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DOE OSTI2023

Preserving Superconvergence of Spectral Elements for Curved Domains via $h$ and $p$-Geometric Refinement

Spectral element methods (SEM), extensions of finite element methods (FEM), have emerged as significant techniques for solving partial differential equations in physics and engineering. SEM can potentially deliver superior accuracy due to the potential superconvergence in nodal solutions for well-shaped tensor-product elements. However, the accuracy of SEM often degrades in complex geometries due to geometric inaccuracies near curved boundaries and the loss of superconvergence with simplicial or non-tensor-product elements. To overcome the first issue, we propose using h- and p-geometric refinement, which refines the mesh near high-curvature regions and increases the degree of geometric basis functions, respectively. We show that when using mixed-element meshes with tensor-product elements in the interior of the domain, curvature-based geometric refinement near boundaries can improve the accuracy of the interior elements by reducing pollution errors and preserving the superconvergence in nodal solutions. To address the second issue, we introduce a post-processing technique using the adaptive extended stencil finite element method (AES-FEM) to recover the accuracy near the curved boundaries. The combination of curvature-based geometric refinement and accurate post-processing offers an effective and easier-to-implement alternative to methods reliant on exact geometries. We demonstrate our techniques by solving the convection-diffusion equation in 2D and show up to two orders of magnitude of improvement in the solution accuracy, even when the elements are poorly shaped near boundaries.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Preserving Superconvergence of Spectral Elements for Curved Domains

Spectral element methods (SEM), extensions of finite element methods (FEM), have emerged as significant techniques for solving partial differential equations in physics and engineering. SEM can potentially deliver superior accuracy due to the potential superconvergence in nodal solutions for well-shaped tensor-product elements. However, the accuracy of SEM often degrades in complex geometries due to geometric inaccuracies near curved boundaries and the loss of superconvergence with simplicial or non-tensor-product elements. To overcome the first issue, we propose using geometric refinement, which both refines the mesh near high-curvature regions and increases the degree of geometric basis functions. We show that when using mixed-element meshes with tensor-product elements in the interior of the domain, curvature-based geometric refinement near boundaries can improve the accuracy of the interior elements by reducing pollution errors and preserving the superconvergence in nodal solutions. To address the second issue, we introduce ApSEM, a post-processing technique using the adaptive extended stencil finite element method (AES-FEM) to recover the accuracy near the curved boundaries. The combination of curvature-based geometric refinement and accurate post-processing offers an effective and easier-to-implement alternative to methods reliant on exact geometries. We demonstrate our techniques by solving the convection-diffusion equation in 2D and 3D and show up to two orders of magnitude of improvement in the solution accuracy, even when the elements are poorly shaped near boundaries. We also show the efficiency of ApSEM as it can recover superconvergence in nodal solutions without drastically increasing the computational cost.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

New adaptive method to optimize the secondary reflector of linear Fresnel collectors

Performance of linear Fresnel collectors may largely depend on the secondary-reflector profile design when small-aperture absorbers are used. Optimization of the secondary-reflector profile is an extremely challenging task because there is no established theory to ensure superior performance of derived profiles. In this work, an innovative optimization method is proposed to optimize the secondary-reflector profile of a generic linear Fresnel configuration. The method correctly and accurately captures impacts of both geometric and optical aspects of a linear Fresnel collector to secondary-reflector design. The proposed method is an adaptive approach that does not assume a secondary shape of any particular form, but rather, starts at a single edge point and adaptively constructs the next surface point to maximize the reflected power to be reflected to absorber(s). As a test case, the proposed optimization method is applied to an industrial linear Fresnel configuration, and the results show that the derived optimal secondary reflector is able to redirect more than 90% of the power to the absorber in a wide range of incidence angles. Here, the proposed method can be naturally extended to other types of solar collectors as well, and it will be a valuable tool for solar-collector designs with a secondary reflector.

