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DOE OSTI2014

U.S. Department of Energy Reference Model Program RM2: Experimental Results

The Reference Model Project (RMP), sponsored by the U.S. Department of Energy’s (DOE) Wind and Water Power Technologies Program within the Office of Energy Efficiency & Renewable Energy (EERE), aims at expediting industry growth and efficiency by providing non-proprietary Reference Models (RM) of MHK technology designs as study objects for open-source research and development (Neary et al. 2014a,b). As part of this program, MHK turbine models were tested in a large open channel facility at the University of Minnesota’s St. Anthony Falls Laboratory (UMN - SAFL) . Reference Model 2 (RM2) is a 1:15 geometric scale dual - rotor cross flow vertical axis device with counter - rotating rotors, each with a rotor diameter d T = 0.43m and rotor height, h T = 0.323 m. RM2 is a river turbine designed for a site modeled after a reach in the lower Mississippi River near Baton Rouge, Louisiana (Barone et al. 2014) . Precise blade angular position and torque measurements were synchronized with three acoustic Doppler velocimeters (ADV) aligned with each rotor and the midpoint for RM2 . Flow conditions for each case were controlled such that depth, h = 1m, and volumetric flow rate, Q w = 2. 35m 3 s -1 , resulting in a hub height velocity of approximately U hub = 1. 2 ms -1 and blade chord length Reynolds numbers of Re c = 6 .1x10 4 . Vertical velocity profiles collected in the wake of each device from 1 to 10 rotor diameters are used to estimate the velocity recovery and turbulent characteristics in the wake, as well as the interaction of the counter-rotating rotor wakes. The development of this high resolution laboratory investigation provides a robust dataset that enables assessing computational fluid dynamics (CFD) models and their ability to accurately simulate turbulent inflow environments, device performance metrics, and to reproduce wake velocity deficit, recovery and higher order turbulent statistics.

13 HYDRO ENERGY↗

NASA NTRS2010

Ares I-X: First Step in a New Era of Exploration

Since 2005, NASA's Constellation Program has been designing, building, and testing the next generation of launch and space vehicles to carry humans beyond low-Earth orbit (LEO). On October 28, 2009, the Ares Projects successfully launched the first suborbital development flight test of the Ares I crew launch vehicle, Ares I-X, from Kennedy Space Center (KSC). Although the final Constellation Program architecture is under review, data and lessons obtained from Ares I-X can be applied to any launch vehicle. This presentation will discuss the mission background and future impacts of the flight. Ares I is designed to carry up to four astronauts to the International Space Station (ISS). It also can be used with the Ares V cargo launch vehicle for a variety of missions beyond LEO. The Ares I-X development flight test was conceived in 2006 to acquire early engineering, operations, and environment data during liftoff, ascent, and first stage recovery. Engineers are using the test flight data to improve the Ares I design before its critical design review the final review before manufacturing of the flight vehicle begins. The Ares I-X flight test vehicle incorporated a mix of flight and mockup hardware, reflecting a similar length and mass to the operational vehicle. It was powered by a four-segment SRB from the Space Shuttle inventory, and was modified to include a fifth, spacer segment that made the booster approximately the same size as the five-segment SRB. The Ares I-X flight closely approximated flight conditions the Ares I will experience through Mach 4.5, performing a first stage separation at an altitude of 125,000 feet and reaching a maximum dynamic pressure ("Max Q") of approximately 850 pounds per square foot. The Ares I-X Mission Management Office (MMO) was organized functionally to address all the major test elements, including: first stage, avionics, and roll control (Marshall Space Flight Center); upper stage simulator (Glenn Research Center); crew module/launch abort system simulator (Langley Research Center); and ground systems and operations (KSC). Interfaces between vehicle elements and vehicle-ground elements, as well as environment analyses were performed by a systems engineering and integration team at Langley. Experience and lessons learned from these integrated product teams area are already being integrated into the Ares Projects to support the next generation of exploration launch vehicles.

Davis, Stephan R.↗

DOE OSTI2012

Gluons and the Quark Sea at High Energies: Distributions, Polarization, Tomography

