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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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BoltzmannMFX is a biological simulation code that solves chemical reaction networks using maximum entropy methods. It uses modules from MFiX-Exa and is based on the AMReX framework for massively parallel block-structured adaptive mesh applications.
MatRed is a parallel redistribution tool for HPC applications. It provides a simple approach that only requires a few relation matrices between entities to build redistribution matrices in parallel simulation codes. In particular, MatRed is well-suited for simulation codes based on finite element/volume methods.
Nonlinear interactions of waves via instantaneous cross-phase modulation can be cast in the same way as ponderomotive wave-particle interactions in high-frequency electromagnetic fi eld. The ponderomotive effect arises when rays of a probe wave scatter off perturbations of the underlying medium produced by a second, modulation wave, much like charged particles scatter off a quasiperiodic field. Parallels with the point-particle dynamics, which itself is generalized by this theory, lead to new methods of wave manipulation, including asymmetric barriers for light.
This report demonstrates promising capabilities and performance characteristics of the proposed method using several power systems models. The new method will help to develop a new generation of highly efficient tools suitable for real-time parallel implementation. The ultimate benefit obtained will be early detection of system instability and prevention of system blackouts in real time.
Early work with rigid rod aromatic polyelectrolytes implied that steric hindrance in packing of the rigid rods left unoccupied volumes that could absorb and hold water molecules strongly. We called this “frozen in free volume). It is illustrated and contrasted with the packing of flexible backbone polyelectrolytes (Reference 5 of this report). This was quantified for poly(biphenylene disulfonic acid) (PBDSA) and poly(phenylene disulfonic acid) (PPDSA). We found that PPDSA held three water molecules per acid group down to 11% relative humidity (RH) and had very high conductivity even at these low RHs. (Reference 1 of report.) The frozen-in free volume was calculated to be equivalent to a λ of 3.5. The work reported below concentrated on studying these polymers and their copolymers with biphenylene disulfonic acid. As expected, the polyelectrolytes are water soluble. Several approaches towards making water stable films were studied. Grafting alkyl benzene substituents on sulfonic acid groups had worked for PBPDSA (1) so it was tried with PPDSA and a 20%/80% copolymer of BPDSA and PDSA (B20P80). T-butyl, n-octyl and n-dodecyl benzene were grafted. Good films could be made. Water absorption and conductivity were studied as a function of RH and temperature (Reference 2). When less than 20% of the sulfonic acid groups were grafted, conductivity was much higher than that of Nafion NR212 at all RHs. At low graft levels, conductivity was ten times higher. Mechanical properties and swelling were acceptable below 90% RH. However, all the films were unstable in water and slowly disintegrated. The proposed explanation was that the molecules formed nano-aggregates in solution held together by hydrophobic bonding. Their cast films disintegrated when placed in water since hydrophobic bonding between the nano-aggregates was poor. We then shifted to crosslinking as a method to produce water stable films (References 3 and 4). Biphenyl could easily be reacted with the polymer, generating biphenyl sulfone grafts. Films were cast and then crosslinked by heating to 210°C for at least one hour. There was no loss of acid groups even after heating at 225°C for two hours. PPDSA and B20P80 polymers were grafted and crosslinked. Conductivity and water absorption were measured on polymers with grafting degrees from 3 to 16%. As before they all had much higher conductivity than Nafion NR212. One sample was tested as a fuel cell membrane. Unfortunately it tore; the tear was mended with a 3M ionomer. There was some hydrogen leakage. However, the current at a given voltage was about 95% that of a Nafion NR212 membrane over the whole useful range. Considering that this was the first test for such a system, this is remarkable performance. A mechanically better membrane was tested at the end of the grant period. This did not have tears or micro cracks (Reference 5). Testing confirmed earlier data (Sergio Granados-Focil, Ph. D. Thesis, CWRU. 2006) that such very polar membranes were excellent barriers to hydrogen diffusion. Standard measurements showed no hydrogen leakage. This was confirmed by open circuit voltage measurements. They were higher than those of the Nafion NR212 cells. Again the single cell performance was about 95% that of the Nafion SR212 cell over the whole range. These films show great promise. They are very stable and perform very well at very low humidity. They should be able to outperform the present cells with relatively little further development. A second project is reported fully in the final report since it was not published. Its goal was to make membranes with high conductivity and good mechanical strength that would have a constant volume at all RHs. We made large planar 2-D polymers containing 1.5 nm holes lined with sulfonic acid groups. These should hold water very strongly. The largest made was calculated to have a number average diameter of 29 nm. It was expected that when they were cast, they would aggregate and create channels for proton conduction. However, they were so large that they aggregated in solution during preparation. Measurements showed that the aggregates developed long channels. This was demonstrated and is reported. Unfortunately, the aggregates could not be cast with the channels perpendicular to the film plane. If methods are developed to keep the molecules in solution until they are cast, their planes should be parallel and the channels perpendicular to the film direction. They could be very interesting and perhaps important materials.
