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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Quantum Solvers for Plane-Wave Hamiltonians: Abridging Virtual Spaces Through the Optimization of Pairwise Correlations

For many-body methods such as MCSCF and CASSCF, in which the number of one-electron orbitals is optimized and independent of the basis set used, there are no problems with using plane-wave basis sets. However, for methods currently used in quantum computing such as select configuration interaction (CI) and coupled cluster (CC) methods, it is necessary to have a virtual space that is able to capture a significant amount of electron-electron correlation in the system. The virtual orbitals in a pseudopotential plane-wave Hartree–Fock calculation, because of Coulomb repulsion, are often scattering states that interact very weakly with the filled orbitals. As a result, very little correlation energy is captured from them. The use of virtual spaces derived from the one-electron operators has also been tried, and while some correlations are captured, the amount is quite low. To overcome these limitations, we have been developing new classes of algorithms to define virtual spaces by optimizing orbitals from small pairwise CI Hamiltonians, which we term as correlation optimized virtual orbitals with the abbreviation COVOs. With these procedures, we have been able to derive virtual spaces, containing only a few orbitals, which are able to capture a significant amount of correlation. The focus in this manuscript is on using these derived basis sets to target full CI (FCI) quality results for H2 on near-term quantum computers. However, the initial results for this approach were promising. We were able to obtain good agreement with FCI/cc-pVTZ results for this system with just 4 virtual orbitals, using both FCI and quantum simulations. The quality of the results using COVOs suggests that it may be possible to use them in other many-body approaches, including coupled cluster and Møller–Plesset perturbation theories, and open up the door to many-body calculations for pseudopotential plane-wave basis set methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Decentralized control of units in smart grids for the support of renewable energy supply

Due to the significant environmental impact of power production from fossil fuels and nuclear fission, future energy systems will increasingly rely on distributed and renewable energy sources (RES). The electrical feed-in from photovoltaic (PV) systems and wind energy converters (WEC) varies greatly both over short and long time periods (from minutes to seasons), and (not only) by this effect the supply of electrical power from RES and the demand for electrical power are not per se matching. In addition, with a growing share of generation capacity especially in distribution grids, the top-down paradigm of electricity distribution is gradually replaced by a bottom-up power supply. This altogether leads to new problems regarding the safe and reliable operation of power grids. In order to address these challenges, the notion of Smart Grids has been introduced. The inherent flexibilities, i.e. the set of feasible power schedules, of distributed power units have to be controlled in order to support demand–supply matching as well as stable grid operation. Controllable power units are e.g. combined heat and power plants, power storage systems such as batteries, and flexible power consumers such as heat pumps. By controlling the flexibilities of these units we are particularly able to optimize the local utilization of RES feed-in in a given power grid by integrating both supply and demand management measures with special respect to the electrical infrastructure. In this context, decentralized systems, autonomous agents and the concept of self-organizing systems will become key elements of the ICT based control of power units. In this contribution, we first show how a decentralized load management system for battery charging/discharging of electrical vehicles (EVs) can increase the locally used share of supply from PV systems in a low voltage grid. For a reliable demand side management of large sets of appliances, dynamic clustering of these appliances into uniformly controlled appliance sets is necessary. We introduce a method for self-organized clustering for this purpose and show how control of such clusters can affect load peaks in distribution grids. Subsequently, we give a short overview on how we are going to expand the idea of self-organized clusters of units into creating a virtual control center for dynamic virtual power plants (DVPP) offering products at a power market. For an efficient organization of DVPPs, the flexibilities of units have to be represented in a compact and easy to use manner. We give an introduction how the problem of representing a set of possibly 10{sup 100} feasible schedules can be solved by a machine-learning approach. In summary, this article provides an overall impression how we use agent based control techniques and methods of self-organization to support the further integration of distributed and renewable energy sources into power grids and energy markets. - Highlights: • Distributed load management for electrical vehicles supports local supply from PV. • Appliances can self-organize into so called virtual appliances for load control. • Dynamic VPPs can be controlled by extensively decentralized control centers. • Flexibilities of units can efficiently be represented by support-vector descriptions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2012

