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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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NASA NTRS2014

Badger COMET Compartmentalized Onboard Material Extrusion Technology

In response to the 2014 NASA Academic Innovation Challenge, the University of Wisconsin – Madison team presents the design of a collapsible Fused Deposition Modeling (FDM) system for in situ manufacturing in a space habitat environment, the Badger Compartmentalized Onboard Material Extrusion Technology (COMET). The proposed mechanism incorporates one year of design and testing on an array of current additive manufacturing techniques, with the goal of providing a reliable and maintainable manufacturing solution. Seven Level 1 requirements were employed to guide the design process, based on information in the challenge, communications with NASA, and the evolving systems feedback of project work groups. These requirements provided a baseline for the development of the System Requirements Document (SRD, Appendix I), which framed the design of the system. The design requirements deemed critical to the success of the systems are as follows: - The system shall compose an FDM workstation capable of producing parts within industry standard tolerances. - The system shall reduce to a minimum of 50 percent or less of its deployed volume when not in use, and must collapse without the need for disassembly. - The system shall meet all relevant NASA safety and functional standards. The final design for the Badger COMET was selected from multiple design iterations, which balanced the critical design requirements listed above with system reliability, with the final goal of providing a minimal system weight. The system collapses in the vertical direction, allowing for a maximum reduction in volume. Guide rods and precision, anti-backlash lead screws provide all linear movement in the device. Stepper motors were chosen to actuate each system axis, due to their high precision and repeatable accuracy. The system is controlled through an on-board computer system and embedded electronics package.

Frederick T. Elder↗
DOE OSTI2022

Multistage mixed precision iterative refinement

Abstract Low precision arithmetic, in particular half precision (16‐bit) floating point arithmetic, is now available in commercial hardware. Using lower precision can offer significant savings in computation and communication costs with proportional savings in energy. Motivated by this, there has been a renewed interest in mixed precision iterative refinement schemes for solving linear systems , and new variants of GMRES‐based iterative refinement have been developed. Each particular variant with a given combination of precisions leads to different condition number‐based constraints for convergence of the backward and forward errors, and each has different performance costs. The constraints for convergence given in the literature are, as an artifact of the analyses, often overly strict in practice, and thus could lead a user to select a more expensive variant when a less expensive one would have sufficed. In this work, we develop a multistage mixed precision iterative refinement solver which aims to combine existing mixed precision approaches to balance performance and accuracy and improve usability. For a user‐specified initial combination of precisions, the algorithm begins with the least expensive approach and convergence is monitored via inexpensive computations with quantities produced during the iteration. If slow convergence or divergence is detected using particular stopping criteria, the algorithm switches to use a more expensive, but more reliable variant. A novel aspect of our approach is that, unlike existing implementations, our algorithm first attempts to use “stronger” GMRES‐based solvers for the solution update before resorting to increasing the precision(s). In some scenarios, this can avoid the need to refactorize the matrix in higher precision. We perform extensive numerical experiments on a variety of random dense problems and problems from real applications which confirm the benefits of the multistage approach.

Oktay, Eda↗
DOE OSTI2014

Electron kinetic effects on interferometry, polarimetry and Thomson scattering measurements in burning plasmas (invited)

At anticipated high electron temperatures in ITER, the effects of electron thermal motion on Thomson scattering (TS), toroidal interferometer/polarimeter (TIP), and poloidal polarimeter (PoPola) diagnostics will be significant and must be accurately treated. The precision of the previous lowest order linear in τ = T{sub e}/m{sub e}c{sup 2} model may be insufficient; we present a more precise model with τ{sup 2}-order corrections to satisfy the high accuracy required for ITER TIP and PoPola diagnostics. The linear model is extended from Maxwellian to a more general class of anisotropic electron distributions that allows us to take into account distortions caused by equilibrium current, ECRH, and RF current drive effects. The classical problem of the degree of polarization of incoherent Thomson scattered radiation is solved analytically exactly without any approximations for the full range of incident polarizations, scattering angles, and electron thermal motion from non-relativistic to ultra-relativistic. The results are discussed in the context of the possible use of the polarization properties of Thomson scattered light as a method of T{sub e} measurement relevant to ITER operational scenarios.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2014