Graphs are widely used to model relationships in a wide variety of domains such as sociology, bioinformatics, infrastructure, the WWW, to name a few. One of the key observations is that while real-world graphs are often globally sparse, they are locally dense. In other words, the average degree is often quite small (say at most 10 in a million vertex graph), but vertex neighborhoods are often dense. Finding dense subgraphs is a critical aspect of graph mining It has been used for finding communities and spam link farms in web graphs, graph visualization, real-time story identification, DNA motif detection in biological networks, finding correlated genes, epilepsy prediction, finding price value motifs in financial data, graph compression, distance query indexing, and increasing the throughput of social networking site servers. However, most standard formulations of this problem (like clique, quasi-clique, k-densest subgraph) are NP-hard. Furthermore, current dense subgraph finding algorithms usually optimize some objective, and only find a few such subgraphs without providing any structural relations, whereas the goal is rarely to find the "true optimum," but to identify many (if not all) dense substructures, understand their distribution in the graph, and ideally determine relationships among them. In this project, we first aim to devise algorithms and provide 3 implementations with nice visualizations to find the hierarchy between dense subgraphs, and then understand the structure of the hierarchy to gain more insight on the hidden patterns in real-world networks. Another important aspects in graph analysis is the temporal nature of networks. Networks evolve over time and in many applications data arrives at a high velocity, and thus it is important to design algorithms that can process data efficiently. We report three main results towards identifying dense structures in large evolving graphs. First, we will show how the hierarchical connectedness structure can be maintained efficiently, where connectedness is defined by increasing levels of connectivity strength. Next, we present dense structure can be identified in bipartite graphs without building projection graphs. And finally, we present a new method for peeling algorithms This new approach avoids sequential nature of peeling algorithms and is amenable to parallelization, which is crucial for processing high velocity data.
The need to solve block tridiagonal systems with hundreds or thousands of right-hand sides for the same block tridiagonal matrix is common in a variety of disciplines. To meet this need, the Accelerated Recursive Doubling Algorithm was developed. After a right-hand side independent phase, the algorithm allows for the quick, online calculation of solutions for different right-hand sides. In this work, we present methods to optimize the Accelerated Recursive Doubling Algorithm in memory usage and computation time in a hybrid parallelization model. The right-hand side independent phase of the naïve implementation takes ≥ 11/3 the amount of memory required to store the tridiagonal matrix, while our implementation reduces the fraction to ≈ 5/3 . The right-hand side dependent phase of the naïve implementation takes ≥ 6 times the amount of memory required to store the right-hand side, while our implementation reduces the fraction to ≈ 3. The computation time for the independent phase is reduced to ≈ 2/3 times that of the naïve implementation, while the computation time for the dependent phase is reduced to ≈ 5/9 . With increasing numbers of shared-memory threads q on every distributed processing element, we have O(q) theoretical speedup.
Accurate models of turbulent buoyant flows are essential for the design of nuclear reactors thermal hydraulics and passive safety systems. However, available models fail to fully capture the physics of turbulent mixing when buoyancy becomes predominant with respect to momentum. Therefore, high-fidelity experiments of well-controlled fundamental flows are needed to develop and validate more accurate models. We performed experiments of positive and negative turbulent buoyant jets, both in uniform and stratified environments, with the aim of understanding the thermal hydraulics of turbulent mixing with variable density and providing high-fidelity data for the development and validation of turbulence models. Non-intrusive, simultaneous Particle Image Velocimetry and Laser Induced Fluorescence measurements were carried out to acquire instantaneous velocity and concentration fields on a vertical section parallel to the axis of a jet in the self-similar region. The Refractive Index Matching method was applied to measure high-resolution buoyant jets with up to 8.6% density difference. These data are free of the typical errors that characterize optical measurements of buoyancy driven flows (e.g., natural and mixed convection) where the refractive index of the fluid is inhomogeneous throughout the measurement domain. Turbulent statistics and entrainment of buoyant jets in uniform and stratified environments are presented. These data are compared with non-buoyant jets in uniform environment, as a reference to investigate the effects of buoyancy and stratification on turbulent mixing. The results will be used for the assessment of current turbulence models and as basis for the development of a new one that captures turbulent mixing.
Disclosed herein is a massively parallel patterning tool for the deposition of single metals or metal alloys with size and composition control. Methods of the disclosure use a hydrogel array of pyramidal pen tips as a medium for localized electrodeposition, in conjunction with a scanning probe lithography platform and a three-electrode cell. This versatile technique can be used for high-throughput 3D printing, biomolecule patterning, or screening of catalyst nanoparticles or thin films.
