base.
Industrial processes drive the exchange of materials, energy, and currency throughout the economy. These processes are powered by electricity and direct combustion, with variation in their operation even within the same industry. This heterogeneity makes it difficult for large models, including the National Energy Modeling System (US), to project their energy use while remaining tractable. Decarbonization and ensuing changes to the energy system require changes to industrial processes while offering opportunities for process innovation, but the extent and nature of changes are difficult to model with current classification schemes and corresponding data. The North American Industrial Classification (NAICS) is an economic taxonomy of industries, but its categories are less meaningful from an energy and material flow perspective. For example, a facility that makes steel from iron ore in a blast furnace/basic oxygen furnace is categorized under the same NAICS code as a facility that makes steel from scrap in an electric arc furnace despite the scale, use of recycled scrap versus iron ore, and energy use differences in the two facility types. Exploratory analysis is performed on a large dataset used for plant-level energy assessment in order to detect clusters that can aid in better modeling of industry for energy analysis in an evolving system with breakthrough technologies.
The advent of unprecedentedly scalable yet energy hungry Exascale supercomputers poses a major challenge in sustaining a high performance-per-watt ratio. With I/O management acquiring a crucial role in supporting scientific simulations, various I/O management approaches have been proposed to achieve high performance and scalability. But, the details of how these approaches affect energy consumption have not been studied yet. Therefore, this paper aims to explore how much energy a supercomputer consumes while running scientific simulations when adopting various I/O management approaches. In particular, we closely examine three radically different I/O schemes including time partitioning, dedicated cores, and dedicated nodes. To accomplish this, we implement the three approaches within the Damaris I/O middleware and perform extensive experiments with one of the target HPC applications of the Blue Waters sustained-petaflop supercomputer project: the CM1 atmospheric model. Our experimental results obtained on the French Grid'5000 platform highlight the differences among these three approaches and illustrate in which way various configurations of the application and of the system can impact performance and energy consumption. Moreover, we propose and validate a mathematical model that estimates the energy consumption of a HPC simulation under different I/O approaches. This proposed model gives hints to pre-select the most energy-efficient I/O approach for a particular simulation on a particular HPC system and therefore provides a step towards energy-efficient HPC simulations in Exascale systems. To the best of our knowledge, our work provides the first in-depth look into the energy-performance tradeoffs of I/O management approaches.
We introduce new methods for integrating nonlinear differential equations on low-rank manifolds. These methods rely on interpolatory projections onto the tangent space, enabling low-rank time integration of vector fields that can be evaluated entry-wise. A key advantage of our approach is that it does not require the vector field to exhibit low-rank structure, thereby overcoming significant limitations of traditional dynamical low-rank methods based on orthogonal projection. To construct the interpolatory projectors, we develop a sparse tensor sampling algorithm based on the discrete empirical interpolation method (DEIM) that parameterizes tensor train manifolds and their tangent spaces with cross interpolation. Using these projectors, we propose two time integration schemes on low-rank tensor train manifolds. The first scheme integrates the solution at selected interpolation indices and constructs the solution with cross interpolation. The second scheme generalizes the well-known orthogonal projector-splitting integrator to interpolatory projectors. We demonstrate the proposed methods with applications to several tensor differential equations arising from the discretization of partial differential equations.
When modeling sparsely observed multivariate data, strong prior information elicited from experts can be used to bolster predictive accuracy and counteract sampling bias. Similarly, modeling autocorrelation in space can help make use of co-occurrence patterns present in many types of spatial data. To make use of both expert prior information and spatial structure, we propose a novel graphical model for a spatial Bayesian network developed specifically to address challenges in inferring the attributes of buildings from geographically sparse observational data. This model is implemented as the sum of a spatial multivariate Gaussian random field and a tabular conditional probability function in real-valued space prior to projection onto the probability simplex. This modeling form is especially suitable for the usage of prior information in the form of sets of atomic rules obtained from experts. To perform inference with missing data, we implement a Markov chain Monte Carlo scheme composed of alternating steps of Gibbs sampling of missing entries and Hamiltonian Monte Carlo for model parameters. A case study in building attribution is presented to highlight the advantages and limitations of this approach.
