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NASA NTRS1978

Effectiveness of basic display augmentation in vehicular control by visual field cues

The paper investigates the effectiveness of different basic display augmentation concepts - fixed reticle, velocity vector, and predicted future vehicle path - for RPVs controlled by a vehicle-mounted TV camera. The task is lateral manual control of a low flying RPV along a straight reference line in the presence of random side gusts. The man-machine system and the visual interface are modeled as a linear time-invariant system. Minimization of a quadratic performance criterion is assumed to underlie the control strategy of a well-trained human operator. The solution for the optimal feedback matrix enables the explicit computation of the variances of lateral deviation and directional error of the vehicle and of the control force that are used as performance measures.

Grunwald, A. J.↗
NASA NTRS2001

Spatial orientation and balance control changes induced by altered gravitoinertial force vectors

To better understand the mechanisms of human adaptation to rotating environments, we exposed 19 healthy subjects and 8 vestibular-deficient subjects ("abnormal"; four bilateral and four unilateral lesions) to an interaural centripetal acceleration of 1 g (resultant 45 degrees roll-tilt of 1.4 g) on a 0.8-m-radius centrifuge for periods of 90 min. The subjects sat upright (body z-axis parallel to centrifuge rotation axis) in the dark with head stationary, except during 4 min of every 10 min, when they performed head saccades toward visual targets switched on at 3- to 5-s intervals at random locations (within +/- 30 degrees) in the earth-horizontal plane. Eight of the normal subjects also performed the head saccade protocol in a stationary chair adjusted to a static roll-tilt angle of 45 degrees for 90 min (reproducing the change in orientation but not the magnitude of the gravitoinertial force on the centrifuge). Eye movements, including voluntary saccades directed along perceived earth- and head-referenced planes, were recorded before, during, and immediately after centrifugation. Postural center of pressure (COP) and multisegment body kinematics were also gathered before and within 10 min after centrifugation. Normal subjects overestimated roll-tilt during centrifugation and revealed errors in perception of head-vertical provided by directed saccades. Errors in this perceptual response tended to increase with time and became significant after approximately 30 min. Motion-sickness symptoms caused approximately 25% of normal subjects to limit their head movements during centrifugation and led three normal subjects to stop the test early. Immediately after centrifugation, subjects reported feeling tilted 10 degrees in the opposite direction, which was in agreement with the direction of their earth-referenced directed saccades. Postural COP, segmental body motion amplitude, and hip-sway frequency increased significantly after centrifugation. These postural effects were short-lived, however, with a recovery time of several postural test trials (minutes). There were also asymmetries in the direction of postcentrifugation COP and head tilt which depended on the subject's orientation during the centrifugation adaptation period (left ear or right ear out). The amount of total head movements during centrifugation correlated poorly or inversely with postcentrifugation postural stability, and the most unstable subject made no head movements. There was no decrease in postural stability after static tilt, although these subjects also reported a perceived tilt briefly after return to upright, and they also had COP asymmetries. Abnormal subjects underestimated roll-tilt during centrifugation, and their directed saccades revealed permanent spatial distortions. Bilateral abnormal subjects started out with poor postural control, but showed no postural decrements after centrifugation, while unilateral abnormal subjects had varying degrees of postural decrement, both in their everyday function and as a result of experiencing the centrifugation. In addition, three unilateral, abnormal subjects, who rode twice in opposite orientations, revealed a consistent orthogonal pattern of COP offsets after centrifugation. These results suggest that both orientation and magnitude of the gravitoinertial vector are used by the central nervous system for calibration of multiple orientation systems. A change in the background gravitoinertial force (otolith input) can rapidly initiate postural and perceptual adaptation in several sensorimotor systems, independent of a structured visual surround.