14 SOLAR ENERGY↗

DOE OSTI2014

SU-D-17A-01: Geometric and Dosimetric Evaluation of a 4D-CBCT Reconstruction Technique Using Prior Knowledge

Purpose: To evaluate a 4D-CBCT reconstruction technique both geometrically and dosimetrically Methods: A prior-knowledge guided 4DC-BCT reconstruction method named the motion-modeling and free-form deformation (MM-FD) has been developed. MM-FD views each phase of the 4D-CBCT as a deformation of a prior CT volume. The deformation field is first solved by principal component analysis based motion modeling, followed by constrained free-form deformation.The 4D digital extended-cardiac- torso (XCAT) phantom was used for comprehensive evaluation. Based on a simulated 4D planning CT of a lung patient, 8 different scenarios were simulated to cover the typical on-board anatomical and respiratory variations: (1) synchronized and (2) unsynchronized motion amplitude change for body and tumor; tumor (3) shrinkage and (4) expansion; tumor average position shift in (5) superior-inferior (SI) direction, (6) anterior-posterior (AP) direction and (7) SI, AP and lateral directions altogether; and (8) tumor phase shift relative to the respiratory cycle of the body. Orthogonal-view 30° projections were simulated based on the eight patient scenarios to reconstruct on-board 4D-CBCTs. For geometric evaluation, the volume-percentage-difference (VPD) was calculated to assess the volumetric differences between the reconstructed and the ground-truth tumor.For dosimetric evaluation, a gated treatment plan was designed for the prior 4D-CT. The dose distributions were calculated on the reconstructed 4D-CBCTs and the ground-truth images for comparison. The MM-FD technique was compared with MM-only and FD-only techniques. Results: The average (±s.d.) VPD values of reconstructed tumors for MM-only, FDonly and MM-FD methods were 59.16%(± 26.66%), 75.98%(± 27.21%) and 5.22%(± 2.12%), respectively. The average min/max/mean dose (normalized to prescription) of the reconstructed tumors by MM-only, FD-only, MM-FD methods and ground-truth tumors were 78.0%/122.2%/108.2%, 13%/117.7%/86%, 58.1%/120.8%/103.6% and 57.6%/118.6%/101.8%,respectively. Conclusion: The MM-FD method provides superior reconstruction accuracy both geometrically and dosimetrically, which can potentially be used for 4D target localization, dose tracking and adaptive radiation therapy. This research is supported by grant from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

HPGMG

HPGMG is a scalable reimplementation of miniGMG (see previous software disclosure) and is a compact geometric multigrid (MG benchmark designed to proxy the performance characteristics of the solves found in adaptive mesh refinement multigrid (AMR MG) applications. It solves the equation a*alpha*u - b div beta grad u = f on a large cubical domain using cell-centered values and either homogenous dirichlet or periodic boundaries. a and b are scalar constants, alpha and beta are space varying constants, f is the right hand side, and u is the solution. The cubical domain is divided into cubical subdomains which are distributed across the supercomputer. Whereas miniGMG enforced a static spatial decomposition across all levels in the MG V-cycle, HPGMG is free to redistribute data at each level including the possibility of moving all data to a single process (memory permitting). Thus, where miniGMG's U-cycle demanded a coarse grid solve across the entire supercomputer (a performance bottleneck), HPGMG can avoid this by combining distributed data and continuing the V-cycle. Technically, HPGMG can still implement a U-cycle or a Krylov bottom solve, but this solve can now be done on a global problem of only 2^3-8^3 cells. Additionally, HPGMG supports the MG F-cycle which avoids the iterative process of the v-cycle with a direct approach that can reach the discretization error in one pass. This provides a substantial performance boosts and opens avenues for exploiting systems that include hierarchical memories or heterogeneous processors. Like miniGMG, the righthand side f in HPGMG is generated from a continuous function for u. Thus, one can solve.