This report on the science case for an Electron-Ion Collider (EIC) is the result of a ten-week program at the Institute for Nuclear Theory (INT) in Seattle (from September 13-November 19, 2010), motivated by the need to develop a strong case for the continued study of the QCD description of hadron structure in the coming decades. Hadron structure in the valence quark region will be studied extensively with the Jefferson Lab 12 GeV science program, the subject of an INT program the previous year. The focus of the INT program was on understanding the role of gluons and sea quarks, the important dynamical degrees of freedom describing hadron structure at high energies. Experimentally, the most direct and precise way to access the dynamical structure of hadrons and nuclei at high energies is with a high luminosity lepton probe in collider mode. An EIC with optimized detectors offers enormous potential as the next generation accelerator to address many of the most important, open questions about the fundamental structure of matter. The goal of the INT program, as captured in the writeups in this report, was to articulate these questions and to identify golden experiments that have the greatest potential to provide definitive answers to these questions. At resolution scales where quarks and gluons become manifest as degrees of freedom, the structure of the nucleon and of nuclei is intimately connected with unique features of QCD dynamics, such as confinement and the self-coupling of gluons. Information on hadron sub-structure in DIS is obtained in the form of 'snapshots' by the 'lepton microscope' of the dynamical many-body hadron system, over different momentum resolutions and energy scales. These femtoscopic snapshots, at the simplest level, provide distribution functions which are extracted over the largest accessible kinematic range to assemble fundamental dynamical insight into hadron and nuclear sub-structure. For the proton, the EIC would be the brightest femtoscope scale lepton-collider ever, exceeding the intensity of the HERA collider a thousand fold. HERA, with its center-of-mass (CM) energy of 320 GeV, was built to search for quark substructure. An EIC, with its scientific focus on studying QCD in the regime where the sea quarks and gluons dominate, would have a lower CM energy. In a staged EIC design, the CM energy will range from 50-70 GeV in stage I to approximately twice that for the full design. In addition to being the first lepton collider exploring the structure of polarized protons, an EIC will also be the first electron-nucleus collider, probing the gluon and sea quark structure of nuclei for the first time. Following the same structure as the scientific discussions at the INT, this report is organized around the following four major themes: (1) The spin and flavor structure of the proton; (2) Three dimensional structure of nucleons and nuclei in momentum and configuration space; (3) QCD matter in nuclei; and (4) Electroweak physics and the search for physics beyond the Standard Model. In this executive summary, we will briefly outline the outstanding physics questions in these areas and the suite of measurements that are available with an EIC to address these. The status of accelerator and detector designs is addressed at the end of the summary. Tables of golden measurements for each of the key science areas outlined are presented on page 12. In addition, each chapter in the report contains a comprehensive overview of the science topic addressed. Interested readers are encouraged to read these and the individual contributions for more details on the present status of EIC science.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Retrospective Analysis of Backwater Habitat Availability Using Remote Sensing

Low-velocity channel-margin habitats serve as important nursery habitats for the endangered Colorado pikeminnow (Ptychocheilus lucius) in the middle Green River between Jensen and Ouray, Utah. These habitats, known as backwaters, are associated with emergent sandbars, and are shaped and reformed annually by peak flows. Our recent knowledge about backwater characteristics and dynamics that is summarized in the synthesis report (Grippo et al. 2015) was based on detailed annual survey data from a relatively small sample of backwaters that were collected from 2003 to 2014 and reach-wide evaluations of backwater surface area based on manual interpretation of aerial and satellite imagery. Methods that bridge the gap between the detailed surveys from a small number of backwaters and the reach-wide assessment of their surface area would enable an assessment of the availability of backwater habitats that meet the minimum depth requirements for suitable habitat for Colorado pikeminnow. In 2015 Argonne National Laboratory (Argonne) tested three regression models—linear, multiple, and partial least square (PLS) regression models—for estimating backwater depth using National Agriculture Imagery Program (NAIP) imagery collected in July 2006 that covered the Jensen-Ouray reach of the Green River (Hamada and LaGory 2016). The results suggested that a PLS regression model showed high correlation with the reference depth (R 2 = 0.69) and had the most unbiased and consistent estimate of backwater depth. The results also indicated that the PLS model would provide reasonable estimates of the amount of habitat providing a minimum suitable depth of 30 cm for young-of-the-year Colorado pikeminnow, even though absolute depth estimates may be uncertain for backwater areas deeper than approximately 40 cm. The study also provided insights regarding the amount and the selection of calibration and validation (cal-val) data needed for improving the accuracy of depth prediction.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2003