The Super BigBite Spectrometer (SBS) program in Experimental Hall A of Jefferson Lab is a series of high-precision, large ?2 , electromagnetic form factor experiments. GMn and nTPE were the first two experiments of the SBS program and ran from Oc?tober 2021 through February 2022. Both experiments detect neutron-tagged ?(?, ???) and proton-tagged ?(?, ???) quasi-elastic electrons scattering from a deuterium tar?get. The GMn experiment is a measurement of the magnetic form factor of the neutron, ?? ?, via the ratio method over a ?2 range of 3.5 to 13.5 (GeV/c)2 . The nTPE experiment ran in-parallel with the GMn experiment and shared an overlap?ping kinematic point with GMn. nTPE extends the GMn experiment to assess the differences between Rosenbluth Slop and the single-photon exchange approximation. The nTPE experiment had two kinematic settings corresponding to different electron scatting angles at a fixed ?2 of 4.5 (GeV/c)? . Comparisons of nucleon form factor ratio measurements acquired through polarization transfer and LT separation reveal discrepancies as ?2 increases. Two-photon exchange is strongly favored as the reason for this discrepancy. ?? ? has been extracted at two kinematic settings corresponding to ?2 values of 3.0 and 4.5 (GeV/c)2 . Additionally, I will present an assessment of the differences between Rosenbluth Separation and single-photon exchange measure?ments.
We develop methods to calculate electron dynamics in crystalline solids in real-time time-dependent density functional theory employing exchange-correlation potentials which reproduce band gap energies of dielectrics; a meta-generalized gradient approximation was proposed by Tran and Blaha [Phys. Rev. Lett. 102, 226401 (2009)] (TBm-BJ) and a hybrid functional was proposed by Heyd, Scuseria, and Ernzerhof [J. Chem. Phys. 118, 8207 (2003)] (HSE). In time evolution calculations employing the TB-mBJ potential, we have found it necessary to adopt the predictor-corrector step for a stable time evolution. We have developed a method to evaluate electronic excitation energy without referring to the energy functional which is unknown for the TB-mBJ potential. For the HSE functional, we have developed a method for the operation of the Fock-like term in Fourier space to facilitate efficient use of massive parallel computers equipped with graphic processing units. We compare electronic excitations in silicon and germanium induced by femtosecond laser pulses using the TB-mBJ, HSE, and a simple local density approximation (LDA). At low laser intensities, electronic excitations are found to be sensitive to the band gap energy: they are close to each other using TB-mBJ and HSE and are much smaller in LDA. At high laser intensities close to the damage threshold, electronic excitation energies do not differ much among the three cases.
Algebraic multigrid (AMG) is often viewed as a scalable [Formula: see text] solver for sparse linear systems. Yet, AMG lacks parallel scalability due to increasingly large costs associated with communication, both in the initial construction of a multigrid hierarchy and in the iterative solve phase. This work introduces a parallel implementation of AMG that reduces the cost of communication, yielding improved parallel scalability. It is common in Message Passing Interface (MPI), particularly in the MPI-everywhere approach, to arrange inter-process communication, so that communication is transported regardless of the location of the send and receive processes. Performance tests show notable differences in the cost of intra- and internode communication, motivating a restructuring of communication. In this case, the communication schedule takes advantage of the less costly intra-node communication, reducing both the number and the size of internode messages. Node-centric communication extends to the range of components in both the setup and solve phase of AMG, yielding an increase in the weak and strong scaling of the entire method.
The extension of the capabilities of the pin-level nuclear reactor core thermal-hydraulics (T/H) code ESCOT to analyze hexagonal fueled cores and its performance are presented. ESCOT is an accurate yet fast core thermal-hydraulics solution aiming at high-fidelity and high-resolution multi-physics core analysis in the framework of massively parallel computing platforms. Its algorithm solution is based on the four-equation drift-flux model for two-phase calculations, these are numerically solved by applying the Finite Volume Method (FVM) and the Semi-Implicit Method for Pressure-Linked Equation (SIMPLE)-like algorithm in a staggered grid system. Constitutive models such as turbulent mixing, pressure drop, and vapor generation are employed to simulate key phenomena in subchannel-scale analysis. ESCOT is parallelized by a double (radial and axial) domain decomposition that enables its highly parallelized execution. The coupling of the code with the neutronics whole core solver for hexagonal geometries nTRACER is described. The newly implemented ESCOT features are validated by comparing single assembly and full core steady state nTRACER-ESCOT solutions with nTRACER standalone internal one-dimensional T/H solver results. The validation problems are based on the VVER 440 and VVER 1000 cores. ESCOT results show differences within an acceptable range with respect to the simple 1D nTRACER built-in solver. (authors)
In this paper, we describe an array-based hierarchical mesh refinement capability through uniform refinement of unstructured meshes for efficient solution of PDE's using finite element methods and multigrid solvers. A multi-degree, multi-dimensional and multi-level framework is designed to generate the nested hierarchies from an initial coarse mesh that can be used for a variety of purposes such as in multigrid solvers/preconditioners, to do solution convergence and verification studies and to improve overall parallel efficiency by decreasing I/O bandwidth requirements (by loading smaller meshes and in memory refinement). We also describe a high-order boundary reconstruction capability that can be used to project the new points after refinement using high-order approximations instead of linear projection in order to minimize and provide more control on geometrical errors introduced by curved boundaries.The capability is developed under the parallel unstructured mesh framework "Mesh Oriented dAtaBase" (MOAB Tautges et al. (2004)). We describe the underlying data structures and algorithms to generate such hierarchies in parallel and present numerical results for computational efficiency and effect on mesh quality. Furthermore, we also present results to demonstrate the applicability of the developed capability to study convergence properties of different point projection schemes for various mesh hierarchies and to a multigrid finite-element solver for elliptic problems.
