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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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At least 739 records · Page 41

Waste Treatment and Immobilization Plant, a Leader in the International Glass Community - 16003

The U.S. Department of Energy (DOE), Office of River Protection (ORP) is constructing the Tank Waste Treatment and Immobilization Plant (WTP) [1] to treat radioactive waste currently stored in underground tanks at the Hanford Site in Washington State. The WTP that is being designed to separate the tank waste into high-level waste (HLW) and low-activity waste (LAW) fractions with the majority of the mass (approximately 90 percent) directed to LAW and most of the activity (greater than 95 percent) directed to HLW. The pretreatment process, envisioned in the baseline, involves the dissolution of aluminum bearing solids to allow the aluminum salts to be processed through the cesium ion exchange and report to the LAW Facility. There is an oxidative leaching process to affect a similar outcome for chromium-bearing wastes. These two unit operations were advanced to accommodate shortcomings in glass formulation for HLW inventories. A significant consideration to the most recent revision of the glass models is the extensive collaboration developed, funded, managed, and coordinated from the ORP. The current effort includes researchers at the Pacific Northwest National Laboratory, Idaho National Laboratory, Savannah River National Laboratory, Brookhaven National Laboratory, Catholic University of America, Washington State University, Rutgers University, Institute of Chemical Technology Prague, University of Ottawa, Tokyo Institute of Technology, The University of Adelaide, and University of Sheffield. Independent technical evaluation having been solicited from faculty of Alfred University and Vanderbilt University. These advances in glass chemistry generate a need to revisit the feed vectors, flowsheet, and the unit operations driven by minimal waste loading requirements set forth in the contract for the design and construction of the plant. The current status and plans for the immediate future of glass chemistry are the subject of the primary concern to successfully completing our clean-up mission at Hanford. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Helical magnetic order and Fermi surface nesting in noncentrosymmetric ScFeGe

Here, an investigation of the structural, magnetic, thermodynamic, and charge transport properties of noncentrosymmetric hexagonal ScFeGe reveals it to be an anisotropic metal with a transition to a weak itinerant incommensurate helimagnetic state below T N =36 K. Neutron diffraction measurements discovered a temperature and field independent helical wave vector k = (0 0 0.193) with magnetic moments of 0.53 μ B per Fe confined to the ab-plane. Density functional theory calculations are consistent with these measurements and find several bands that cross the Fermi level along the c-axis with a nearly degenerate set of flat bands just above the Fermi energy. The anisotropy found in the electrical transport is reflected in the calculated Fermi surface, which consists of several warped flat sheets along the c-axis with two regions of significant nesting, one of which has a wave vector that closely matches that found in the neutron diffraction. The electronic structure calculations, along with a strong anomaly in the c-axis conductivity at TN, signal a Fermi surface driven magnetic transition, similar to that found in spin density wave materials. Magnetic fields applied in the ab-plane result in a metamagnetic transition with a threshold field of ≈ 6.7 T along with a sharp, strongly temperature dependent discontinuity and a change in sign of the magnetoresistance for in-plane currents. Thus, ScFeGe is an ideal system to investigate the effect of in-plane magnetic fields on a helimagnet with a c-axis propagation vector, where the relative strength of the magnetic interactions and anisotropies determine the topology and magnetic structure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Constraints on Wildfire Smoke Source Strength, Injection Height, and Particle Evolution

Aerosol sources are represented in climate and air quality models with an injection height and a source strength. We have applied a combination of Multi-angle Imaging SpectroRadiometer (MISR) and MODerate resolution Imaging Spectroradiometer (MODIS) observations to help constrain these two key model variables for wildfire smoke plumes. Injection height is obtained from MISR stereo imagery, which makes it possible to map plume elevation and estimate the associated motion vectors at plume altitude near-source, where contrast features in the plume can be identified in the multi-angle views. A current limitation of injection-height mapping is the relatively narrow MISR swath width (~380 km) and 10:30 AM equator crossing time on the day side of Earth. However, upcoming missions, as well as advanced imagers on geostationary platforms, promise to greatly expand the spatial and temporal range over which this technique can be applied. We estimate source strength by matching forward-simulated plume aerosol optical depth (AOD) from models with AOD snapshots retrieved from MODIS observations. This technique works best for large, isolated plumes common in boreal forest, and tends to fail where plume AOD is low and/or background AOD, distinct from the specific source of interest, is high. These two approaches for constraining aerosol modeling with satellite observations have been the subject of ongoing AeroCom/AeroSat studies by our group. A third effort applies the combination of MISR plume heights, wind vectors, and particle microphysical property constraints to infer smoke-plume particle evolution processes and timescales, including the emission and subsequent evolution of black and brown smoke. In this presentation, we will provide an update on the status of these efforts.