Laboratory for Atmospheres 2002 Technical Highlights

How can we improve our ability to predict the weather-tomorrow, next week, and into the future? How is the Earth's climate changing? What causes such change? And what are its costs? What can the atmospheres of distant planets teach us about our own planet and its evolution? The Laboratory for Atmospheres is helping to answer these and other scientific questions about our planet and its neighbors. The Laboratory conducts a broad theoretical and experimental research program studying all aspects of the atmospheres of the Earth and other planets, including their structural, dynamical, radiative, and chemical properties, with the overarching goal to provide better understanding and to improve prediction of the Earth's climate. Vigorous research is central to NASA's exploration of the frontiers of knowledge. NASA scientists play a key role in conceiving new space missions, providing mission requirements, and carrying out research to explore the behavior of planetary systems, including, notably, the Earth's. Our Laboratory's scientists also supply outside scientists with technical assistance and scientific data to further investigations not immediately addressed by NASA itself. Laboratory scientists submit competitive research proposals with diverse scientific or technological approaches to NASA and other Federal agencies to acquire research support. The Laboratory management strives to provide a working environment that promotes creativity, competition, and openness. The Laboratory for Atmospheres is a vital participant in NASA's research program. Our Laboratory often has relatively large programs, sizable satellite missions, or observational campaigns that require the cooperative and collaborative efforts of many scientists. We ensure an appropriate balance between our scientists' responsibility for these large collaborative projects and their need for an active individual research agenda. This balance allows members of the Laboratory to continuously improve their scientific credentials. The Laboratory places high importance on promoting and measuring quality in its scientific research. We strive to assure high quality through peer-review funding processes that support approximately 90% of the work in the Laboratory. The overall quality of our scientific efforts is evaluated periodically by committees of advisors from the external scientific community, as detailed in Appendix 2 of this document. Members of the Laboratory interact with the general public to support a wide range of interests in the atmospheric sciences. Among other activities, the Laboratory raises the public's awareness of atmospheric science by presenting public lectures and demonstrations, by making scientific data available to wide audiences, by teaching, and by mentoring students and teachers. Section 6 presents details of the Laboratory's outreach activities during 2002. The Laboratory is also committed to addressing the demographic imbalances that exist today in the atmospheric and space sciences. We must address these imbalances for our field to enjoy the full benefit of all of the Nation's talent. The Laboratory makes substantial efforts to attract new scientists to the fields of atmospheric and space sciences. We strongly encourage the establishment of partnerships with Federal and state agencies that have operational responsibilities to promote the societal application of Earth sciences.

Steven E. Platnick↗

NASA NTRSDate not supplied

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

The Orbital Debris Engineering Model (ORDEM) developed by the NASA Orbital Debris Program Office (ODPO) is a data-driven model — extensive radar, optical, laboratory, and in situ measurement data sets have been used to build the model since its earliest versions. A salient aspect of professional software development is the verification and validation (V&V) process. Verification answers the question “Is the model built correctly?” while validation addresses the question “Did we build the correct model?” Less extensive, reserved, or independent data sets serve the validation requirement. Due to the dynamic nature of the orbital debris environment, it is critical to use contemporaneous data sources that represent the current environment to support ORDEM development and validation. ORDEM has utilized in situ data collected from Space Shuttle and Hubble Space Telescope surface inspections, now over a decade old. This historical dataset is fundamental for providing baseline in situ measurement data for sizes between 10 to 300 microns, but new data sources are being evaluated using returned surfaces from or near the International Space Station (ISS). This paper reviews a general microscopic survey of ISS soft goods, the Pressurized Mating Adapter 2 (PMA-2) blanket, and a limited-scope feasibility study conducted on the Space Exploration Technologies Corporation (SpaceX) Dragon capsule’s Thermal Protection System (TPS) material. The PMA-2 blanket, exposed to the space environment between 09 July 2013 and 25 February 2015, is an approximately 3.7 m2-area blanket composed of a betacloth outer layer and multiple ballistic fabric inner layers. The SpaceX Cargo Dragon capsule regularly visited the ISS from 2012 through 2020 and potentially provides a timely and well-characterized source of data for modeling purposes. The capsule’s lateral surfaces use SpaceX Proprietary Ablative Material (SPAM) TPS material, a syntactic foam, for thermal management during all mission phases. Seven SPAM extracted samples have been analyzed to date. This paper will provide an overview of the characterization completed for impact features by size, depth, impactor diameter, and the impactor residues chemical analyses, allowing a differentiation between micrometeoroids and orbital debris and a categorization by mass density and density class. Impactor diameter is estimated using damage equations generated from ground-based hypervelocity impact testing. The orbital debris impactors are compared to the current ORDEM 3.2 model of the environment at ISS altitudes. We briefly discuss the meteoroid impactors, including constituents and mass densities, in the general context of current models.

Phillip Anz-meador↗

NASA NTRSDate not supplied

A Survey of ISS and Visiting Vehicle Returned Surfaces for Environmental Characterization and Computer Model Development