Cation-Bonding and Protonation of the Fe[subscript 4]-Square Cluster

The synthesis and characterization of discrete, molecular iron-oxo clusters is pursued in the interest of molecular magnets, bioinspired materials and models for the geochemical aqueous-mineral interface. Iron-oxo clusters are challenging to synthesize in water, due to the extremely acidic and reactive nature of dissolved iron species, and thus require chelating ligands to passivate and neutralize the cluster surface. The 2-hydroxy-1,3-N,N,N',N'-diamino-propanetetraacetic acid (HPDTA) ligand has been used to isolate several Al and Fe cluster geometries, including the square clusters Fe{sub 4}(HPDTA){sub 2} and Al{sub 4}(HPDTA){sub 2}. While prior reports on the Fe{sub 4}(HPDTA){sub 2} cluster have focused on the magnetic properties, no solution characterization has been carried out. Using electrospray ionization mass-spectrometry (ESI-MS) we show this anionic Fe{sub 4}(HPDTA){sub 2} cluster can be dissolved intact in water, and recrystallized with virtually any metal as a countercation. The bonding of the metal cation to the square face of the cluster trends with ionic radii of the cations, as shown by structural characterization of Fe{sub 4}(HPDTA){sub 2} with Li{sup +}, Na{sup +}, Cs{sup +}, Mg{sup 2+}, Ba{sup 2+}, La{sup 3+}, Eu{sup 3+}, and Zn{sup 2+}. This trend is similar to that observed for association of cations on metal oxide surfaces in the environment. Furthermore, protonation of the bridging oxo ligands of this series of Fe{sub 4}(HPDTA){sub 2} clusters is variable (0, 1, or 2 protons), and structures as a function of protonation is discussed. This paper, largely structural in nature, sets the foundation for future aqueous phase studies of iron-oxo molecular clusters as models for the oxide-water interface in the natural aqueous environment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

On lithium-rich red giants: engulfment on the giant branch of Trumpler 20

The Gaia-ESO survey recently reported on a large sample of lithium (Li) abundance determinations for evolved stars in the rich open cluster Trumpler 20. They argue for a scenario where virtually all stars experience post-main-sequence mixing and Li is preserved in only two objects. We present an alternate explanation, where Li is normal in the vast majority of cluster stars and anomalously high in these two cases. We demonstrate that the Li upper limits in the red giants can be explained with a combination of main-sequence depletion and standard dredge-up and that they are close to the detected levels in other systems of similar age. In our framework, two of the detected giants are anomalously Li-rich, and we propose that both could have been produced by the engulfment of a substellar mass companion of 16{sub −10}{sup +6} M{sub J}. This would imply that ∼5% of 1.8 M{sub ⊙} stars in this system, and by extension elsewhere, should have substellar mass companions of high mass that could be engulfed at some point in their lifetimes. We discuss future tests that could confirm or refute this scenario.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2012

THE IMPACT OF THERMODYNAMICS ON GRAVITATIONAL COLLAPSE: FILAMENT FORMATION AND MAGNETIC FIELD AMPLIFICATION

Stars form by the gravitational collapse of interstellar gas. The thermodynamic response of the gas can be characterized by an effective equation of state. It determines how gas heats up or cools as it gets compressed, and hence plays a key role in regulating the process of stellar birth on virtually all scales, ranging from individual star clusters up to the galaxy as a whole. We present a systematic study of the impact of thermodynamics on gravitational collapse in the context of high-redshift star formation, but argue that our findings are also relevant for present-day star formation in molecular clouds. We consider a polytropic equation of state, P = k{rho}{sup {Gamma}}, with both sub-isothermal exponents {Gamma} < 1 and super-isothermal exponents {Gamma} > 1. We find significant differences between these two cases. For {Gamma} > 1, pressure gradients slow down the contraction and lead to the formation of a virialized, turbulent core. Weak magnetic fields are strongly tangled and efficiently amplified via the small-scale turbulent dynamo on timescales corresponding to the eddy-turnover time at the viscous scale. For {Gamma} < 1, on the other hand, pressure support is not sufficient for the formation of such a core. Gravitational contraction proceeds much more rapidly and the flow develops very strong shocks, creating a network of intersecting sheets and extended filaments. The resulting magnetic field lines are very coherent and exhibit a considerable degree of order. Nevertheless, even under these conditions we still find exponential growth of the magnetic energy density in the kinematic regime.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1993

A distributed version of the NASA Engine Performance Program

Distributed NEPP, a version of the NASA Engine Performance Program, uses the original NEPP code but executes it in a distributed computer environment. Multiple workstations connected by a network increase the program's speed and, more importantly, the complexity of the cases it can handle in a reasonable time. Distributed NEPP uses the public domain software package, called Parallel Virtual Machine, allowing it to execute on clusters of machines containing many different architectures. It includes the capability to link with other computers, allowing them to process NEPP jobs in parallel. This paper discusses the design issues and granularity considerations that entered into programming Distributed NEPP and presents the results of timing runs.