wildfire↗

A generalized plasma dispersion function for electron damping in tokamak plasmas

Radio frequency wave propagation in finite temperature, magnetized plasmas exhibits a wide range of physics phenomena. The plasma response is nonlocal in space and time, and numerous modes are possible with the potential for mode conversions and transformations. Additionally, diffraction effects are important due to finite wavelength and finite-size wave launchers. Multidimensional simulations are required to describe these phenomena, but even with this complexity, the fundamental plasma response is assumed to be the uniform plasma response with the assumption that the local plasma current for a Fourier mode can be described by the Stix conductivity. But, for plasmas with non-uniform magnetic fields, the wave vector itself is nonlocal. When resolved into components perpendicular (k ) and parallel (k ||) to the magnetic field, locality of the parallel component can easily be violated when the wavelength is large. The impact of this inconsistency is that estimates of the wave damping can be incorrect (typically low) due to unresolved resonances. For the case of ion cyclotron damping, this issue has already been addressed by including the effect of parallel magnetic field gradients. In this case, a modified plasma response (Z function) allows resonance broadening even when k || = 0, and this improves the convergence and accuracy of wave simulations. In our paper, we extend this formalism to include electron damping and find improved convergence and accuracy for parameters where electron damping is dominant, such as high harmonic fast wave heating in the NSTX-U tokamak, and helicon wave launch for off-axis current drive in the DIII-D tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Thermal Stress Reduction in Power Switching Devices Using Distributed Loss PWM Concept for Current Source Inverters

A new modulation scheme is proposed for current source inverters (CSIs) that reduces the variation and peak junction temperature in the CSIs' power devices. The distributed loss pulse-width modulation (DLM) concept is introduced and applied to traditional space vector modulation methods to develop modified modulation schemes that reduce the thermal stress on power devices. The device junction temperatures resulting from conventional and DLM schemes are compared. Simulation and experimental results confirm that the proposed DLM concept reduces thermal stress on the devices while maintaining the same high output current waveform quality compared to traditional CSI modulation schemes. The CSI power device lifetime (i.e., the number of cycles to failure) are estimated using the simulation and experimental results. The proposed DLM significantly increases the device lifetime (by 5 to 6 times) by reducing the junction temperature variation compared to the conventional modulations.

42 ENGINEERING↗

Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective

Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both prognostic and therapeutic purposes has exploded thanks to increasing availability of electronic data and genomics. One promising direction that medical modeling is moving toward is adopting the same machine learning methods used by companies such as Google and Facebook to combat disease. Broadly defined, machine learning is a branch of computer science that deals with making predictions from complex data through statistical models. These methods serve to uncover patterns in data and are actively used in areas such as speech recognition, handwriting recognition, face recognition, “spam” filtering (junk email), and targeted advertising. Although multiple radiation oncology research groups have shown the value of applied machine learning (ML), clinical adoption has been slow due to the high barrier to understanding these complex models by clinicians. Here, we present a review of the use of ML to predict radiation therapy outcomes from the clinician's point of view with the hope that it lowers the “barrier to entry” for those without formal training in ML. We begin by describing 7 principles that one should consider when evaluating (or creating) an ML model in radiation oncology. We next introduce 3 popular ML methods—logistic regression (LR), support vector machine (SVM), and artificial neural network (ANN)—and critique 3 seminal papers in the context of these principles. Although current studies are in exploratory stages, the overall methodology has progressively matured, and the field is ready for larger-scale further investigation.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

A Machine Learning based Approach of Estimating Equivalent Circuit Model Parameters at Different SoCs of Li-ion Batteries from Voltage Relaxation

Abstract: In this study, an approach of estimating the equivalent circuit model (ECM) parameters for Li-ion batteries (LIBs) is proposed based on the voltage value at different intervals while relaxing the LIB after discharge. The typical approach for estimating ECM parameters of a LIB is to conduct electrochemical impedance spectroscopy (EIS) measurements at different frequencies and fit them to a predefined circuit model, which requires additional measuring arrangements and specialized devices. The proposed methodology utilizes four different voltages at 0s, 60s, 360s, and 1800s alongside the specific state of charge (SoC) value for a specific constant discharge current value of ~1C until the relaxation stage to train and evaluate three regression-based machine learning models— Support Vector Regression (SVR), Extreme Gradient Boosting (XGBoost), and Gaussian Process Regression (GPR)—for estimating the ECM parameters of the selected model. Bayesian optimization is employed for hyperparameter tuning to achieve optimal performance for all the regressor models, among which, the GPR provided the best performance with the root-mean-squared error (RMSE) of less than 4x10-4 on average for the resistive components and less than 0.27 for capacitive components with excellent R2 scores. The simplicity of the approach enables it to eliminate the need for sophisticated measuring equipment and computation power.