WE-D-BRF-05: Quantitative Dual-Energy CT Imaging for Proton Stopping Power Computation

Purpose: To extend the two-parameter separable basis-vector model (BVM) to estimation of proton stopping power from dual-energy CT (DECT) imaging. Methods: BVM assumes that the photon cross sections of any unknown material can be represented as a linear combination of the corresponding quantities for two bracketing basis materials. We show that both the electron density (ρe) and mean excitation energy (Iex) can be modeled by BVM, enabling stopping power to be estimated from the Bethe-Bloch equation. We have implemented an idealized post-processing dual energy imaging (pDECT) simulation consisting of monogenetic 45 keV and 80 keV scanning beams with polystyrene-water and water-CaCl2 solution basis pairs for soft tissues and bony tissues, respectively. The coefficients of 24 standard ICRU tissue compositions were estimated by pDECT. The corresponding ρe, Iex, and stopping power tables were evaluated via BVM and compared to tabulated ICRU 44 reference values. Results: BVM-based pDECT was found to estimate ρe and Iex with average and maximum errors of 0.5% and 2%, respectively, for the 24 tissues. Proton stopping power values at 175 MeV, show average/maximum errors of 0.8%/1.4%. For adipose, muscle and bone, these errors result range prediction accuracies less than 1%. Conclusion: A new two-parameter separable DECT model (BVM) for estimating proton stopping power was developed. Compared to competing parametric fit DECT models, BVM has the comparable prediction accuracy without necessitating iterative solution of nonlinear equations or a sample-dependent empirical relationship between effective atomic number and Iex. Based on the proton BVM, an efficient iterative statistical DECT reconstruction model is under development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2016

TU-H-BRA-04: A Novel Superconducting Magnet Design for Optimized Patient Access and Minimal SSD for Use in a Linac-MR Hybrid

Purpose: A prototype rotating hybrid MR imaging system and linac has been developed to allow for simultaneous imaging and radiation delivery parallel to B{sub 0}. However, the design of a compact magnet capable of rotation in a small vault with sufficient patient access and a typical clinical source-to-surface distance (SSD) is challenging. This work presents a novel superconducting magnet design that allows for a reduced SSD and ample patient access by moving the superconducting coils to the side of the yoke. The yoke and pole-plate structures are shaped to direct the magnetic flux appropriately. Methods: The surface of the pole plate for the magnet assembly is optimized. The magnetic field calculations required in this work are performed with the 3D finite element method software package Opera-3D. Each tentative design strategy is virtually modeled in this software package and externally controlled by MATLAB, with its key geometries defined as variables. The particle swarm optimization algorithm is used to optimize the variables subject to the minimization of a cost function. At each iteration, Opera-3D will solve the magnetic field solution over a field-of-view suitable for MR imaging and the degree of field uniformity will be assessed to calculate the value of the cost function associated with that iteration. Results: An optimized magnet assembly that generates a homogenous 0.2T magnetic field over an ellipsoid with large axis of 30 cm and small axes of 20 cm is obtained. Conclusion: The distinct features of this model are the minimal distance between the yoke’s top and the isocentre and the improved patient access. On the other hand, having homogeneity over an ellipsoid give us a larger field-of-view, essential for geometric accuracy of the MRI system. The increase of B{sub 0} from 0.2T in the present model to 0.5T is the subject of future work. Funding Sources: Alberta Innovates - Health Solutions (AIHS)| Disclosure and Conflict of Interest: B. Gino Fallone is a co-founder and CEO of MagnetTx Oncology Solutions (under discussions to license Alberta biplanar linac MR for commercialization).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Hybrid Multiscale Finite Volume Method for Advection-Diffusion Equations Subject to Heterogeneous Reactive Boundary Conditions