Williams, Samuel↗

DOE OSTI2013

miniGMG

miniGMG is a compact geometric multigrid (MG benchmark designed to proxy the performance characteristics of the solves found in adaptive mesh refinement multigrid (AMR MG) applications. It solves the equation a*alpha*u - b div beta grad u = f on a large cubical domain using cell-centered values and periodic boundaries. a and b are scalar constants, alpha and beta are space varying constants, f is the right hand side, and u is the solution. The cubical domain is divided into cubical subdomains which are distributed across the supercomputer. The righthand side f is generated from a continuous function for u. Thus, one can solve this linear system of equations and verify the error properties of the discrete solution u by comparing to a sampling of the continuous u. miniGMG implements both v- and f- cycles, as well as two constant coeffficient discretications of the equation above (one 27pt 2nd order, and one 13pt 4th order). In both cases, the (embedded) v-cycles are truncated when a subdomain reaces 4^3, 2^3, or 1^3 cells (a u-cycle). The multigrd solver then swtiches to one of seven coarse grid (bottom) solves. relaxation, BiCGStab, CABiCGStab, TelescopingCABiCGStab, CG, or CACG. The code exploits two forms of communication-avoiding. The first is exemplified by the referenced SC'12 paper in which DRAM data movment is avoided when smoothing. The second, described in the IPDPS'14 paper avoids collectives in a bottom solve (the CA bottom solves). There are a number of implementations of the operators for both CPUs and NVIDIA GPUs. The CPUs have been optimized to exploit a wavefront approach to communication-avoiding. The GPU versions include a number of optimized and tunable implementations. The code has been demonstrated to scale to 46K nodes on the BGQ Mira (750K cores), 9K nodes on Edison (111K cores), and 14K GPUs on Titan (37M cuda cores). It thus acts as a scalable testbed for a wide range of computer science and applied math research. Nominally, one invokes the benchmark as ./run b x y z alpha beta gamma Each subdomain is (2^b)^3 cells Each MPI process receives a x-by-y-by-z collection of subdomains. There are alpha*beta*gamma total MPI processes For correctness (a cubical domain), *alpha==y*beta==z*gamma.

Williams, Sameul↗

DOE OSTI2022

Manifold Learning-Based Polynomial Chaos Expansions for High-Dimensional Surrogate Models

In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantities of interest of the computational or analytical model. For this purpose, we employ Grassmannian diffusion maps, a two-step nonlinear dimension reduction technique which allows us to reduce the dimensionality of the data and identify meaningful geometric descriptions in a parsimonious and inexpensive manner. Polynomial chaos expansion is then used to construct a mapping between the stochastic input parameters and the diffusion coordinates of the reduced space. An adaptive clustering technique is proposed to identify an optimal number of clusters of points in the latent space. The similarity of points allows us to construct a number of geometric harmonic emulators which are finally utilized as a set of inexpensive pretrained models to perform an inverse map of realizations of latent features to the ambient space and thus perform accurate out-of-sample predictions. Thus, the proposed method acts as an encoder-decoder system which is able to automatically handle very high-dimensional data while simultaneously operating successfully in the small-data regime. The method is demonstrated on two benchmark problems and on a system of advection-diffusion-reaction equations which model a first-order chemical reaction between two species. In all test cases, the proposed method is able to achieve highly accurate approximations which ultimately lead to the significant acceleration of UQ tasks.

42 ENGINEERING↗

NASA NTRS1994

A Cartesian, cell-based approach for adaptively-refined solutions of the Euler and Navier-Stokes equations

A Cartesian, cell-based approach for adaptively-refined solutions of the Euler and Navier-Stokes equations in two dimensions is developed and tested. Grids about geometrically complicated bodies are generated automatically, by recursive subdivision of a single Cartesian cell encompassing the entire flow domain. Where the resulting cells intersect bodies, N-sided 'cut' cells are created using polygon-clipping algorithms. The grid is stored in a binary-tree structure which provides a natural means of obtaining cell-to-cell connectivity and of carrying out solution-adaptive mesh refinement. The Euler and Navier-Stokes equations are solved on the resulting grids using a finite-volume formulation. The convective terms are upwinded: a gradient-limited, linear reconstruction of the primitive variables is performed, providing input states to an approximate Riemann solver for computing the fluxes between neighboring cells. The more robust of a series of viscous flux functions is used to provide the viscous fluxes at the cell interfaces. Adaptively-refined solutions of the Navier-Stokes equations using the Cartesian, cell-based approach are obtained and compared to theory, experiment, and other accepted computational results for a series of low and moderate Reynolds number flows.