Clinical Trial↗
DOE OSTI2019

Two-pion contribution to hadronic vacuum polarization

We present a detailed analysis of e + e - → π + π - data up to \( \sqrt{s}=1 \) GeV in the framework of dispersion relations. Starting from a family of ππ P -wave phase shifts, as derived from a previous Roy-equation analysis of ππ scattering, we write down an extended Omnès representation of the pion vector form factor in terms of a few free parameters and study to which extent the modern high-statistics data sets can be described by the resulting fit function that follows from general principles of QCD. We find that statistically acceptable fits do become possible as soon as potential uncertainties in the energy calibration are taken into account, providing a strong cross check on the internal consistency of the data sets, but preferring a mass of the ω meson significantly lower than the current PDG average. In addition to a complete treatment of statistical and systematic errors propagated from the data, we perform a comprehensive analysis of the systematic errors in the dispersive representation and derive the consequences for the two-pion contribution to hadronic vacuum polarization. In a global fit to both time- and space-like data sets we find a ππ μ | ≤ 1 GeV = 495.0(1.5)(2.1) × 10 -10 and a ππ μ | ≤ 0.63 GeV = 132.8(0.4)(1.0) × 10 -10 . While the constraints are thus most stringent for low energies, we obtain uncertainty estimates throughout the whole energy range that should prove valuable in corroborating the corresponding contribution to the anomalous magnetic moment of the muon. As side products, we obtain improved constraints on the ππ P -wave, valuable input for future global analyses of low-energy ππ scattering, as well as a determination of the pion charge radius, $\langle$$r^{2}_{π}$$\rangle$ = 0 . 429(1)(4) fm 2 .

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Multi-fidelity Gaussian process regression for prediction of random fields

We propose a new multi-fidelity Gaussian process regression (GPR) approach for prediction of random fields based on observations of surrogate models or hierarchies of surrogate models. Our method builds upon recent work on recursive Bayesian techniques, in particular recursive co-kriging, and extends it to vector-valued fields and various types of covariances, including separable and non-separable ones. The framework we propose is general and can be used to perform uncertainty propagation and quantification in model-based simulations, multi-fidelity data fusion, and surrogate-based optimization. We demonstrate the effectiveness of the proposed recursive GPR techniques through various examples. Specifically, we study the stochastic Burgers equation and the stochastic Oberbeck–Boussinesq equations describing natural convection within a square enclosure. In both cases we find that the standard deviation of the Gaussian predictors as well as the absolute errors relative to benchmark stochastic solutions are very small, suggesting that the proposed multi-fidelity GPR approaches can yield highly accurate results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Direct, simple and efficient computation of all components of the virtual-casing magnetic field in axisymmetric geometries with Kapur–Rokhlin quadrature

In a recent publication (Toler et al., J. Plasma Phys., vol. 89, issue 2, 2023, p. 905890210), we demonstrated that for axisymmetric geometries, the Kapur–Rokhlin quadrature rule provided an efficient and high-order accurate method for computing the normal component, on the plasma surface, of the magnetic field due to the toroidal current flowing in the plasma, via the virtual-casing principle. The calculation was indirect, as it required the prior computation of the magnetic vector potential from the virtual-casing principle, followed by the computation of its tangential derivative by Fourier differentiation, to obtain the normal component of the magnetic field. Our approach did not provide the other components of the virtual-casing magnetic field. In this letter, we show that a more direct and more general approach is available for the computation of the virtual-casing magnetic field. The Kapur–Rokhlin quadrature rule accurately calculates the principal value integrals in the expression for all the components of the magnetic field on the plasma boundary, and the numerical error converges at a rate nearly as high as the indirect method we presented previously.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

SU-E-J-73: Generation of Volumetric Images with a Respiratory Motion Model Based On An External Surrogate Signal

Purpose: Respiratory motion during radiotherapy treatment can differ significantly from motion observed during imaging for treatment planning. Our goal is to use an initial 4DCT scan and the trace of an external surrogate marker to generate 3D images of patient anatomy during treatment. Methods: Deformable image registration is performed on images from an initial 4DCT scan. The deformation vectors are used to develop a patient-specific linear relationship between the motion of each voxel and the trajectory of an external surrogate signal. Correlations in motion are taken into account with principal component analysis, reducing the number of free parameters. This model is tested with digital phantoms reproducing the breathing patterns of ten measured patient tumor trajectories, using five seconds of data to develop the model and the subsequent thirty seconds to test its predictions. The model is also tested with a breathing physical anthropomorphic phantom programmed to reproduce a patient breathing pattern. Results: The error (mean absolute, 95th percentile) over 30 seconds in the predicted tumor centroid position ranged from (0.8, 1.3) mm to (2.2, 4.3) mm for the ten patient breathing patterns. The model reproduced changes in both phase and amplitude of the breathing pattern. Agreement between prediction and truth over the entire image was confirmed by assessing the global voxel intensity RMS error. In the physical phantom, the error in the tumor centroid position was less than 1 mm for all images. Conclusion: We are able to reconstruct 3D images of patient anatomy with a model correlating internal respiratory motion with motion of an external surrogate marker, reproducing the expected tumor centroid position with an average accuracy of 1.4 mm. The images generated by this model could be used to improve dose calculations for treatment planning and delivered dose estimates. This work was partially funded by a research grant from Varian Medical Systems.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-AB-202-05: GPU-Based 4D Deformable Image Registration Using Adaptive Tetrahedral Mesh Modeling