We present a hybrid scheme for the coupling of macro and microscale continuum models for reactive contaminant transport in fractured and porous media. The transport model considered is the advection-dispersion equation, subject to linear heterogeneous reactive boundary conditions. The Multiscale Finite Volume method (MsFV) is employed to define an approximation to the microscale concentration field defined in terms of macroscopic or \emph{global} degrees of freedom, together with local interpolator and corrector functions capturing microscopic spatial variability. The macroscopic mass balance relations for the MsFV global degrees of freedom are coupled with the macroscopic model, resulting in a global problem for the simultaneous time-stepping of all macroscopic degrees of freedom throughout the domain. In order to perform the hybrid coupling, the micro and macroscale models are applied over overlapping subdomains of the simulation domain, with the overlap denoted as the handshake subdomain $\Omega^{hs}$, over which continuity of concentration and transport fluxes between models is enforced. Continuity of concentration is enforced by posing a restriction relation between models over $\Omega^{hs}$. Continuity of fluxes is enforced by prolongating the macroscopic model fluxes across the boundary of $\Omega^{hs}$ to microscopic resolution. The microscopic interpolator and corrector functions are solutions to local microscopic advection-diffusion problems decoupled from the global degrees of freedom and from each other by virtue of the MsFV decoupling ansatz. The error introduced by the decoupling ansatz is reduced iteratively by the preconditioned GMRES algorithm, with the hybrid MsFV operator serving as the preconditioner.

Barajas-Solano, David A.↗
DOE OSTI2016

MO-AB-BRA-01: A Global Level Set Based Formulation for Volumetric Modulated Arc Therapy

Purpose: The current clinical Volumetric Modulated Arc Therapy (VMAT) optimization is formulated as a non-convex problem and various greedy heuristics have been employed for an empirical solution, jeopardizing plan consistency and quality. We introduce a novel global direct aperture optimization method for VMAT to overcome these limitations. Methods: The global VMAT (gVMAT) planning was formulated as an optimization problem with an L2-norm fidelity term and an anisotropic total variation term. A level set function was used to describe the aperture shapes and adjacent aperture shapes were penalized to control MLC motion range. An alternating optimization strategy was implemented to solve the fluence intensity and aperture shapes simultaneously. Single arc gVMAT plans, utilizing 180 beams with 2° angular resolution, were generated for a glioblastoma multiforme (GBM), lung (LNG), and 2 head and neck cases—one with 3 PTVs (H&N3PTV) and one with 4 PTVs (H&N4PTV). The plans were compared against the clinical VMAT (cVMAT) plans utilizing two overlapping coplanar arcs. Results: The optimization of the gVMAT plans had converged within 600 iterations. gVMAT reduced the average max and mean OAR dose by 6.59% and 7.45% of the prescription dose. Reductions in max dose and mean dose were as high as 14.5 Gy in the LNG case and 15.3 Gy in the H&N3PTV case. PTV coverages (D95, D98, D99) were within 0.25% of the prescription dose. By globally considering all beams, the gVMAT optimizer allowed some beams to deliver higher intensities, yielding a dose distribution that resembles a static beam IMRT plan with beam orientation optimization. Conclusions: The novel VMAT approach allows for the search of an optimal plan in the global solution space and generates deliverable apertures directly. The single arc VMAT approach fully utilizes the digital linacs’ capability in dose rate and gantry rotation speed modulation. Varian Medical Systems, NIH grant R01CA188300, NIH grant R43CA183390.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Breaking Computational Barriers: Real-time Analysis and Optimization with Large-scale Nonlinear Models via Model Reduction