Phillip Anz-Meador↗

DOE OSTI2015

OVERVIEW OF THE SDSS-IV MaNGA SURVEY: MAPPING NEARBY GALAXIES AT APACHE POINT OBSERVATORY

We present an overview of a new integral field spectroscopic survey called MaNGA (Mapping Nearby Galaxies at Apache Point Observatory), one of three core programs in the fourth-generation Sloan Digital Sky Survey (SDSS-IV) that began on 2014 July 1. MaNGA will investigate the internal kinematic structure and composition of gas and stars in an unprecedented sample of 10,000 nearby galaxies. We summarize essential characteristics of the instrument and survey design in the context of MaNGA's key science goals and present prototype observations to demonstrate MaNGA's scientific potential. MaNGA employs dithered observations with 17 fiber-bundle integral field units that vary in diameter from 12'' (19 fibers) to 32'' (127 fibers). Two dual-channel spectrographs provide simultaneous wavelength coverage over 3600-10300 Å at R ∼ 2000. With a typical integration time of 3 hr, MaNGA reaches a target r-band signal-to-noise ratio of 4-8 (Å{sup –1} per 2'' fiber) at 23 AB mag arcsec{sup –2}, which is typical for the outskirts of MaNGA galaxies. Targets are selected with M {sub *} ≳ 10{sup 9} M {sub ☉} using SDSS-I redshifts and i-band luminosity to achieve uniform radial coverage in terms of the effective radius, an approximately flat distribution in stellar mass, and a sample spanning a wide range of environments. Analysis of our prototype observations demonstrates MaNGA's ability to probe gas ionization, shed light on recent star formation and quenching, enable dynamical modeling, decompose constituent components, and map the composition of stellar populations. MaNGA's spatially resolved spectra will enable an unprecedented study of the astrophysics of nearby galaxies in the coming 6 yr.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2020

Approximating Trajectory Constraints With Machine Learning – Microgrid Islanding With Frequency Constraints

Here, we introduce deep earning aided constraint encoding to tackle the frequency-constraint microgrid scheduling problem. The nonlinear function between system operating condition and frequency nadir is approximated by using a neural network, which admits an exact mixed-integer formulation (MIP). This formulation is then integrated with the scheduling problem to encode the frequency constraint. With the stronger representation power of the neural network, the resulting commands can ensure adequate frequency response in a realistic setting in addition to islanding success. The proposed method is validated on a modified 33-node system. Successful islanding with a secure response is simulated under the scheduled commands using a detailed three-phase model in Simulink. The advantages of our model are particularly remarkable when the inertia emulation functions from wind turbine generators are considered.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Short-Depth QAOA circuits and Quantum Annealing on Higher-Order Ising Models (Rev.2)

The Quantum Alternating Operator Ansatz (QAOA) and Quantum Annealing (QA) are quantum algorithms that are both based on the adiabatic theorem and both have the goal of sampling the optimal solution(s) of combinatorial optimization problems. Quantum annealing has been physically instantiated on D-Wave devices using superconducting flux qubits, and QAOA can be programmed on digital gate-model quantum computers such as the programmable superconducting transmon qubits devices of the IBMQ series, for instance ibm washington. QAOA and QA address the same types of problems, but it is unclear how they will scale to large problem sizes and to larger and higher-fidelity quantum computers. In this article, we present a direct comparison between QAOA, one and two rounds, run on all 127 qubits of ibm washington and QA run on D-Wave Advantage system4.1 and Advantage system6.1. The problems which allow for this comparison are random Ising model problems whose connectivity matches the heavy hexagonal lattice topology of ibm washington and the Pegasus graph connectivity of the two D-Wave devices. We create two classes of problem instances for this comparison: one with higher order terms (ZZZ variable interactions), linear terms, and quadratic terms, and a separate problem type with only linear and quadratic terms. Our QAOA circuits are novel and extremely short depth, with a CNOT depth of 6 per round, which allows whole chip usage of ibm washington’s heavy hexagonal lattice and can be applied to future heavy-hex chips. We also test the effectiveness of the error suppression technique digital dynamical decoupling on the QAOA circuits. The QAOA circuits compiled to ibm washington are composed of several thousand circuit instructions, approximately 3, 000 depending on the details of the circuit, making these some the largest quantum circuits ever executed on a digital quantum processor. QAOA and QA are compared against the classical heuristic algorithm of simulated annealing and all problem instances are exactly solved using CPLEX in order to evaluate which samplers, if any, correctly found the ground state solution(s) of the problem instances. We find that (i) QA outperforms QAOA on all problem instances, (ii) QAOA samples the problems better than random sampling, and (iii) QAOA angle computation exhibits clear parameter concentration across the ensemble of Ising models.

127 Qubits↗

NASA NTRS2019

High-Performance Computing Optimization for Aladyn – Adaptive Neural Network Molecular Dynamics Mini-Application