Purpose: Deformable image registration (DIR) has been employed today as an automated and effective segmentation method to transfer tumor or organ contours from the planning image to daily images, instead of manual segmentation. However, the computational time and accuracy of current DIR approaches are still insufficient for online adaptive radiation therapy (ART), which requires real-time and high-quality image segmentation, especially in a large datasets of 4D-CT images. The objective of this work is to propose a new DIR algorithm, with fast computational speed and high accuracy, by using adaptive feature-based tetrahedral meshing and GPU-based parallelization. Methods: The first step is to generate the adaptive tetrahedral mesh based on the image features of a reference phase of 4D-CT, so that the deformation can be well captured and accurately diffused from the mesh vertices to voxels of the image volume. Subsequently, the deformation vector fields (DVF) and other phases of 4D-CT can be obtained by matching each phase of the target 4D-CT images with the corresponding deformed reference phase. The proposed 4D DIR method is implemented on GPU, resulting in significantly increasing the computational efficiency due to its parallel computing ability. Results: A 4D NCAT digital phantom was used to test the efficiency and accuracy of our method. Both the image and DVF results show that the fine structures and shapes of lung are well preserved, and the tumor position is well captured, i.e., 3D distance error is 1.14 mm. Compared to the previous voxel-based CPU implementation of DIR, such as demons, the proposed method is about 160x faster for registering a 10-phase 4D-CT with a phase dimension of 256×256×150. Conclusion: The proposed 4D DIR method uses feature-based mesh and GPU-based parallelism, which demonstrates the capability to compute both high-quality image and motion results, with significant improvement on the computational speed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Machine Learning with Gradient-Based Optimization of Nuclear Waste Vitrification with Uncertainties and Constraints

Gekko is an optimization suite in Python that solves optimization problems involving mixed-integer, nonlinear, and differential equations. The purpose of this study is to integrate common Machine Learning (ML) algorithms such as Gaussian Process Regression (GPR), support vector regression (SVR), and artificial neural network (ANN) models into Gekko to solve data based optimization problems. Uncertainty quantification (UQ) is used alongside ML for better decision making. These methods include ensemble methods, model-specific methods, conformal predictions, and the delta method. An optimization problem involving nuclear waste vitrification is presented to demonstrate the benefit of ML in this field. ML models are compared against the current partial quadratic mixture (PQM) model in an optimization problem in Gekko. GPR with conformal uncertainty was chosen as the best substitute model as it had a lower mean squared error of 0.0025 compared to 0.018 and more confidently predicted a higher waste loading of 37.5 wt% compared to 34 wt%. The example problem shows that these tools can be used in similar industry settings where easier use and better performance is needed over classical approaches. Future works with these tools include expanding them with other regression models and UQ methods, and exploration into other optimization problems or dynamic control.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Using optimal estimation to retrieve winds from velocity-azimuth display (VAD) scans by a Doppler lidar