Model reduction for dynamical systems is a promising approach for reducing the computational cost of large-scale physics-based simulations to enable high-fidelity models to be used in many- query (e.g., Bayesian inference) and near-real-time (e.g., fast-turnaround simulation) contexts. While model reduction works well for specialized problems such as linear time-invariant systems, it is much more difficult to obtain accurate, stable, and efficient reduced-order models (ROMs) for systems with general nonlinearities. This report describes several advances that enable nonlinear reduced-order models (ROMs) to be deployed in a variety of time-critical settings. First, we present an error bound for the Gauss-Newton with Approximated Tensors (GNAT) nonlinear model reduction technique. This bound allows the state-space error for the GNAT method to be quantified when applied with the backward Euler time-integration scheme. Second, we present a methodology for preserving classical Lagrangian structure in nonlinear model reduction. This technique guarantees that important properties--such as energy conservation and symplectic time-evolution maps--are preserved when performing model reduction for models described by a Lagrangian formalism (e.g., molecular dynamics, structural dynamics). Third, we present a novel technique for decreasing the temporal complexity --defined as the number of Newton-like iterations performed over the course of the simulation--by exploiting time-domain data. Fourth, we describe a novel method for refining projection-based reduced-order models a posteriori using a goal-oriented framework similar to mesh-adaptive h -refinement in finite elements. The technique allows the ROM to generate arbitrarily accurate solutions, thereby providing the ROM with a 'failsafe' mechanism in the event of insufficient training data. Finally, we present the reduced-order model error surrogate (ROMES) method for statistically quantifying reduced- order-model errors. This enables ROMs to be rigorously incorporated in uncertainty-quantification settings, as the error model can be treated as a source of epistemic uncertainty. This work was completed as part of a Truman Fellowship appointment. We note that much additional work was performed as part of the Fellowship. One salient project is the development of the Trilinos-based model-reduction software module Razor , which is currently bundled with the Albany PDE code and currently allows nonlinear reduced-order models to be constructed for any application supported in Albany. Other important projects include the following: 1. ROMES-equipped ROMs for Bayesian inference: K. Carlberg, M. Drohmann, F. Lu (Lawrence Berkeley National Laboratory), M. Morzfeld (Lawrence Berkeley National Laboratory). 2. ROM-enabled Krylov-subspace recycling: K. Carlberg, V. Forstall (University of Maryland), P. Tsuji, R. Tuminaro. 3. A pseudo balanced POD method using only dual snapshots: K. Carlberg, M. Sarovar. 4. An analysis of discrete v. continuous optimality in nonlinear model reduction: K. Carlberg, M. Barone, H. Antil (George Mason University). Journal articles for these projects are in progress at the time of this writing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

SU-E-T-270: Diffusion Synthetic Acceleration for Linear Boltzmann Transport Equation

Purpose: Linear Boltzmann transport equation (LBTE) is as accurate as the Monte Carlo method (MC) for dose calculation in photon/particle therapy (LBTE is a deterministic and Eulerian formulation and MC is a statistical and Lagrangian description). An advantage of LBTE is that numerous acceleration techniques can be utilized for acceleration. This work is to explore the acceleration of LBTE via diffusion synthetic acceleration (DSA). Methods: For simplicity, two-dimensional, steady-state, and within-group LBTE is considered with two angular dimensions and two spatial dimensions. The discrete ordinate method is developed for solving this integro-differential equation. The angular variables are discretized using a level-symmetric quadrature set on the unit sphere. The spatial variables are discretized on the structured grid based on the diamond scheme. The source-iteration method (SI) is used to solve the discretized system.Since SI is slow in optically thick and highly scattering regime. DSA is developed to accelerate SI. The motivation for DSA is that diffusion equation (DE) is a good approximation of LBTE in the above regime. However, DE is much cheaper than LBTE computationally since DE only involves spatial variables. Thus, in each DSA iteration, DSA adds to the SI step a computationally-negligible DE step, i.e., to first solve DE with the SI residual as source term, and then compensate the SI solution with DE solution. Results: DSA was benchmarked and compared with SI. The difference between two methods was within 0.12% which verifies the accuracy of DSA, while DSA demonstrated the great advantage in speed, e.g., the reduction of iteration number to 6% and 4% respectively for cases with 100 and 1,000 scattering-absorption ratio that commonly occur in clinical dose calculation. Conclusion: DSA has been developed as one of many possible means for accelerating the numerical solver of LBTE for dose calculation. The authors were partially supported by the NSFC (#11405105), the 973 Program (#2015CB856000) and the Shanghai Pujiang Talent Program (#14PJ1404500)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

A Full Multigrid Method for the Self-Adjoint Angular Flux Equation Based on Cellwise Block Jacobi Iteration