The collection of Earth system models available in the archive of phase 5 of CMIP (CMIP5) represents, at least to some degree, a sample of uncertainty of future climate evolution. The presence of duplicated code as well as shared forcing and validation data in the multiple models in the archive raises at least three potential problems: biases in the mean and variance, the overestimation of sample size, and the potential for spurious correlations to emerge in the archive because of model replication. Analytical evidence is presented to demonstrate that the distribution of models in the CMIP5 archive is not consistent with a random sample, and a weighting scheme is proposed to reduce some aspects of model codependency in the ensemble. A method is proposed for selecting diverse and skillful subsets of models in the archive, which could be used for impact studies in cases where physically consistent joint projections of multiple variables (and their temporal and spatial characteristics) are required.
We present a high-performance coupled electrodynamics–micromagnetics solver for full physical modeling of signals in microelectronic circuitry. The overall strategy couples a finite-difference time-domain approach for Maxwell’s equations to a magnetization model described by the Landau–Lifshitz–Gilbert equation. The algorithm is implemented in the Exascale Computing Project software framework, AMReX, which provides effective scalability on manycore and GPU-based supercomputing architectures. Furthermore, the code leverages ongoing developments of the Exascale Application Code, WarpX, which is primarily being developed for plasma wakefield accelerator modeling. Our temporal coupling scheme provides second-order accuracy in space and time by combining the integration steps for the magnetic field and magnetization into an iterative sub-step that includes a trapezoidal temporal discretization for the magnetization. The performance of the algorithm is demonstrated by the excellent scaling results on NERSC multicore and GPU systems, with a significant (59×) speedup on the GPU using a node-by-node comparison. We demonstrate the utility of our code by performing simulations of an electromagnetic waveguide and a magnetically tunable filter.
This dataset contains measured ecosystem data from four Free Air CO2 Enrichment (FACE) experiments–Duke, Oak Ridge (ORNL), and Rhinelander -- and one Open Top Chamber (OTC) experiment -- Kennedy Space Center (KSCO). The sites were located in the United States and contain data from 1996-2009. These sites were the study sites of the FACE Model Data Synthesis (FACE-MDS) project phase 2. The file naming convention can be found in the file 'facemds-file-table-sitedata.xml' and information about variable naming convention can be found in the file 'facemds-standard-name-table-modvars.xml'. We followed the ALMA v3 convention for meteorological variables and developed a hierarchical naming scheme for ecosystem variables. Additional info can be found in the protocols in the accompanying meteorological dataset (Walker et al. 2018: doi:10.15485/1480328). We replaced the original naming convention mentioned in the protocol with the one described in 'facemds-standard-name-table-modvars.xml'. The outputs of the FACE-MDS phase 2 are in Walker et al (2018: doi:10.15485/1480327). The dataset contains 18 data files that are available in comma-separate (*.csv), and 18 R Data Serialization (*.rds) format. 2 XML (*.xml) companion files and additional metadata are provided: 2 data dictionaries and a file-level metadata file in comma-separate (.csv) format and a user guide in PDF (*.pdf) format. This dataset was updated on 2019-06-28 to fix daily files at Duke and ORNL were incorrectly labelled and were standard error files instead of plot level data. Now corrected and all three (plot, mean, standard error) daily data files for both sites have been added. This dataset was updated on 2026-06-08 to add a user guide, data dictionary file, and a file-level metadata file. DUKE_ax_v2.csv was added to match the no data value format of other files in this dataset. DUKE_ax.csv is maintained as a data file. No previously released data values were changed.
The magnitude and spatial dependence of neutral density in magnetic confinement fusion experiments is a key physical parameter, particularly in the plasma edge. Modeling codes require precise measurements of the neutral density to calculate charge-exchange power losses and drag forces on rotating plasmas. However, direct measurements of the neutral density are problematic. In this work, we proposed to construct a laser-based diagnostic capable of providing spatially resolved measurements of the neutral density in the edge of plasma in the DIII-D tokamak. The diagnostic concept is based on two-photon absorption laser induced fluorescence (TALIF). By injecting two beams of 205 nm light (co or counter propagating), ground state hydrogen (or deuterium or tritium) can be excited from the n = 1 level to the n = 3 level at the location where the two beams intersect. Individually, the beams experience no absorption, and therefore have no difficulty penetrating even dense plasmas. After excitation, a fraction of the hydrogen atoms decay from the n = 3 level to the n = 2 level and emit photons at 656 nm (the H α line). Calculations based on the results of previous TALIF experiments in magnetic fusion devices indicated that a laser pulse energy of approximately 3 mJ delivered in 5 ns would provide sufficient signal-to-noise for detection of the fluorescence. In collaboration with the DIII-D engineering staff and experts in plasma edge diagnostics for DIII-D from Oak Ridge National Laboratory (ORNL), WVU researchers designed a TALIF system capable of providing spatially resolved measurements of neutral deuterium densities in the DIII-D edge plasma. The laser systems were specified, purchased, and assembled at WVU. The TALIF system was tested on a low-power hydrogen discharge at WVU and the plan was to move the instrument to DIII-D for installation in collaboration with ORNL researchers. After budget cuts at DIII-D, the DIII-D facility declined to support installation on their tokamak. Instead, after a no-cost extension, the apparatus was moved to the University of Washington-Seattle and successfully tested on the HIT-SI3 spheromak experiment. As a result of this project, TALIF measurements of the absolutely calibrated neutral density hydrogen and deuterium were obtained in a helicon source and in a spheromak, designs were developed for installation of a TALIF system on a tokamak, and a new, xenon-based calibration scheme was proposed and demonstrated. The xenon-calibration scheme eliminates significant problems that were identified with the standard krypton calibration scheme.