Coirier, William J.↗

NASA NTRS1995

A Cartesian, cell-based approach for adaptively-refined solutions of the Euler and Navier-Stokes equations

A Cartesian, cell-based approach for adaptively-refined solutions of the Euler and Navier-Stokes equations in two dimensions is developed and tested. Grids about geometrically complicated bodies are generated automatically, by recursive subdivision of a single Cartesian cell encompassing the entire flow domain. Where the resulting cells intersect bodies, N-sided 'cut' cells are created using polygon-clipping algorithms. The grid is stored in a binary-tree data structure which provides a natural means of obtaining cell-to-cell connectivity and of carrying out solution-adaptive mesh refinement. The Euler and Navier-Stokes equations are solved on the resulting grids using a finite-volume formulation. The convective terms are upwinded: A gradient-limited, linear reconstruction of the primitive variables is performed, providing input states to an approximate Riemann solver for computing the fluxes between neighboring cells. The more robust of a series of viscous flux functions is used to provide the viscous fluxes at the cell interfaces. Adaptively-refined solutions of the Navier-Stokes equations using the Cartesian, cell-based approach are obtained and compared to theory, experiment and other accepted computational results for a series of low and moderate Reynolds number flows.

Coirier, William J.↗

NASA NTRS1975

An adaptive maneuvering logic computer program for the simulation of one-to-one air-to-air combat. Volume 2: Program description

A detailed description is presented of the computer programs in order to provide an understanding of the mathematical and geometrical relationships as implemented in the programs. The individual sbbroutines and their underlying mathematical relationships are described, and the required input data and the output provided by the program are explained. The relationship of the adaptive maneuvering logic program with the program to drive the differential maneuvering simulator is discussed.

Burgin, G. H.↗

DOE OSTI2013

Novel multimodality segmentation using level sets and Jensen-Rényi divergence

Purpose: Positron emission tomography (PET) is playing an increasing role in radiotherapy treatment planning. However, despite progress, robust algorithms for PET and multimodal image segmentation are still lacking, especially if the algorithm were extended to image-guided and adaptive radiotherapy (IGART). This work presents a novel multimodality segmentation algorithm using the Jensen-Rényi divergence (JRD) to evolve the geometric level set contour. The algorithm offers improved noise tolerance which is particularly applicable to segmentation of regions found in PET and cone-beam computed tomography. Methods: A steepest gradient ascent optimization method is used in conjunction with the JRD and a level set active contour to iteratively evolve a contour to partition an image based on statistical divergence of the intensity histograms. The algorithm is evaluated using PET scans of pharyngolaryngeal squamous cell carcinoma with the corresponding histological reference. The multimodality extension of the algorithm is evaluated using 22 PET/CT scans of patients with lung carcinoma and a physical phantom scanned under varying image quality conditions. Results: The average concordance index (CI) of the JRD segmentation of the PET images was 0.56 with an average classification error of 65%. The segmentation of the lung carcinoma images had a maximum diameter relative error of 63%, 19.5%, and 14.8% when using CT, PET, and combined PET/CT images, respectively. The estimated maximal diameters of the gross tumor volume (GTV) showed a high correlation with the macroscopically determined maximal diameters, with aR{sup 2} value of 0.85 and 0.88 using the PET and PET/CT images, respectively. Results from the physical phantom show that the JRD is more robust to image noise compared to mutual information and region growing. Conclusions: The JRD has shown improved noise tolerance compared to mutual information for the purpose of PET image segmentation. Presented is a flexible framework for multimodal image segmentation that can incorporate a large number of inputs efficiently for IGART.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2016

TH-AB-202-05: BEST IN PHYSICS (JOINT IMAGING-THERAPY): First Online Ultrasound-Guided MLC Tracking for Real-Time Motion Compensation in Radiotherapy