Previous work by Densmore et al. has demonstrated that multigrid methods for the self-adjoint angular flux (SAAF) equation with cellwise block Jacobi smoothing can be extremely effective at solving for the angular flux in one dimension. The extension of that work to two dimensions demonstrated that while the smoother works well, the use of a direct coarse-grid approximation can severely limit the rate of convergence for optically thin cells. In that paper, this convergence limit was evaded through the use of a partially Galerkin coarse-grid approximation. However, relying on a Galerkin coarse-grid approximation is not ideal as constructing the coarse-grid discretization in this approach is complicated. The motivation for this summary is to find a method that can work without the need for a Galerkin coarse-grid approximation. The Full Multigrid (FMG) method is well known as a method that can theoretically solve a problem to its discretization accuracy with optimal linear computational complexity, that is in just O(N) operations for N unknowns. Indeed, we develop an FMG method for the 2-D SAAF equation that yields discretization accuracy and does not require the use of a Galerkin coarse-grid approximation. Until recently, aside from proofs about the order of the error for FMG, little work had been done in quantifying when and how FMG can obtain discretization accuracy. However, recent work by Rodrigo et al. has introduced a Fourier analysis technique called worst-case right-hand side analysis used to calculate the FMG accuracy measure. The FMG accuracy measure is the upper bound on the constant of proportionality between the error of the FMG solution and the discretization error. In this summary, we develop and implement an FMG method for the 2-D Cartesian SAAF equations. We then perform worst-case right-hand side analysis and give numerical examples that demonstrate under what circumstances the method can solve the 2-D SAAF equations to discretization accuracy, for optically thin cells, without the need for a Galerkin coarse-grid approximation. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Discontinuous Finite Element Quasidiffusion Methods

Here in this paper, two-level methods for solving transport problems in one-dimensional slab geometry based on the quasi-diffusion (QD) method are developed. A linear discontinuous finite element method (LDFEM) is derived for the spatial discretization of the low-order QD (LOQD) equations. It involves special interface conditions at the cell edges based on the idea of QD boundary conditions (BCs). We consider different kinds of QD BCs to formulate the necessary cell-interface conditions. We develop two-level methods with independent discretization of the high-order transport equation and LOQD equations, where the transport equation is discretized using the method of characteristics and the LDFEM is applied to the LOQD equations. We also formulate closures that lead to the discretization consistent with a LDFEM discretization of the transport equation. The proposed methods are studied by means of test problems formulated with the method of manufactured solutions. Numerical experiments are presented demonstrating the performance of the proposed methods. Lastly, we also show that the method with independent discretization has the asymptotic diffusion limit.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Design and Analysis of the US ITER Central Solenoid Module Lifting Fixture

The central solenoid (CS) consists of six large high field superconducting magnets (also known as modules) approximately 4 m in diameter and 2 m tall that weigh approximately 120 tonnes each. These large and complex modules create challenges during assembly of the CS that require the development of custom assembly tooling such as the CS lifting fixture. The CS module lifting fixture is designed to lift and stack the six CS modules in the assembly building on the ITER site. Because of its unique design, fabrication, and assembly features, no lifting attachments could be incorporated within or under the CS modules. This limitation motivated the development of a friction-based lift fixture. The design and evaluation of the CS module lifting fixture considered both worker safety and investment protection, and the assessments were performed to international codes and standards. The CS module lifting fixture consists of two principal subassemblies: spider assembly and ring weldment. These subassemblies allow the frictional force to be augmented by the mechanical advantage of shallow-angle wedges. Large radial preloads created by both screw jack assemblies and the weight of a CS module develop frictional forces capable of performing a lift with a safety factor of at least 2. The design effort resulted in the use of low friction linear bearings on angle surfaces to ensure constant pressure, integrated jacks for pretensioning the fixture prior to lifting, and load pin strain gauges for monitoring the normal force. Testing of various materials and surface treatments led to the selection of laminated aluminum and rubber pads as the friction interface on the CS lifting fixture side and a grit-blasted Nitronic 50 stainless steel band on the CS module side. A redundant lifting method using the module slings between the spider and module is also utilized after the initial friction lift. The CS lifting fixture provides a safe and reliable solution for lifting and stacking the CS module during assembly.

Morris, Eric↗
DOE OSTI2025

Leveraging operator learning to accelerate convergence of the preconditioned conjugate gradient method

We propose a new deflation strategy to accelerate the convergence of the preconditioned conjugate gradient (PCG) method for solving parametric large-scale linear systems of equations. Unlike traditional deflation techniques that rely on eigenvector approximations or recycled Krylov subspaces, we generate the deflation subspaces using operator learning, specifically the Deep Operator Network (DeepONet). To this aim, we introduce two complementary approaches for assembling the deflation operators. The first approach approximates near-null space vectors of the discrete PDE operator using the basis functions learned by the DeepONet. The second approach directly leverages solutions predicted by the DeepONet. To further enhance convergence, we also propose several strategies for prescribing the sparsity pattern of the deflation operator. Here, a comprehensive set of numerical experiments encompassing steady-state, time-dependent, scalar, and vector-valued problems posed on both structured and unstructured geometries is presented and demonstrates the effectiveness of the proposed DeepONet-based deflated PCG method, as well as its generalization across a wide range of model parameters and problem resolutions.