Abstract. Low-powered commercially available coherent Doppler lidar (CDL) wind profilers provide continuous measurement of vertical profiles of wind in the lower troposphere, usually close to or up to the top of the planetary boundary layer. The vertical extent of these wind profiles is limited by the availability of scatterers and thus varies substantially throughout the day and from one day to the next. This makes it challenging to develop continuous products that rely on CDL-observed wind profiles. In order to overcome this problem, we have developed a new method for wind profile retrievals from CDL that combines the traditional velocity-azimuth display (VAD) technique with optimal estimation (OE) to provide continuous wind profiles up to 3 km. The new method exploits the level-to-level covariance present in the wind profile to fill in the gaps where the signal-to-noise ratio of the CDL return is too low to provide reliable results using the traditional VAD method. Another advantage of the new method is that it provides the full error covariance matrix of the solution and profiles of information content, which more easily facilitates the assimilation of the observed wind profiles into numerical weather prediction models. This method was tested using yearlong CDL measurements at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility in 2019. Comparison with the ARM operational CDL wind profile product and collocated radiosonde wind measurements shows excellent agreement (R2>0.99) with no degradation in results where the traditional VAD provided a valid solution. In the region where traditional VAD does not provide results, the OE wind speed and wind vector have uncertainties of 3.44 and 4.33 m s−1, respectively. As a result, the new method provides additional information over the standard technique and increases the effective range of existing CDL systems without the need for additional hardware.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1989

Stability analysis of multiple-robot control systems

In a space telerobotic service scenario, cooperative motion and force control of multiple robot arms are of fundamental importance. Three paradigms to study this problem are proposed. They are distinguished by the set of variables used for control design. They are joint torques, arm tip force vectors, and an accelerated generalized coordinate set. Control issues related to each case are discussed. The latter two choices require complete model information, which presents practical modeling, computational, and robustness problems. Therefore, focus is on the joint torque control case to develop relatively model independent motion and internal force control laws. The rigid body assumption allows the motion and force control problems to be independently addressed. By using an energy motivated Lyapunov function, a simple proportional derivative plus gravity compensation type of motion control law is always shown to be stabilizing. The asymptotic convergence of the tracing error to zero requires the use of a generalized coordinate with the contact constraints taken into account. If a non-generalized coordinate is used, only convergence to a steady state manifold can be concluded. For the force control, both feedforward and feedback schemes are analyzed. The feedback control, if proper care has been taken, exhibits better robustness and transient performance.

Wen, John T.↗
NASA NTRS1991

Flux-vector splitting algorithm for chain-rule conservation-law form

A flux-vector splitting algorithm with Newton-Raphson iteration was developed for the 'full compressible' Navier-Stokes equations cast in chain-rule conservation-law form. The algorithm is intended for problems with deforming spatial domains and for problems whose governing equations cannot be cast in strong conservation-law form. The usefulness of the algorithm for such problems was demonstrated by applying it to analyze the unsteady, two- and three-dimensional flows inside one combustion chamber of a Wankel engine under nonfiring conditions. Solutions were obtained to examine the algorithm in terms of conservation error, robustness, and ability to handle complex flows on time-dependent grid systems.

Shih, T. I.-P.↗
DOE OSTI2018

A new potential energy surface and state-to-state quantum dynamics of the $\mathrm{Li + HF → H + LiF}$ reaction

A new global potential energy surface (PES) for the ground ($\tilde{X}^2A'$) state of the Li + HF → LiF + H reactive system is constructed by fitting 12,399 points computed at the UCCSD(T)-F12b/aug-cc-pV5Z level of theory. The use of a neural network method helps to achieve a high-fidelity fit with a root mean square error of 0.88 meV. Quantum dynamics calculations with full Coriolis coupling on the new PES yield both differential and integral cross sections over a range of energy. In agreement with experiment, the product angular distribution depends sensitively on collision energy, but all with a forward bias. Moderate internal excitation is found in the LiF product. The energy dependence of the integral cross section is in reasonably good accord with the experimental excitation function, although some quantitative differences persist. This late-barrier reaction shows a dramatic vibrational enhancement of reactivity. The mode specificity is rationalized using the Sudden Vector Projection model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2011

Estimation of three-dimensional intrinsic dosimetric uncertainties resulting from using deformable image registration for dose mapping