Purpose: While MLC tracking has been successfully used for motion compensation of moving targets, current real-time target localization methods rely on correlation models with x-ray imaging or implanted electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging yields volumetric data in real-time (4D) without ionizing radiation. We report the first results of online 4D ultrasound-guided MLC tracking in a phantom. Methods: A real-time tracking framework was installed on a 4D ultrasound station (Vivid7 dimension, GE) and used to detect a 2mm spherical lead marker inside a water tank. The volumetric frame rate was 21.3Hz (47ms). The marker was rigidly attached to a motion stage programmed to reproduce nine tumor trajectories (five prostate, four lung). The 3D marker position from ultrasound was used for real-time MLC aperture adaption. The tracking system latency was measured and compensated by prediction for lung trajectories. To measure geometric accuracy, anterior and lateral conformal fields with 10cm circular aperture were delivered for each trajectory. The tracking error was measured as the difference between marker position and MLC aperture in continuous portal imaging. For dosimetric evaluation, 358° VMAT fields were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using a 3%/3 mm γ-test. Results: The tracking system latency was 170ms. The mean root-mean-square tracking error was 1.01mm (0.75mm prostate, 1.33mm lung). Tracking reduced the mean γ-failure rate from 13.9% to 4.6% for prostate and from 21.8% to 0.6% for lung with high-modulation VMAT plans and from 5% (prostate) and 18% (lung) to 0% with low modulation. Conclusion: Real-time ultrasound tracking was successfully integrated with MLC tracking for the first time and showed similar accuracy and latency as other methods while holding the potential to measure target motion non-invasively. SI was supported by the Graduate School for Computing in Medicine and Life Science, German Excellence Initiative [grant DFG GSC 235/1].

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Spatially Accelerated Winding Numbers for Curved Geometry

The generalized winding number (GWN) is a scalar field that supports robust containment queries on curved geometry, including non-watertight, overlapping, and nested boundary representations. While queries can be easily parallelized over samples, direct evaluation on parametric curves and surfaces remains costly for large and complex models. Fast, state-of-the-art GWN approaches leverage a spatial index to approximate the GWN, typically coupled with a Taylor expansion which approximates the GWN contribution for far clusters of geometric primitives. However, such methods operate only on discrete inputs such as triangle meshes and point clouds, and would introduce containment errors near boundaries if applied to curved input. We extend support for fast GWN evaluation over arbitrary collections of NURBS curves in 2D and trimmed NURBS patches in 3D via a Bounding Volume Hierarchy that stores efficiently precomputed moment data in the hierarchy nodes. When querying the hierarchy, approximations for far clusters are used alongside direct evaluation for nearby NURBS primitives, achieving sub-linear complexity while preserving the geometric features in the vicinity of the query point. Central to our performance improvements is an adaptive subdivision strategy for NURBS primitives during a preprocessing phase, creating better spatial partitions while retaining the same accuracy for containment decisions as a direct evaluation. We demonstrate the performance and accuracy of our approach across a large collection of 2D and 3D datasets.

Computer science↗

NASA NTRS1989

Automatic control of cryogenic wind tunnels

Inadequate Reynolds number similarity in testing of scaled models affects the quality of aerodynamic data from wind tunnels. This is due to scale effects of boundary-layer shock wave interaction which is likely to be severe at transonic speeds. The idea of operation of wind tunnels using test gas cooled to cryogenic temperatures has yielded a quantrum jump in the ability to realize full scale Reynolds number flow similarity in small transonic tunnels. In such tunnels, the basic flow control problem consists of obtaining and maintaining the desired test section flow parameters. Mach number, Reynolds number, and dynamic pressure are the three flow parameters that are usually required to be kept constant during the period of model aerodynamic data acquisition. The series of activity involved in modeling, control law development, mechanization of the control laws on a microcomputer, and the performance of a globally stable automatic control system for the 0.3-m Transonic Cryogenic Tunnel (TCT) are discussed. A lumped multi-variable nonlinear dynamic model of the cryogenic tunnel, generation of a set of linear control laws for small perturbation, and nonlinear control strategy for large set point changes including tunnel trajectory control are described. The details of mechanization of the control laws on a 16 bit microcomputer system, the software features, operator interface, the display and safety are discussed. The controller is shown to provide globally stable and reliable temperature control to + or - 0.2 K, pressure to + or - 0.07 psi and Mach number to + or - 0.002 of the set point value. This performance is obtained both during large set point commands as for a tunnel cooldown, and during aerodynamic data acquisition with intrusive activity like geometrical changes in the test section such as angle of attack changes, drag rake movements, wall adaptation and sidewall boundary-layer removal. Feasibility of the use of an automatic Reynolds number control mode with fixed Mach number control is demonstrated.