Deflation↗
DOE OSTI2016

Uranium and strontium fate in waste-weathered sediments: Scaling of molecular processes to predict reactive transport

Objectives of the project: 1. Determine the process coupling that occurs between mineral transformation and contaminant (U and Sr) speciation in acid-uranium waste weathered Hanford sediments. 2. Establish linkages between molecular-scale contaminant speciation and meso-scale contaminant lability, release and reactive transport. 3. Make conjunctive use of molecular- to bench-scale data to constrain the development of a mechanistic, reactive transport model that includes coupling of contaminant sorption-desorption and mineral transformation reactions. Hypotheses tested: - Uranium and strontium speciation in legacy sediments from the U-8 and U-12 Crib sites can be reproduced in bench-scale weathering experiments conducted on unimpacted Hanford sediments from the same formations. - Reactive transport modeling of future uranium and strontium releases from the vadose zone of acid-waste weathered sediments can be effectively constrained by combining molecular-scale information on contaminant bonding environment with grain-scale information on contaminant phase partitioning, and meso-scale kinetic data on contaminant release from the waste-weathered porous media. - Although field contamination and laboratory experiments differ in their diagenetic time scales (decades for field vs. months to years for lab), sediment dissolution, neophase nucleation, and crystal growth reactions that occur during the initial disequilibrium induced by waste-sediment interaction leave a strong imprint that persists over subsequent longer-term equilibration time scales and, therefore, give rise to long-term memory effects. Enabling capabilities developed: Our team developed an iterative measure-model approach that is broadly applicable to elucidate the mechanistic underpinnings of reactive contaminant transport in geomedia subject to active weathering. Experimental design: Hypotheses were tested by comparing (with a similar set of techniques) the geochemical transformations and transport behaviors that occured in bench-scale studies of waste-sediment interaction with parallel model systems studies of homogeneous nucleation and neo-phase dissolution. Initial plans were to compare results with core sample extractions from the acid uranium waste impacted U-8 and U-12 Cribs at Hanford (see original proposal and letter of collaboration from J. Zachara). However, this part of the project was impossible because funding for core extractions were eliminated from the DoE budget. Three distinct crib waste aqueous simulants (whose composition is based on the most up-to-date information from field site investigations) were reacted with Hanford sediments in batch and column systems. Coupling of contaminant uptake to mineral weathering was monitored using a suite of methods both during waste-sediment interaction, and after, when waste-weathered sediments were subjected to infusion with circumneutral background pore water solutions. Our research was designed to adapt as needed to maintain a strong dialogue between laboratory and modeling investigations so that model development was increasingly constrained by emergent data and understanding. Potential impact of the project to DOE: Better prediction of contaminant uranium transport was achieved by employing multi-faceted lines of inquiry to build a strong bridge between molecular- and field-scale information. By focusing multiple lines and scales of observation on a common experimental design, our collaborative team revealed non-linear and emergent behavior in contaminated weathering systems. A goal of the current project was to expand our modeling capabilities, originally focused on hyperalkaline legacy waste streams, to include acidic weathering reactions that, as described above, were expected to result in profoundly different products. We were able to achieve this goal, and showed that these products nonetheless undergo analogous silicate and non-silicate transformation, ripening and aging processes. Our prediction that these weathering reactions would vary with waste stimulant chemistry resulted in data that was incorporated directly into a reactive transport model structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

SU-E-T-295: Simultaneous Beam Sampling and Aperture Shape Optimization for Station Parameter Optimized Radiation Therapy (SPORT)