Sagar, Md. Samiul [The University of Alabama (UA)]↗

Lepton Pair Production in Neutrino–Nucleus Scattering

The impact of the emission of new light gauge bosons in neutrino–nucleus scattering on the observed signal is studied. As an example, a model with a neutral vector boson Z {sup ′} with a mass of a few tens of MeV, interacting with neutrinos via the V−A current, is considered. An equivalent Z {sup ′} boson spectrum for neutrinos is introduced. The corresponding correction to the total neutrino–nucleus scattering cross section as a function of the collision energy is calculated. This correction for several values of the model parameters allowed by the existing experimental bounds is presented.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Aperture synthesis using orbiting telescopes

A study was carried out to determine the feasibility, with current technology, of performing aperture synthesis using two telescopes orbiting the earth in coordinated orbits separated by approximately 10 m to 1 km. The objective was to determine whether there is a practical alternative to a very large, deployed, servo-controlled submillimeter telescope (i.e., the Large Deployable Reflector) for obtaining high-resolution submillimeter images of astronomical sources. It is found that suitable classes of orbits exist which can provide good UV coverage over the entire sky and the real-time correlation of wideband signals can be performed in orbit using current technology. The most difficult task appears to be the real-time determination of the orientation of the baseline vector in a stable coordinate system. A plausible scheme has been identified for the determination of an arbitrary direction to within 0.003 arcsec in an astrometric coordinate system. This scheme not only makes submillimeter interferometric image reconstruction possible but should also have numerous other applications.

Kuiper, T. B. H.↗

Unified control/structure design and modeling research

To demonstrate the applicability of the control theory for distributed systems to large flexible space structures, research was focused on a model of a space antenna which consists of a rigid hub, flexible ribs, and a mesh reflecting surface. The space antenna model used is discussed along with the finite element approximation of the distributed model. The basic control problem is to design an optimal or near-optimal compensator to suppress the linear vibrations and rigid-body displacements of the structure. The application of an infinite dimensional Linear Quadratic Gaussian (LQG) control theory to flexible structure is discussed. Two basic approaches for robustness enhancement were investigated: loop transfer recovery and sensitivity optimization. A third approach synthesized from elements of these two basic approaches is currently under development. The control driven finite element approximation of flexible structures is discussed. Three sets of finite element basic vectors for computing functional control gains are compared. The possibility of constructing a finite element scheme to approximate the infinite dimensional Hamiltonian system directly, instead of indirectly is discussed.

Mingori, D. L.↗

Probe Compensation in Cylindrical Near-Field Scanning: A Novel Simulation Methodology

Probe pattern compensation is essential in near-field scanning geometry, where there is a greatneed to accurately know far-field pattern at wide angular range. This paper focuses on a novelformulation and computer simulation to determine the precise need for and effect of probecompensation in cylindrical near-field scanning. The methodology is applied to a linear test arrayantenna and the NASA scatterometer radar antenna. The formulation is based on representing theprobe (circular aperture) by its equivalent tangential magnetic currents. The interaction between theprobe equivalent aperture currents and the test antenna fields is obtained with the application ofreciprocity theorem. This allows us to obtain the probe vector output pickup integral which isproportional to the amplitude and phase of the electric field induced in the probe aperture with respectto its position to the test antenna.