Balakrishna, S.↗

NASA NTRSDate not supplied

Boundary Representation Tolerance Impacts on Mesh Generation and Adaptation

The control of discretization error is critical to obtaining reliable simulation results. Re-cent progress has matured anisotropic mesh adaptation, which automates discretization error control for complex geometries. However, the meshing process can fail when geometric model Boundary REPresentation (BREP) tolerances are larger than boundary layer surface nor-mal and tangential spacing requirements. Geometry sources are often created in Mechanical Computer-Aided Design (MCAD) systems, which are designed to produce models for manufacturing and not the stricter requirements of viscous flow analysis. BREP tolerances are strained by three factors: the inherent complexity of the model (e.g., large range of scales and complex topology), the numerical difficulties arising from surface/surface intersections, and the omission of crucial data during export and translation. Manual preparation of geometry is commonly employed to enable expert-guided mesh generation, which severely inhibits work-flow automation. Accommodation of loose BREP tolerances is required for automated mesh processes, because barrier issues may not be detected until well into the solution process. To raise awareness of this class of geometry issues and their impact on simulation, a survey of these barrier issues is presented with example mitigation techniques. This awareness may also impact geometry creation workflows to prevent the introduction of these artifacts.

CAD↗

DOE OSTI2016

WE-AB-209-08: Novel Beam-Specific Adaptive Margins for Reducing Organ-At-Risk Doses

Purpose: Current practice of using 3D margins in radiotherapy with high-energy photon beams provides larger-than-required target coverage. According to the photon depth-dose curve, target displacements in beam direction result in minute changes in dose delivered. We exploit this behavior by generating margins on a per-beam basis which simultaneously account for the relative distance of the target and adjacent organs-at-risk (OARs). Methods: For each beam, we consider only geometrical uncertainties of the target location perpendicular to beam direction. By weighting voxels based on its proximity to an OAR, we generate adaptive margins that yield similar overall target coverage probability and reduced OAR dose-burden, at the expense of increased target volume. Three IMRT plans, using 3D margins and 2D per-beam margins with and without adaptation, were generated for five prostate patients with a prescription dose Dpres of 78Gy in 2Gy fractions using identical optimisation constraints. Systematic uncertainties of 1.1, 1.1, 1.5mm in the LR, SI, and AP directions, respectively, and 0.9, 1.1, 1.0mm for the random uncertainties, were assumed. A verification tool was employed to simulate the effects of systematic and random errors using a population size of 50,000. The fraction of the population that satisfies or violates a given DVH constraint was used for comparison. Results: We observe similar target coverage across all plans, with at least 97.5% of the population meeting the D98%>95%Dpres constraint. When looking at the probability of the population receiving D5<70Gy for the rectum, we observed median absolute increases of 23.61% (range, 2.15%–27.85%) and 6.97% (range, 0.65%–17.76%) using per-beam margins with and without adaptation, respectively, relative to using 3D margins. Conclusion: We observed sufficient and similar target coverage using per-beam margins. By adapting each per-beam margin away from an OAR, we can further reduce OAR dose without significantly lowering target coverage probability by irradiating more less-important tissues. This work is supported by Cancer Research UK under Programme C33589/A19908. Research at ICR is also supported by Cancer Research UK under Programme C33589/A19727 and NHS funding to the NIHR Biomedical Research Centre at RMH and ICR.