This report provides a description and performance evaluation of the optimization techniques for high performance computing (HPC) implementation of the open source Computational Materials mini-application Aladyn (https://github.com/nasa/aladyn). Aladyn is a basic molecular dynamics code written in FORTRAN 2003, which is designed to demonstrate the use of adaptive neural networks (ANNs) in atomistic simulations. The role of ANNs is to efficiently reproduce the very complex energy landscape resulting from the atomic interactions in materials with the accuracy of the more expensive quantum mechanics-based calculations. The ANN is trained on a large set of atomic structures calculated using the density functional theory (DFT) method. While achieving orders of magnitude faster computational performance than DFT, the ANN-based approach was still very computationally demanding compared to the conventional approach of using empirically fitted energy functions. After its initial development, Aladyn was evaluated and optimized by experts at the NASA Advanced Supercomputing (NAS) division to exploit modern supercomputer architectures. The code has been optimized for execution on multicore central processing units (CPUs), including Intel® Skylake microarchitecture, and on graphic accelerators, such as Nvidia® V100 graphic processing units (GPUs), using Open Multi-Processing (OpenMP) and Open Accelerators (OpenACC) programming interfaces. The optimization achieved a speedup of 4.7 times the baseline version on CPU performance and an additional 2.4 times on CPU+GPU performance. Atomistic computer simulations are a fundamental tool in materials research to model material properties form physics-based first principles. Atomic interaction, governed by Quantum Mechanics (QM) require sophisticated and highly computationally demanding mathematical models to calculate [1]. Classical methods use approximate functional forms, empirically fitted through a set of variable parameters to emulate atomic energies as direct functions of atomic coordinates [2]. While empirical potentials are computationally much simpler, allowing simulations of large-scale systems of up to a trillion (1012) atoms [3], they are substantially less accurate compared to quantum calculations and applicable only to very specific atomic configurations or predefined crystallographic phases. A recently suggested approach is to use heuristic machine learning methods [4], such as those based on Adaptive Neural Networks (ANNs) to predict atomic energies, after being trained on a sufficiently large database of QM-calculated structures [5,6]. This approach reduces significantly the computational complexity, allowing for simulations of orders of magnitude larger systems compared to QM-based methods without compromising accuracy. Still, compared to classical methods using empirical energy functions, ANN methods remain two- to three orders of magnitude more computationally demanding. Hence, the computational cost of simulations, together with the need for extensive training of ANNs, still makes the practical implementation of ANN-based methods quite challenging. The purpose of the Aladyn mini-application software [7], available as open source at https://github.com/nasa/aladyn, is to be a testbed for exploring possible optimization strategies to develop highly scalable parallel algorithms for ANN-based atomistic simulations. Aladyn is aimed at utilizing the architecture of the high-end modern highperformance computing (HPC) hardware based on multicore central processing units (CPUs) equipped with graphic processing unit (GPU) accelerators. Specifically, the goal is to optimize the performance on a single HPC compute node, before implementing scaling to multi-node parallelization using message passing interface (MPI). At the same time, the open source code of Aladyn can serve as a training model for students and professors in academia.

Yamakov, Vesselin I.↗

NASA NTRS1989

Ecological applications of high resolution spectrometry

Future directions of NASA's space program plans include a significant effort at studying the Earth as a system of interrelated ecosystems. As part of NASA's Earth Observing System (Eos) Program a series of space platforms will be launched and operated to study the Earth with a variety of active and passive instruments. Several of the Eos instruments will be capable of imaging the planet's surface reflectance on a large number of very narrow portions of the solar spectrum. After the development of appropriate algorithms, this reflectance information will be used to determine key parameters about the structure and function of terrestrial and aquatic ecosystems and the pattern and processes of those systems across large areas of the globe. Algorithm development applicable to terrestrial systems will permit the inference of ecological processes from high resolution spectrometry data, similar to that to be forthcoming from the Eos mission. The first summer was spent working with tropical soils and relating their reflectance characteristics to particle size, iron content, and color. This summer the emphasis is on vegetation and work was begun with the Forest Ecosystems Dynamics Project in the Earth Resources Branch where both optical and radar characteristics of a mixed conifer/hardwood forest in Maine are being studied for use in a ecological modeling effort. A major series of aircraft overflights will take place throughout the summer. Laboratory and field spectrometers are used to measure the spectral reflectance of a hierarchy of vegetation from individual leaves to whole canopies for eventual modeling of their nutrient content using reflectance data. Key leaf/canopy parameters are being approximated including chlorophyll, nitrogen, phosphorus, water content, and leaf specific weight using high resolution spectrometry alone. Measurements are made of carbon exchange across the landscape for input to a spatial modeling effort to gauge production within the forest. A Geographic Information System approach is used to associate these data, images, and other collateral information for the forest into a database with a common projection suitable for spatial modeling.