Rahmat-Samii, Y↗

Roofline Analysis in the Intel® Advisor to Deliver Optimized Performance for applications on Intel® Xeon Phi™ Processor

In this session we show, in two case studies, how the roofline feature of Intel Advisor has been utilized to optimize the performance of kernels of the XGC1 and PICSAR codes in preparation for Intel Knights Landing architecture. The impact of the implemented optimizations and the benefits of using the automatic roofline feature of Intel Advisor to study performance of large applications will be presented. This demonstrates an effective optimization strategy that has enabled these science applications to achieve up to 4.6 times speed-up and prepare for future exascale architectures. # Goal/Relevance of Session The roofline model [1,2] is a powerful tool for analyzing the performance of applications with respect to the theoretical peak achievable on a given computer architecture. It allows one to graphically represent the performance of an application in terms of operational intensity, i.e. the ratio of flops performed and bytes moved from memory in order to guide optimization efforts. Given the scale and complexity of modern science applications, it can often be a tedious task for the user to perform the analysis on the level of functions or loops to identify where performance gains can be made. With new Intel tools, it is now possible to automate this task, as well as base the estimates of peak performance on measurements rather than vendor specifications. The goal of this session is to demonstrate how the roofline feature of Intel Advisor can be used to balance memory vs. computation related optimization efforts and effectively identify performance bottlenecks. A series of typical optimization techniques: cache blocking, structure refactoring, data alignment, and vectorization illustrated by the kernel cases will be addressed. # Description of the codes ## XGC1 The XGC1 code [3] is a magnetic fusion Particle-In-Cell code that uses an unstructured mesh for its Poisson solver that allows it to accurately resolve the edge plasma of a magnetic fusion device. After recent optimizations to its collision kernel [4], most of the computing time is spent in the electron push (pushe) kernel, where these optimization efforts have been focused. The kernel code scaled well with MPI+OpenMP but had almost no automatic compiler vectorization, in part due to indirect memory addresses and in part due to low trip counts of low-level loops that would be candidates for vectorization. Particle blocking and sorting have been implemented to increase trip counts of low-level loops and improve memory locality, and OpenMP directives have been added to vectorize compute-intensive loops that were identified by Advisor. The optimizations have improved the performance of the pushe kernel 2x on Haswell processors and 1.7x on KNL. The KNL node-for-node performance has been brought to within 30% of a NERSC Cori phase I Haswell node and we expect to bridge this gap by reducing the memory footprint of compute intensive routines to improve cache reuse. ## PICSAR is a Fortran/Python high-performance Particle-In-Cell library targeting at MIC architectures first designed to be coupled with the PIC code WARP for the simulation of laser-matter interaction and particle accelerators. PICSAR also contains a FORTRAN stand-alone kernel for performance studies and benchmarks. A MPI domain decomposition is used between NUMA domains and a tile decomposition (cache-blocking) handled by OpenMP has been added for shared-memory parallelism and better cache management. The so-called current deposition and field gathering steps that compose the PIC time loop constitute major hotspots that have been rewritten to enable more efficient vectorization. Particle communications between tiles and MPI domain has been merged and parallelized. All considered, these improvements provide speedups of 3.1 for order 1 and 4.6 for order 3 interpolation shape factors on KNL configured in SNC4 quadrant flat mode. Performance is similar between a node of cori phase 1 and KNL at order 1 and better on KNL by a factor 1.6 at order 3 with the considered test case (homogeneous thermal plasma).

97 MATHEMATICS AND COMPUTING↗

Scattering of dark particles with light mediators

We present a treatment of the high energy scattering of dark Dirac fermions from nuclei, mediated by the exchange of a light vector boson. The dark fermions are produced by proton-nucleus interactions in a fixed target and, after traversing shielding that screens out strongly interacting products, appear similarly to neutrino neutral current scattering in a detector. Using the Fermilab experiment E613 as an example, we place limits on a secluded dark matter scenario. Visible scattering in the detector includes both the familiar regime of large momentum transfer to the nucleus (Q 2 ) described by deeply inelastic scattering, as well as small Q 2 kinematics described by the exchanged vector mediator fluctuating into a quark-antiquark pair whose interaction with the nucleus is described by a saturation model. Here, we find that the improved description of the low Q 2 scattering leads to important corrections, resulting in more robust constraints in a regime where a description entirely in terms of deeply inelastic scattering cannot be trusted.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Nonlinear electromagnetic formulation for particle-in-cell simulation of lower hybrid waves in toroidal geometry

An electromagnetic particle simulation model has been formulated and verified for nonlinear processes of lower hybrid (LH) waves in fusion plasmas. Electron dynamics are described by the drift kinetic equation using either kinetic momentum or canonical momentum. Ion dynamics are treated as the fluid system or by the Vlasov equation. Compressible magnetic perturbation is retained to simulate both the fast and slow LH waves. Numerical properties are greatly improved by using the electron continuity equation to enforce the consistency between electrostatic potential and vector potential, and by using the importance sampling scheme. The simulation model has been implemented in the gyrokinetic toroidal code (GTC), and verified for the dispersion relation and nonlinear particle trapping of the electromagnetic LH waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multisensor monitoring of deforestation in the Guinea Highlands of West Africa