07 ISOTOPE AND RADIATION SOURCES↗

NASA NTRS1995

Adaptively Refined Euler and Navier-Stokes Solutions with a Cartesian-Cell Based Scheme

A Cartesian-cell based scheme with adaptive mesh refinement for solving the Euler and Navier-Stokes equations in two dimensions has been developed and tested. Grids about geometrically complicated bodies were generated automatically, by recursive subdivision of a single Cartesian cell encompassing the entire flow domain. Where the resulting cells intersect bodies, N-sided 'cut' cells were created using polygon-clipping algorithms. The grid was stored in a binary-tree data structure which provided a natural means of obtaining cell-to-cell connectivity and of carrying out solution-adaptive mesh refinement. The Euler and Navier-Stokes equations were solved on the resulting grids using an upwind, finite-volume formulation. The inviscid fluxes were found in an upwinded manner using a linear reconstruction of the cell primitives, providing the input states to an approximate Riemann solver. The viscous fluxes were formed using a Green-Gauss type of reconstruction upon a co-volume surrounding the cell interface. Data at the vertices of this co-volume were found in a linearly K-exact manner, which ensured linear K-exactness of the gradients. Adaptively-refined solutions for the inviscid flow about a four-element airfoil (test case 3) were compared to theory. Laminar, adaptively-refined solutions were compared to accepted computational, experimental and theoretical results.

Coirier, William J.↗

NASA NTRS2016

Relationships Between Vestibular Measures as Potential Predictors for Spaceflight Sensorimotor Adaptation

Introduction: During space exploration missions astronauts are exposed to a series of novel sensorimotor environments, requiring sensorimotor adaptation. Until adaptation is complete, sensorimotor decrements occur, affecting critical tasks such as piloted landing or docking. Of particularly interest are locomotion tasks such as emergency vehicle egress or extra-vehicular activity. While nearly all astronauts eventually adapt sufficiently, it appears there are substantial individual differences in how quickly and effectively this adaptation occurs. These individual differences in capacity for sensorimotor adaptation are poorly understood. Broadly, we aim to identify measures that may serve as pre-flight predictors of and individual's adaptation capacity to spaceflight-induced sensorimotor changes. As a first step, since spaceflight is thought to involve a reinterpretation of graviceptor cues (e.g. otolith cues from the vestibular system) we investigate the relationships between various measures of vestibular function in humans. Methods: In a set of 15 ground-based control subjects, we quantified individual differences in vestibular function using three measures: 1) ocular vestibular evoked myogenic potential (oVEMP), 2) computerized dynamic posturography and 3) vestibular perceptual thresholds. oVEMP responses are elicited using a mechanical stimuli approach. Computerized dynamic posturography was used to quantify Sensory Organization Tests (SOTs), including SOT5M which involved performing pitching head movements while balancing on a sway-reference support surface with eyes closed. We implemented a vestibular perceptual threshold task using the tilt capabilities of the Tilt-Translation Sled (TTS) at JSC. On each trial, the subject was passively roll-tilted left ear down or right ear down in the dark and verbally provided a forced-choice response regarding which direction they felt tilted. The motion profile was a single-cycle sinusoid of angular acceleration with a duration of 5 seconds (frequency of 0.2 Hz), which was selected as it requires sensory integration of otolith and semicircular canal cues. Stimuli direction was randomized and magnitude was determined using an adaptive sampling procedure. One hundred trials were provided and each subject's responses were fit with a psychometric curve to estimate the subject's threshold. Results: Roll tilt perceptual thresholds at 0.2 Hz ranged from 0.5 degrees to 1.82 degrees across the 15 subjects (geometric mean of 1.04 degrees), consistent with previous studies. The inter-individual variability in thresholds may be able to help explain individual differences observed in sensorimotor adaptation to spaceflight. Analysis is ongoing for the oVEMPS and computerized dynamic posturography to identify relationships between the various vestibular measures. Discussion: Predicting individual differences in sensorimotor adaptation is critical both for the development of personalized countermeasures and mission planning. Here we aim to develop a basis of vestibular tests and parameters which may serve as predictors of individual differences in sensorimotor adaptability through studying the relationship between these measures.

Clark, T. K.↗