Lawrence, William T.↗

DOE OSTI2022

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2017

High temperature ceramic heat exchanger for solid oxide fuel cell

A ceramic heat exchanger with high effectiveness and low-pressure drop has been developed for application as a cathode air preheater for a Solid Oxide Fuel Cell (SOFC). At the operating conditions of SOFCs, typical metallic alloys as those used in commercial heat exchangers may undergo chromium volatilization, which is a known cathode degradation mechanism that reduces SOFC performance and life. Use of ceramics such as alumina or alumina-silicate instead of chromium-containing metal is one approach to eliminate the effects of chromium on the SOFC cathode. This project leverages the geometric design of a heat exchanger previously prototyped and tested [1] to fabricate a novel heat exchanger made from a ceramic material. All calculations of heat exchanger performance requirements are based on state of the art SOFC operating conditions. The alumina-silicate material selected to fabricate the modular prototype heat exchanger was made via a heat transfer based trade-off analysis that shows that for low pressure-drop devices, flow convection is the limiting heat transfer mechanism, and therefore wall conductivity becomes less relevant to heat transfer effectiveness. The modular design presented allows for incremental aggregation of modules to target a broad range of operating conditions typical of present and upcoming SOFC applications (e.g., 25 to 400 kWe). The completed prototype was subjected to a series of static leak/pressure tests, dynamic pressure drop tests both at ambient and realistic service temperature conditions, and finally to a matrix of heat transfer experiments to fully characterize its heat transfer effectiveness (including tests at hot gas temperatures up to 1033 K or 1400oF). The stand-alone system was demonstrated in the laboratory to successfully satisfy the design criteria at realistic operating conditions, showing a total pressure drop at the design flow of 8 g/sec of 6 kPa (vs. 3.45 kPa approximate requirement). It was also shown to have heat transfer effectiveness of 76% (with 73% being the design requirement). Moreover, the unit was shown to operate leak-free, and the ceramic elements and seals were capable of withstanding the thermal cycling resulting from the testing procedure. The heat exchanger was then integrated into a modified fuel cell test stand and tested at steady state operation. Unfortunately, the level of performance achieved was lower than expected based on laboratory performance tests. This appears to have been the result of an unforeseen loosening of a heat exchanger structural component, which resulted into a leak that prevented proper supply of hot gas to the heat exchanger. However, in general terms, the heat exchanger/fuel cell integration process provides confidence that a future application of the unit with a SOFC is feasible, assuming structural issues are addressed. It is considered that the difficulties encountered at the last stage of the program provided invaluable input in locating shortcomings of the mechanical design and integration approach. A portion of this work was presented at the ASME Power & Energy Conference, in Charlotte, NC, on June 28th 2016 in a paper entitled “Development of a Ceramic Heat Exchanger for Application as Solid Oxide Fuel Cell Cathode Air Preheater” and the corresponding paper was published in the Proceedings of the ASME 2016 Power & Energy Conference, Paper No.: PowerEnergy2016-59333 [8].

20 FOSSIL-FUELED POWER PLANTS↗

NASA NTRS2000

Performance of an Optimized Eta Model Code on the Cray T3E and a Network of PCs

In the year 2001, NASA will launch the satellite TRIANA that will be the first Earth observing mission to provide a continuous, full disk view of the sunlit Earth. As a part of the HPCC Program at NASA GSFC, we have started a project whose objectives are to develop and implement a 3D cloud data assimilation system, by combining TRIANA measurements with model simulation, and to produce accurate statistics of global cloud coverage as an important element of the Earth's climate. For simulation of the atmosphere within this project we are using the NCEP/NOAA operational Eta model. In order to compare TRIANA and the Eta model data on approximately the same grid without significant downscaling, the Eta model will be integrated at a resolution of about 15 km. The integration domain (from -70 to +70 deg in latitude and 150 deg in longitude) will cover most of the sunlit Earth disc and will continuously rotate around the globe following TRIANA. The cloud data assimilation is supposed to run and produce 3D clouds on a near real-time basis. Such a numerical setup and integration design is very ambitious and computationally demanding. Thus, though the Eta model code has been very carefully developed and its computational efficiency has been systematically polished during the years of operational implementation at NCEP, the current MPI version may still have problems with memory and efficiency for the TRIANA simulations. Within this work, we optimize a parallel version of the Eta model code on a Cray T3E and a network of PCs (theHIVE) in order to improve its overall efficiency. Our optimization procedure consists of introducing dynamically allocated arrays to reduce the size of static memory, and optimizing on a single processor by splitting loops to limit the number of streams. All the presented results are derived using an integration domain centered at the equator, with a size of 60 x 60 deg, and with horizontal resolutions of 1/2 and 1/3 deg, respectively. In accompanying charts we report the elapsed time, the speedup and the Mflops as a function of the number of processors for the non-optimized version of the code on the T3E and theHIVE. The large amount of communication required for model integration explains its poor performance on theHIVE. Our initial implementation of the dynamic memory allocation has contributed to about 12% reduction of memory but has introduced a 3% overhead in computing time. This overhead was removed by performing loop splitting in some of the high demanding subroutines. When the Eta code is fully optimized in order to meet the memory requirement for TRIANA simulations, a non-negligeable overhead may appear that may seriously affect the efficiency of the code. To alleviate this problem, we are considering implementation of a new algorithm for the horizontal advection that is computationally less expensive, and also a new approach for marching in time.