Cours, Jeffrey T.↗
DOE OSTI2015

ZFIRE: Galaxy cluster kinematics, Hα star formation rates, and gas phase metallicities of XMM-LSS J02182-05102 AT z{sub cl}=1.6233

We spectroscopically survey the galaxy cluster XMM-LSS J02182-05102 (hereafter IRC 0218) using LRIS (optical) and MOSFIRE (near-infrared) on Keck I as part of the ZFIRE survey. IRC 0218 has a narrow redshift range of 1.612 < z{sub spec} < 1.635 defined by 33 members of which 20 are at R{sub proj} < 1 Mpc. The cluster redshift and velocity dispersion are z{sub cl}=1.6233±0.0003 and σ{sub cl}=254±50 km s{sup −1}. We reach NIR line sensitivities of ∼0.3 × 10{sup −17} erg s{sup −1} cm{sup −2} that, combined with multi-wavelength photometry, provide extinction-corrected Hα star formation rates (SFR), gas phase metallicities from [N ii]/Hα, and stellar masses. We measure an integrated Hα SFR of ∼325 M{sub ⊙} yr{sup −1} (26 members; R{sub proj} < 2 Mpc) and show that the elevated star formation in the cluster core (R{sub proj} < 0.25 Mpc) is driven by the concentration of star-forming members, but the average SFR per Hα-detected galaxy is half that of members at R{sub proj} ∼ 1 Mpc. However, we do not detect any environmental imprint when comparing attenuation and gas phase metallicities: the cluster galaxies show similar trends with M{sub ⋆} as to the field, e.g., more massive galaxies have larger stellar attenuation. IRC 0218’s gas phase metallicity–M{sub ⋆} relation (MZR) is offset to lower metallicities relative to z∼0 and has a slope of 0.13 ± 0.10. Comparing the MZR in IRC 0218 to the COSMOS cluster at z = 2.1 shows no evolution (Δt∼1 Gyr): the MZR for both galaxy clusters are remarkably consistent with each other and virtually identical to several field surveys at z∼2.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

minimega

Minimega is a simple emulytics platform for creating testbeds of networked devices. The platform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. Minimega attempts to allow experiments to be brought up quickly with nearly no configuration. Minimega also includes tools for simple cluster management, as well as tools for creating Linux based virtual machine images.

David Fritz, JohnFloren↗
DOE OSTI2013

minimega

Minimega is a simple emulytics platform for creating testbeds of networked devices. The platform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. Minimega attempts to allow experiments to be brought up quickly with nearly no configuration. Minimega also includes tools for simple cluster management, as well as tools for creating Linux based virtual machine images.

David Fritz, John Floren↗
DOE OSTI2017

Three-Dimensional Modeling of Fracture Clusters in Geothermal Reservoirs

The objective of this is to develop a 3-D numerical model for simulating mode I, II, and III (tensile, shear, and out-of-plane) propagation of multiple fractures and fracture clusters to accurately predict geothermal reservoir stimulation using the virtual multi-dimensional internal bond (VMIB). Effective development of enhanced geothermal systems can significantly benefit from improved modeling of hydraulic fracturing. In geothermal reservoirs, where the temperature can reach or exceed 350oC, thermal and poro-mechanical processes play an important role in fracture initiation and propagation. In this project hydraulic fracturing of hot subsurface rock mass will be numerically modeled by extending the virtual multiple internal bond theory and implementing it in a finite element code, WARP3D, a three-dimensional finite element code for solid mechanics. The new constitutive model along with the poro-thermoelastic computational algorithms will allow modeling the initiation and propagation of clusters of fractures, and extension of pre-existing fractures. The work will enable the industry to realistically model stimulation of geothermal reservoirs. The project addresses the Geothermal Technologies Office objective of accurately predicting geothermal reservoir stimulation (GTO technology priority item). The project goal will be attained by: (i) development of the VMIB method for application to 3D analysis of fracture clusters; (ii) development of poro- and thermoelastic material sub-routines for use in 3D finite element code WARP3D; (iii) implementation of VMIB and the new material routines in WARP3D to enable simulation of clusters of fractures while accounting for the effects of the pore pressure, thermal stress and inelastic deformation; (iv) simulation of 3D fracture propagation and coalescence and formation of clusters, and comparison with laboratory compression tests; and (v) application of the model to interpretation of injection experiments (planned by our industrial partner) with reference to the impact of the variations in injection rate and temperature, rock properties, and in-situ stress.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