Scientific workflows consist of multiple, connected applications, with data and results flowing from one to another in a pipeline. Traditionally, such workflows are executed in sequential order, storing intermediate data in storage disks. Co-scheduling application workflows concurrently on the same compute nodes would greatly reduce the cost of moving data to/from storage and allow real-time analysis of intermediate results. Nevertheless, most parallel programming runtimes do not allow seamless integration of various applications in a scientific workflow, in part due to the complexity of managing data and resources. The situation is even more complicated for heterogeneous systems. In this work we extend the Minos Computing Library (MCL) runtime to accelerate pipe-lined and parallel workloads where multiple applications are running in the same system. MCL’s asynchronous task library and runtime dynamically manages resources to allow co-scheduling of multiple processes sharing heterogeneous resources. In addition, we design a custom ex- tension of the Open Compute Language (OpenCL) to enable multiple processes to share device memory. We enable MCL to coordinate these shared buffers to allow for easy, fast data sharing between applications. Using malleable micro-benchmarks and two application workflows that combine scientific simulation and AI-based analysis, we show that our method outperforms traditional approaches.
As machine learning models continue to increase in complexity, so does the potential number of free model parameters commonly known as hyperparameters. While there has been considerable progress toward finding optimal configurations of these hyperparameters, many optimization procedures are treated as black boxes. We believe optimization methods should not only return a set of optimized hyperparameters, but also give insight into the effects of model hyperparameter settings. To this end, we present HyperSpace, a parallel implementation of Bayesian sequential model-based optimization. HyperSpace leverages high performance computing (HPC) resources to better understand unknown, potentially non-convex hyperparameter search spaces. We show that it is possible to learn the dependencies between model hyperparameters through the optimization process. By partitioning large search spaces and running many optimization procedures in parallel, we also show that it is possible to discover families of good hyperparameter settings over a variety of models including unsupervised clustering, regression, and classification tasks.
We describe the implementation of a module for the Athena magnetohydrodynamics (MHD) code that solves the time-independent, multi-frequency radiative transfer (RT) equation on multidimensional Cartesian simulation domains, including scattering and non-local thermodynamic equilibrium (LTE) effects. The module is based on well known and well tested algorithms developed for modeling stellar atmospheres, including the method of short characteristics to solve the RT equation, accelerated Lambda iteration to handle scattering and non-LTE effects, and parallelization via domain decomposition. The module serves several purposes: it can be used to generate spectra and images, to compute a variable Eddington tensor (VET) for full radiation MHD simulations, and to calculate the heating and cooling source terms in the MHD equations in flows where radiation pressure is small compared with gas pressure. For the latter case, the module is combined with the standard MHD integrators using operator splitting: we describe this approach in detail, including a new constraint on the time step for stability due to radiation diffusion modes. Implementation of the VET method for radiation pressure dominated flows is described in a companion paper. We present results from a suite of test problems for both the RT solver itself and for dynamical problems that include radiative heating and cooling. These tests demonstrate that the radiative transfer solution is accurate and confirm that the operator split method is stable, convergent, and efficient for problems of interest. We demonstrate there is no need to adopt ad hoc assumptions of questionable accuracy to solve RT problems in concert with MHD: the computational cost for our general-purpose module for simple (e.g., LTE gray) problems can be comparable to or less than a single time step of Athena's MHD integrators, and only few times more expensive than that for more general (non-LTE) problems.
Structure-preserving algorithms obtained via discrete variational principles exhibit strong promise for the calculation of guiding center test particle trajectories. The non-canonical Hamiltonian structure of the guiding center equations forms a novel and challenging context for geometric integration. To demonstrate the practical relevance of these methods, a prototypical variational midpoint algorithm is applied to an experimental magnetic equilibrium. The stability characteristics, conservation properties, and implementation requirements associated with the variational algorithms are addressed. Furthermore, computational run time is reduced for large numbers of particles by parallelizing the calculation on GPU hardware.