Conventional hydrogen compressors often contribute over half of the cost of hydrogen stations, have poor reliability, and have insufficient flow rates for a mature FCEV market. Fatigue associated with their moving parts including cracking of diaphragms and failure of seal leads to failure in conventional compressors, which is exacerbated by the repeated starts and stops expected at fueling stations. Furthermore, the conventional lubrication of these compressors with oil is generally unacceptable at fueling stations due to potential fuel contamination. Metal hydride (MH) technology offers a very good alternative to both conventional (mechanical) and newly developed (electrochemical, ionic liquid pistons) methods of hydrogen compression. Advantages of MH compression include simplicity in design and operation, absence of moving parts, compactness, safety and reliability, and the possibility to utilize waste industrial heat to power the compressor. Beyond conventional H2 supplies of pipelines or tanker trucks, another attractive scenario is the on-site generating, pressuring and delivering pure H 2 at pressure (≥ 875 bar) for refueling vehicles at electrolysis, wind, or solar generating production facilities in distributed locations that are too remote or widely distributed for cost effective bulk transport. MH hydrogen compression utilizes a reversible heat-driven interaction of a hydride-forming metal alloy with hydrogen gas to form the MH phase and is a promising process for hydrogen energy applications [1,2]. To deliver hydrogen continuously, each stage of the compressor must consist of multiple MH beds with synchronized hydrogenation & dehydrogenation cycles. Multistage pressurization allows achievement of greater compression ratios using reduced temperature swings compared to single stage compressors. The objectives of this project are to investigate and demonstrate on a laboratory scale a two-stage MH hydrogen (H 2 ) gas compressor with a feed pressure of >50 bar and a delivery pressure ≥ 875 bar of high purity H 2 gas using the scheme shown in Figure 1. Progress to date includes the selection of two candidate metal hydrides for each compressor stage, supplier engagement and synthesis of small samples, and the beginning of in-depth characterization of their thermodynamics, kinetics, and hydrogen capacities for optimal performance with respect to energy requirements and efficiency. Additionally, bed design trade studies are underway and will be finalized in FY18. Subsequently, the prototype two-stage compressor will be fabricated, assembled and experimentally evaluated in FY19.
Understanding stress distributions in solid materials is complicated by the fact that most materials are polycrystalline in nature, with each crystal having an elastically anisotropic reaction to force. This study is to gain a better understanding on how external forces placed on a polycrystal are related to internal reactions within and between the grains. The hypothesis is that the stress distribution in porous to fully dense materials are self-organized based on strong contacts between and within the individual grains created by force chains. Force chains, commonly known in loaded granular materials, and could be the phenomenon that connect micro to macro deformation. Scale bridging measurements conducted through Raman spectroscopy, Atomic Force Microscopy, and Digital Image Correlation will be used to create stress maps, modulus maps, and elastic strain maps across a variety of geological and pharmaceutical polycrystals. When possible, the resulting maps will be compared to current homogenization schemes and a full field models. Finite element modeling will be used to assess whether the patterning seen in the experimental map is a reasonable approximation based on the orientation data of the samples used. A minimum of three publications is projected to be accomplished focusing each on a different method to experimentally test and analyze stress distributions.
The increasing development of small microprocessor systems has allowed the use of more advanced software in the area of control systems. This paper discusses the development of software for small Space Shuttle Getaway Special Project payloads using payload G285 as a case example. The development process behind a space related software package (as in any software package) is a major factor. The design process for G285 is discussed in some detail along with the general scheme behind data acquisition and thermal environmental control for a space related payload. Additionally, key concepts in a software system concern the implementation of redundant systems, error detection, and error response. All of these factors are discussed.