minimega v. 3.0

minimega is an emulytics platform for creating testbeds of networked devices. The platoform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. minimega allows experiments to be brought up quickly with almost no configuration. minimega also includes tools for simple cluster, management, as well as tools for creating Linux-based virtual machines. This release of minimega includes new emulated sensors for Android devices to improve the fidelity of testbeds that include mobile devices. Emulated sensors include GPS and

Crussell, Jonathan↗
DOE OSTI2015

minimega v. 3.0

minimega is an emulytics platform for creating testbeds of networked devices. The platoform consists of easily deployable tools to facilitate bringing up large networks of virtual machines including Windows, Linux, and Android. minimega allows experiments to be brought up quickly with almost no configuration. minimega also includes tools for simple cluster, management, as well as tools for creating Linux-based virtual machines. This release of minimega includes new emulated sensors for Android devices to improve the fidelity of testbeds that include mobile devices. Emulated sensors include GPS and

Crussell, Jonathan↗
NASA NTRS1992

The engine design engine. A clustered computer platform for the aerodynamic inverse design and analysis of a full engine

An application for parallel computation on a combined cluster of powerful workstations and supercomputers was developed. A Parallel Virtual Machine (PVM) is used as message passage language on a macro-tasking parallelization of the Aerodynamic Inverse Design and Analysis for a Full Engine computer code. The heterogeneous nature of the cluster is perfectly handled by the controlling host machine. Communication is established via Ethernet with the TCP/IP protocol over an open network. A reasonable overhead is imposed for internode communication, rendering an efficient utilization of the engaged processors. Perhaps one of the most interesting features of the system is its versatile nature, that permits the usage of the computational resources available that are experiencing less use at a given point in time.

Sanz, J.↗
DOE OSTI2015

Interactions of model biomolecules. Benchmark CC calculations within MOLCAS

We present results using the OVOS approach (Optimized Virtual Orbitals Space) aimed at enhancing the effectiveness of the Coupled Cluster calculations. This approach allows to reduce the total computer time required for large-scale CCSD(T) calculations about ten times when the original full virtual space is reduced to about 50% of its original size without affecting the accuracy. The method is implemented in the MOLCAS computer program. When combined with the Cholesky decomposition of the two-electron integrals and suitable parallelization it allows calculations which were formerly prohibitively too demanding. We focused ourselves to accurate calculations of the hydrogen bonded and the stacking interactions of the model biomolecules. Interaction energies of the formaldehyde, formamide, benzene, and uracil dimers and the three-body contributions in the cytosine – guanine tetramer are presented. Other applications, as the electron affinity of the uracil affected by solvation are also shortly mentioned.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

Virtual Log-Structured Storage for High-Performance Streaming

Over the past decade, given the higher number of data sources (e.g., Cloud applications, Internet of things) and critical business demands, Big Data transitioned from batch-oriented to real-time analytics. Stream storage systems, such as Apache Kafka, are well known for their increasing role in real-time Big Data analytics. For scalable stream data ingestion and processing, they logically split a data stream topic into multiple partitions. Stream storage systems keep multiple data stream copies to protect against data loss while implementing a stream partition as a replicated log. This architectural choice enables simplified development while trading cluster size with performance and the number of streams optimally managed. This paper introduces a shared virtual log-structured storage approach for improving the cluster throughput when multiple producers and consumers write and consume in parallel data streams. Stream partitions are associated with shared replicated virtual logs transparently to the user, effectively separating the implementation of stream partitioning (and data ordering) from data replication (and durability). We implement the virtual log technique in the KerA stream storage system. When comparing with Apache Kafka, KerA improves the cluster ingestion throughput by up to 4x when multiple producers write over hundreds of data streams.

consistent stream ordering↗
DOE OSTI2012

Megatux

The Megatux platform enables the emulation of large scale (multi-million node) distributed systems. In particular, it allows for the emulation of large-scale networks interconnecting a very large number of emulated computer systems. It does this by leveraging virtualization and associated technologies to allow hundreds of virtual computers to be hosted on a single moderately sized server or workstation. Virtualization technology provided by modern processors allows for multiple guest OSs to run at the same time, sharing the hardware resources. The Megatux platform can be deployed on a single PC, a small cluster of a few boxes or a large cluster of computers. With a modest cluster, the Megatux platform can emulate complex organizational networks. By using virtualization, we emulate the hardware, but run actual software enabling large scale without sacrificing fidelity.