Multiple remote sensing systems were used to assess deforestation in the Guinea Highlands (Fouta Djallon) of West Africa. Sensor systems included: (1) historical (1953) and current (1989) aerial mapping photography; (2) current large-scale, small format (35mm) aerial photography; (3) current aerial video imagery; and (4) historical (1973) and recent (1985) LANDSAT MSS. Photographic and video data were manually interpreted and incorporated in a vector-based geographic information system (GIS). LANDSAT data were digitally classified. General results showed an increase in permanent and shifting agriculture over the past 35 years. This finding is consistent with hypothesized strategies to increase agricultural production through a shortening of the fallow period in areas of shifting cultivation. However, results also show that the total area of both permanent and shifting agriculture had expanded at the expense of natural vegetation and an increase in erosion. Although sequential LANDSAT MSS cannot be used in this region to accurately map land over, the location, direction and magnitude of changes can be detected in relative terms. Historical and current aerial photography can be used to map agricultural land use changes with some accuracy. Video imagery is useful as ancillary data for mapping vegetation. The most prudent approach to mapping deforestation would incorporate a multistage approach based on these sensors.

Gilruth, Peter T.↗

Improving the Communication Pattern in Matrix-Vector Operations for Large Scale-Free Graphs by Disaggregation

Matrix-vector multiplication is the key operation in any Krylov-subspace iteration method. We are interested in Krylov methods applied to problems associated with the graph Laplacian arising from large scale-free graphs. Furthermore, computations with graphs of this type on parallel distributed-memory computers are challenging. This is due to the fact that scale-free graphs have a degree distribution that follows a power law, and currently available graph partitioners are not efficient for such an irregular degree distribution. The lack of a good partitioning leads to excessive interprocessor communication requirements during every matrix-vector product. Here, we present an approach to alleviate this problem based on embedding the original irregular graph into a more regular one by disaggregating (splitting up) vertices in the original graph. The matrix-vector operations for the original graph are performed via a factored triple matrix-vector product involving the embedding graph. And even though the latter graph is larger, we are able to decrease the communication requirements considerably and improve the performance of the matrix-vector product.

97 MATHEMATICS AND COMPUTING↗

Virtual sensor supervised learning for cyber-attack neutralization

An industrial asset may have monitoring nodes that generate current monitoring node values. A dynamic, resilient estimator may split a temporal monitoring node space into normal and one or more abnormal subspaces associated with different kinds of attack vectors. According to some embodiments, a neutralization model is constructed and trained for each attack vector using supervised learning and the associated abnormal subspace. In other embodiments, a single model is created using out-of-range values for abnormal monitoring nodes. Responsive to an indication of a particular abnormal monitoring node or nodes, the system may automatically invoke the appropriate neutralization model to determine estimated values of the particular abnormal monitoring node or nodes (e.g., by selecting the correct model or using out-of-range values). The series of current monitoring node values from the abnormal monitoring node or nodes may then be replaced with the estimated values.

97 MATHEMATICS AND COMPUTING↗

Vector interaction enhanced bag model for astrophysical applications

For quark matter studies in astrophysics the thermodynamic bag model (tdBAG) has been widely used. Despite its success it fails to account for various phenomena expected from QCD. We suggest a straightforward extension of tdBAG in order to take the dynamical breaking of chiral symmetry and the influence of vector interactions explicitly into account. As for tdBAG the model mimics confinement in a phenomenological approach. It is based on an analysis of the Nambu–Jona-Lasinio (NJL) model at finite density. Furthermore, we demonstrate how NJL and bag models in this regime follow from the more general and QCD-based framework of the Dyson–Schwinger equations in a medium by assuming simple gluon contact interaction. Based on our simple and novel model, we construct quark hadron hybrid equations of state and systematically study chiral and deconfinement phase transitions, the appearance of s-quarks, and the role of vector interaction. We further study these aspects for matter in β-equilibrium at zero temperature, with particular focus on the current ∼2 M{sub ⊙} maximum mass constraint for neutron stars. Our approach indicates that the currently only theoretical evidence for the hypothesis of stable strange matter is an artifact of tdBAG and results from neglecting the dynamical breaking of chiral symmetry.

79 ASTRONOMY AND ASTROPHYSICS↗