Kouatchou, Jules↗

DOE OSTI2012

Energy Reductions Using Next-Generation Remanufacturing Techniques

The goal of this project was to develop a radically new surface coating approach that greatly enhances the performance of thermal spray coatings. Rather than relying on a roughened grit blasted substrate surface for developing a mechanical bond between the coating and substrate, which is the normal practice with conventional thermal spraying, a hybrid approach of combining a focused laser beam to thermally treat the substrate surface in the vicinity of the rapidly approaching thermally-sprayed powder particles was developed. This new surface coating process is targeted primarily at enabling remanufacturing of components used in engines, drive trains and undercarriage systems; thereby providing a substantial global opportunity for increasing the magnitude and breadth of parts that are remanufactured through their life cycle, as opposed to simply being replaced by new components. The projected benefits of a new remanufacturing process that increases the quantity of components that are salvaged and reused compared to being fabricated from raw materials will clearly vary based on the specific industry and range of candidate components that are considered. At the outset of this project two different metal processing routes were considered, castings and forgings, and the prototypical components for each process were liners and crankshafts, respectively. The quantities of parts used in the analysis are based on our internal production of approximately 158,000 diesel engines in 2007. This leads to roughly 1,000,000 liners (assuming a mixture of 6- and 8-cylinder engines) and 158,000 crankshafts. Using energy intensity factors for casting and forgings, respectively, of 4450 and 5970 Btu-hr/lb along with the energy-induced CO 2 generation factor of 0.00038 lbs CO 2 /Btu, energy savings of over 17 trillion BTUs and CO 2 reductions of over 6.5 million lbs could potentially be realized by remanufacturing the above mentioned quantities of crankshafts and liners. This project supported the Industrial Technologies Program's initiative titled 'Industrial Energy Efficiency Grand Challenge.' To contribute to this Grand Challenge, we. pursued an innovative processing approach for the next generation of thermal spray coatings to capture substantial energy savings and green house gas emission reductions through the remanufacturing of steel and aluminum-based components. The primary goal was to develop a new thermal spray coating process that yields significantly enhanced bond strength. To reach the goal of higher coating bond strength, a laser was coupled with a traditional twin-wire arc (TWA) spray gun to treat the component surface (i.e., heat or partially melt) during deposition. Both ferrous and aluminum-based substrates and coating alloys were examined to determine what materials are more suitable for the laser-assisted twin-wire arc coating technique. Coating adhesion was measured by static tensile and dynamic fatigue techniques, and the results helped to guide the identification of appropriate remanufacturing opportunities that will now be viable due to the increased bond strength of the laser-assisted twin-wire arc coatings. The feasibility of the laser-assisted TWA (LATWA) process was successfully demonstrated in this current effort. Critical processing parameters were identified, and when these were properly controlled, a strong, diffusion bond was developed between the substrate and the deposited coating. Consequently, bond strengths were nearly doubled over those typically obtained using conventional grit-blast TWA coatings. Note, however, that successful LATWA processing was limited to ferrous substrates coated with steel coatings (e.g., 1020 and 1080 steel). With Al-based substrates, it was not possible to avoid melting a thin layer of the substrate during spraying, and this layer re-solidified to form a band of intermetallic phases at the substrate/coating interface, which significantly diminished the coating adhesion. The capability to significantly increase the bond strength with ferrous substrates and coatings may open new remanufacturing opportunities that were previously not considered due to concerns with the limits of the mechanical bonding of conventional TWA coatings. However, the limited results obtained within this one-year program are not sufficient to move the LATWA into a production environment. Additional work will be needed engineer the process to coat components with more complex geometries than the flat specimens studied in this work. In addition part-specific bench testing and relevant field tests will be required to fully establish the necessary confidence for introducing the LATWA process. These are typical constraints and requirements for most any new production process, and it is quite possible this new process will continue to be a viable approach for extending the usage of remanufacturing, and in turn capturing the resulting energy savings and green house gas emission reductions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

NASA NTRS1996

Intracellular magnetophoresis of amyloplasts and induction of root curvature

High-gradient magnetic fields (HGMFs) were used to induce intracellular magnetophoresis of amyloplasts. The HGMFs were generated by placing a small ferromagnetic wedge into a uniform magnetic field or at the gap edge between two permanent magnets. In the vicinity of the tip of the wedge the dynamic factor of the magnetic field, delta(H2/2), was about 10(9) Oe2.cm-1, which subjected the amyloplasts to a force comparable to that of gravity. When roots of 2-d-old seedlings of flax (Linum usitatissimum L.) were positioned vertically and exposed to an HGMF, curvature away from the wedge was transient and lasted approximately 1 h. Average curvature obtained after placing magnets, wedge and seedlings on a 1-rpm clinostat for 2 h was 33 +/- 5 degrees. Roots of horizontally placed control seedlings without rotation curved about 47 +/- 4 degrees. The time course of curvature and changes in growth rate were similar for gravicurvature and for root curvature induced by HGMFs. Microscopy showed displacement of amyloplasts in vitro and in vivo. Studies with Arabidopsis thaliana (L.) Heynh. showed that the wild type responded to HGMFs but the starchless mutant TC7 did not. The data indicate that a magnetic force can be used to study the gravisensing and response system of roots.