Purpose: Station Parameter Optimized Radiation Therapy (SPORT) was recently proposed to fully utilize the technical capability of emerging digital LINACs, in which the station parameters of a delivery system, (such as aperture shape and weight, couch position/angle, gantry/collimator angle) are optimized altogether. SPORT promises to deliver unprecedented radiation dose distributions efficiently, yet there does not exist any optimization algorithm to implement it. The purpose of this work is to propose an optimization algorithm to simultaneously optimize the beam sampling and aperture shapes. Methods: We build a mathematical model whose variables are beam angles (including non-coplanar and/or even nonisocentric beams) and aperture shapes. To solve the resulting large scale optimization problem, we devise an exact, convergent and fast optimization algorithm by integrating three advanced optimization techniques named column generation, gradient method, and pattern search. Column generation is used to find a good set of aperture shapes as an initial solution by adding apertures sequentially. Then we apply the gradient method to iteratively improve the current solution by reshaping the aperture shapes and updating the beam angles toward the gradient. Algorithm continues by pattern search method to explore the part of the search space that cannot be reached by the gradient method. Results: The proposed technique is applied to a series of patient cases and significantly improves the plan quality. In a head-and-neck case, for example, the left parotid gland mean-dose, brainstem max-dose, spinal cord max-dose, and mandible mean-dose are reduced by 10%, 7%, 24% and 12% respectively, compared to the conventional VMAT plan while maintaining the same PTV coverage. Conclusion: Combined use of column generation, gradient search and pattern search algorithms provide an effective way to optimize simultaneously the large collection of station parameters and significantly improves quality of resultant treatment plans as compared with conventional VMAT or IMRT treatments.

07 ISOTOPE AND RADIATION SOURCES↗
NASA NTRS2010

Fast Solution in Sparse LDA for Binary Classification

An algorithm that performs sparse linear discriminant analysis (Sparse-LDA) finds near-optimal solutions in far less time than the prior art when specialized to binary classification (of 2 classes). Sparse-LDA is a type of feature- or variable- selection problem with numerous applications in statistics, machine learning, computer vision, computational finance, operations research, and bio-informatics. Because of its combinatorial nature, feature- or variable-selection problems are NP-hard or computationally intractable in cases involving more than 30 variables or features. Therefore, one typically seeks approximate solutions by means of greedy search algorithms. The prior Sparse-LDA algorithm was a greedy algorithm that considered the best variable or feature to add/ delete to/ from its subsets in order to maximally discriminate between multiple classes of data. The present algorithm is designed for the special but prevalent case of 2-class or binary classification (e.g. 1 vs. 0, functioning vs. malfunctioning, or change versus no change). The present algorithm provides near-optimal solutions on large real-world datasets having hundreds or even thousands of variables or features (e.g. selecting the fewest wavelength bands in a hyperspectral sensor to do terrain classification) and does so in typical computation times of minutes as compared to days or weeks as taken by the prior art. Sparse LDA requires solving generalized eigenvalue problems for a large number of variable subsets (represented by the submatrices of the input within-class and between-class covariance matrices). In the general (fullrank) case, the amount of computation scales at least cubically with the number of variables and thus the size of the problems that can be solved is limited accordingly. However, in binary classification, the principal eigenvalues can be found using a special analytic formula, without resorting to costly iterative techniques. The present algorithm exploits this analytic form along with the inherent sequential nature of greedy search itself. Together this enables the use of highly-efficient partitioned-matrix-inverse techniques that result in large speedups of computation in both the forward-selection and backward-elimination stages of greedy algorithms in general.