Evensky, David↗
DOE OSTI2016

Speeding up equation of motion coupled cluster theory with the chain of spheres approximation

In the present paper, the chain of spheres exchange (COSX) approximation is applied to the highest scaling terms in the equation of motion (EOM) coupled cluster equations with single and double excitations, in particular, the terms involving integrals with four virtual labels. It is found that even the acceleration of this single term yields significant computational gains without compromising the desired accuracy of the method. For an excitation energy calculation on a cluster of five water molecules using 585 basis functions, the four virtual term is 9.4 times faster using COSX with a loose grid than using the canonical implementation, which yields a 2.6 fold acceleration for the whole of the EOM calculation. For electron attachment calculations, the four virtual term is 15 times and the total EOM calculation is 10 times faster than the canonical calculation for the same system. The accuracy of the new method was tested using Thiel’s test set for excited states using the same settings and the maximum absolute deviation over the whole test set was found to be 12.945 cm{sup −1} (59 μHartree) for excitation energies and 6.799 cm{sup −1} (31 μHartree) for electron attachments. Using MP2 amplitudes for the ground state in combination with the parallel evaluation of the full EOM equations in the manner discussed in this paper enabled us to perform calculations for large systems. Electron affinity values for the two lowest states of a Zn protoporphyrine model compound (224 correlated electrons and 1120 basis functions) were obtained in 3 days 19 h using 4 cores of a Xeon E5-2670 processor allocating 10 GB memory per core. Calculating the lowest two excitation energies for trans-retinal (114 correlated electrons and 539 basis functions) took 1 day 21 h using eight cores of the same processor and identical memory allocation per core.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Towards an improved understanding of the influence of subpixel vegetation structure on pixel-level spectra: a simulation approach

The planned NASA Hyperspectral Infrared Imager (HyspIRI) mission, equipped with an imaging spectrometer that has the capability of monitoring ecosystems globally, will provide an unprecedented opportunity to address scientific challenges related to ecosystem function and change. However, uncertainty remains around the impact of subpixel vegetation structure, in combination with the point spread function, on pixel-level imaging spectroscopy data. We estimated structural parameters, e.g., leaf area index (LAI), canopy cover, and tree location, from HyspIRI spectral data, with the goal of assessing how subpixel variation in these parameters impact pixel-level imaging spectroscopy data. The fine-scale variability of real vegetation structure makes this a challenging endeavor. Therefore, we utilized a simulation-based approach to counter the time-consuming and often destructive sampling needs of vegetation structural analysis and to simultaneously generate synthetic HyspIRI data pre-launch. Three virtual scenes were constructed, corresponding to the actual vegetation structure in the National Ecological Observatory Network’s (NEON) Pacific Southwest Domain (Fresno, CA). These included an oak savanna, a dense coniferous forest, and a conifer-manzanita-mixed forest. Simulated spectroscopy data for these scenes were then generated using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. Simulations first were used to verify the physical model, virtual scene geometrical information, and simulation parameters. This was followed by simulations of HyspIRI data, where within-pixel structural variability was introduced, e.g., by iteratively changing per-pixel canopy cover and tree placement, tree clustering, leaf area index (LAI), etc., between simulation runs for the virtual scenes. Finally, narrow-band vegetation indices (VIs) were extracted from the data in an attempt to describe the variability of the subpixel structural parameters; this was done in order to assess VI robustness to changes in structural “levels”, as well as placement of trees/canopies within the instrument’s instantaneous field-of-view (IFOV). Our ultimate goal is not only to better understand how such subpixel variability influence imaging spectroscopy outputs, but also to better estimate vegetation structural parameters using spectra. We constructed regression models for LAI (R2 = 0.92) and canopy cover (R2 = 0.97) with narrow-band VIs via this simulation approach. Our models ultimately are intended to improve the HyspIRI mission’s ability to monitor global vegetation structure.

Van Aardt, Jan↗