Non-NASA Center↗

NASA NTRS2022

Design of Hypervelocity Flow Generator (HFG) and Its Diagnostics

Ground facilities for hypersonic research are a key element for successful development of aerodynamically proven hypervelocity vehicles. Design concepts and diagnostics of a hypervelocity flow generator (HFG) were made as a test platform for hypersonic/hypervelocity spacecraft models at the NASA Langley Research Center. The HFG is a hypersonic flow field generator using optically heated gas which is blown into an 80 cu m vacuum chamber. The vacuum chamber is kept at a stable vacuum pressure with a combination of three large vacuum pumps, while the HFG is in the test mode. The HFG provides a relatively small test section with approximately a 20 cm window. This facility was designed to generate 2.45 km/sec of flow speed, and potentially generate a continuous flow with the nozzle and vacuum system. The window in test section provides a direct view of the shock wave around a model in order to measure temperature, pressure, and density profile within the shock layer. One of the key test goals under this project is to understand why the emission spectra from the standing shockwave plasma predicted by Lora-Loran codes are significantly different from the measured emission spectra from the Flight Investigation Reentry Environment (FIRE II) Flight. The correct estimate of the thermal loading on the leading edge of hypersonic vehicles greatly affects the aerodynamic design, the material selection for the vehicle, and the cooling requirement and can be obtained by the precise modeling of emission spectra from shockwave plasma. However, the estimation of thermal loading is not an easy task due to complex non-equilibrium radiative process within high temperature shock layers that still falls into a category of cold plasma. Direct flight experiments are the most desirable, but not a cost-effective approach. Analysis by computational fluid dynamics (CFD) offers many test flexibilities. However, the CFD codes must be fully tested and validated with experimental data before the codes are effectively used for practical design. Large discrepancies between experiments and codes appear in hypersonic/hypervelocity flow regimes at high altitudes of 60 km ~ 90 km. This HFG facility offers some important parameters for CFD code validation, such as collision cross-sections, relaxation times, reaction rate coefficients and transportation coefficients. The HFG test facility is based on the ejection flow of high temperature gas heated over to 3500 K through a nozzle. The tungsten gas chamber of the HFG is heated up to a desired temperature by a 60 kW optical power beam source. This system consists of an optical power source, a thermal chamber, an expansion nozzle, a test section, and an 80 cu m vacuum tank. 60 kW optical input power is obtained from the 150 kW Vortek arc lamp system (by Vortek Industries, Vancouver, Canada). This optical beam is focused to heat the gas chamber within which a flow media is heated. The maximum achievable temperature of the flow medium reached approximately 3500 K or even higher but is limited by the melting point of the chamber material used. The exhaust velocity through the nozzle was determined by the stagnation temperature and the molecular weight of the working medium at the test section. To provide design parameters, a NASA Chemical Equilibrium with Application (CEA) computer program is used for the simulation of aerothermal data. This CEA program can calculate chemical equilibrium and properties of complex mixtures using shock tube parameters. For nitrogen gas at 2666 K stagnation temperature, the maximum achievable velocity at the test section is approximately 2.45 km/sec which is within the range of the thermal velocity of 8000 K shock layer. Based on the calculation through the CEA program, the design parameters of a HFG were determined and implemented for the test section that includes an expansion nozzle. The installed test section of the experimental facility can sustain a condition of a re-entry vehicle from the Space at an altitude of 60-90 km. After installation of the HFG, the system was fully tested and its operational parameters were measured. An 80 cu m vacuum chamber of HFG was set at 1 torr level to keep a stable downstream condition. The pumping time to reach the minimum vacuum pressure (~ 1 torr) at the test chamber from atmospheric pressure was approximately an hour using Kinney (MBV-14000/MB -1600/KT-300) and Stokes (Model 1772 and 412) pumps. Such a setup condition allowed a continued stable operation of the HFG experiment with flowrates through 1-, 3-, or 5-mm diameters of nozzle throat. The flow characteristics of the HFG for various operating conditions were performed using a focused Schlieren method. At 0.8 torr chamber pressure, a barrel shock was observed at the test section. With a sphere obstacle of 12 mm diameter in the flow, a bow shock (~ 2-mm thickness) was observed by a focused Schlieren visualization method.

Hypervelocity flow↗