Moghaddam, Baback↗
NASA NTRS1998

Transition in Turbine Flows

We have further developed our capabilities to analyze transition in turbine boundary layers from first principles by integrating the nonlinear parabolized stability equations (PSE) with improved initial and boundary conditions. With modified iteration schemes, we are able to proceed deeper into the transition region where skin friction coefficient and heat transfer coefficient significantly increase. Initial and boundary conditions at elevated turbulence levels can be derived by receptivity analysis. Test runs for ERCOFTAC test case T3A at 2.4\% turbulence level provide results in good agreement with the experimental data. The sharper minimum of the skin coefficient also shown by DNS results is likely due to the missing intermittency. The method has been applied to various experimentally studied turbine blades (UTRC, VKI, Zierke, Langston, Hippensteele, and others). The PSE results, though physically reasonable, do not agree as well as expected with the experimental findings. We have, therefore, performed an extensive search for the reasons of the seemingly systematic deviations. A first source of uncertainty has been found in the often insufficient documentation of the experiments (e.g. on blockage by end-wall boundary layers). However, variation of the relevant parameters does not lead to more satisfactory agreement. A second reason has been found in the "standard procedure" which considers a 2D flow at midspan and uses a panel code and subsequent boundary-layer code to obtain the laminar basic flow for the transition analysis. Comparison with the pressure distribution obtained with a 3D design code (RVC3D) shows significant three-dimensionality of the flow (e.g. in the UTRC experiments). The spanwise variation has been neglected in our original PSE code. To overcome this problem, we have developed the PSE/3D for fully 3D boundary layers to account for streamwise and spanwise variations. Since the design code does not provide the boundary-layer flow with sufficient resolution, we have generated the Euler solution and employed a 3D boundary-layer code to obtain the viscous basic flow. Although only the linear stability level of PSE/3D has been implemented so far, the discrepancies with the experiments change but do not disappear. We still find deviations between the computed and experimental variations of C(sub f), and St along the blade for laminar flow. The main reason can be seen by comparing the solution of the boundary-layer code with the viscous results of the design code. The conventional boundary-layer solution exhibits an asymptotic behavior appropriate in external aerodynamics but does not match the steep gradients of the inviscid flow through the passage and consequently provides biased results for C(sub f), and St. An attempt is currently being made to correct this deficiency. Before attempting to perform the transition analysis for the viscous flow provided by the design code, we have analyzed the implementation and "best possible" results. Code and results exhibit flaws that may negatively affect the design and are intolerable for transition analysis. Therefore, we have decided to develop a new code to obtain a reliable basis for stability and transition studies. We expect to report improved results by the time of the meeting.

Herbert, Thorwald↗
NASA NTRS2014

Data-Intensive Science meets Inquiry-Driven Pedagogy: Interactive Big Data Exploration, Threshold Concepts, and Liminality

Threshold concepts in any discipline are the core concepts an individual must understand in order to master a discipline. By their very nature, these concepts are troublesome, irreversible, integrative, bounded, discursive, and reconstitutive. Although grasping threshold concepts can be extremely challenging for each learner as s/he moves through stages of cognitive development relative to a given discipline, the learner's grasp of these concepts determines the extent to which s/he is prepared to work competently and creatively within the field itself. The movement of individuals from a state of ignorance of these core concepts to one of mastery occurs not along a linear path but in iterative cycles of knowledge creation and adjustment in liminal spaces - conceptual spaces through which learners move from the vaguest awareness of concepts to mastery, accompanied by understanding of their relevance, connectivity, and usefulness relative to questions and constructs in a given discipline. For example, challenges in the teaching and learning of atmospheric science can be traced to threshold concepts in fluid dynamics. In particular, Dynamic Meteorology is one of the most challenging courses for graduate students and undergraduates majoring in Atmospheric Science. Dynamic Meteorology introduces threshold concepts - those that prove troublesome for the majority of students but that are essential, associated with fundamental relationships between forces and motion in the atmosphere and requiring the application of basic classical statics, dynamics, and thermodynamic principles to the three dimensionally varying atmospheric structure. With the explosive growth of data available in atmospheric science, driven largely by satellite Earth observations and high-resolution numerical simulations, paradigms such as that of dataintensive science have emerged. These paradigm shifts are based on the growing realization that current infrastructure, tools and processes will not allow us to analyze and fully utilize the complex and voluminous data that is being gathered. In this emerging paradigm, the scientific discovery process is driven by knowledge extracted from large volumes of data. In this presentation, we contend that this paradigm naturally lends to inquiry-driven pedagogy where knowledge is discovered through inductive engagement with large volumes of data rather than reached through traditional, deductive, hypothesis-driven analyses. In particular, data-intensive techniques married with an inductive methodology allow for exploration on a scale that is not possible in the traditional classroom with its typical problem sets and static, limited data samples. In addition, we identify existing gaps and possible solutions for addressing the infrastructure and tools as well as a pedagogical framework through which to implement this inductive approach.

Ramachandran, Rahul↗