Purpose: This article presents a general procedural framework to assess the point-by-point precision in mapped dose associated with the intrinsic uncertainty of a deformable image registration (DIR) for any arbitrary patient. Methods: Dose uncertainty is obtained via a three-step process. In the first step, for each voxel in an imaging pair, a cluster of points is obtained by an iterative DIR procedure. In the second step, the dispersion of the points due to the imprecision of the DIR method is used to compute the spatial uncertainty. Two different ways to quantify the spatial uncertainty are presented in this work. Method A consists of a one-dimensional analysis of the modules of the position vectors, whereas method B performs a more detailed 3D analysis of the coordinates of the points. In the third step, the resulting spatial uncertainty estimates are used in combination with the mapped dose distribution to compute the point-by-point dose standard deviation. The process is demonstrated to estimate the dose uncertainty induced by mapping a 62.6 Gy dose delivered on maximum exhale to maximum inhale of a ten-phase four-dimensional lung CT. Results: For the demonstration lung image pair, the standard deviation of inconsistency vectors is found to be up to 9.2 mm with a mean {sigma} of 1.3 mm. This uncertainty results in a maximum estimated dose uncertainty of 29.65 Gy if method A is used and 21.81 Gy for method B. The calculated volume with dose uncertainty above 10.00 Gy is 602 cm{sup 3} for method A and 1422 cm{sup 3} for method B. Conclusions: This procedure represents a useful tool to evaluate the precision of a mapped dose distribution due to the intrinsic DIR uncertainty in a patient. The procedure is flexible, allowing incorporation of alternative intrinsic error models.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1985

Applications of Some Artificial Intelligence Methods to Satellite Soundings

Hard clustering of temperature profiles and regression temperature retrievals were used to refine the method using the probabilities of membership of each pattern vector in each of the clusters derived with discriminant analysis. In hard clustering the maximum probability is taken and the corresponding cluster as the correct cluster are considered discarding the rest of the probabilities. In fuzzy partitioned clustering these probabilities are kept and the final regression retrieval is a weighted regression retrieval of several clusters. This method was used in the clustering of brightness temperatures where the purpose was to predict tropopause height. A further refinement is the division of temperature profiles into three major regions for classification purposes. The results are summarized in the tables total r.m.s. errors are displayed. An approach based on fuzzy logic which is intimately related to artificial intelligence methods is recommended.

Munteanu, M. J.↗
NASA NTRS1990

Numerical experiments in geomagnetic modeling

Numerical tests were made, using least squares fitting of a spherical harmonic model, to a selection of Magsat data to determine the practical limits of this technique with modern computers. The resulting (M102189) model, whose coefficients were adjusted up to n = 50, was compared with M07AV6, a previous model which used least squares (on vector data) for coefficients up to n = 29, and Gauss-Legendre quadrature (on Z residuals) to adjust the coefficients up to n = 63. For the new least squares adjustment to n = 50 a condition number of 115 was obtained for the solution matrix, with a resulting precision of 11 significant figures. The M102189 model shows a lower and more Gaussian residual distribution than did M07AV6, though the Gaussian envelope fits to the residual distributions, even for the scalar field, gives "standard deviations' never lower than 6 nT, a factor of three higher than the estimated Magsat observational errors. Ionospheric currents are noted to have a significant effect on the coefficients of the internal potential functions.

Cain, Joseph C.↗
NASA NTRS1996

A Real-Time Position-Locating Algorithm for CCD-Based Sunspot Tracking

NASA Marshall Space Flight Center's (MSFC) EXperimental Vector Magnetograph (EXVM) polarimeter measures the sun's vector magnetic field. These measurements are taken to improve understanding of the sun's magnetic field in the hopes to better predict solar flares. Part of the procedure for the EXVM requires image motion stabilization over a period of a few minutes. A high speed tracker can be used to reduce image motion produced by wind loading on the EXVM, fluctuations in the atmosphere and other vibrations. The tracker consists of two elements, an image motion detector and a control system. The image motion detector determines the image movement from one frame to the next and sends an error signal to the control system. For the ground based application to reduce image motion due to atmospheric fluctuations requires an error determination at the rate of at least 100 hz. It would be desirable to have an error determination rate of 1 kHz to assure that higher rate image motion is reduced and to increase the control system stability. Two algorithms are presented that are typically used for tracking. These algorithms are examined for their applicability for tracking sunspots, specifically their accuracy if only one column and one row of CCD pixels are used. To examine the accuracy of this method two techniques are used. One involves moving a sunspot image a known distance with computer software, then applying the particular algorithm to see how accurately it determines this movement. The second technique involves using a rate table to control the object motion, then applying the algorithms to see how accurately each determines the actual motion. Results from these two techniques are presented.

Taylor, Jaime R.↗
NASA NTRS2002

Preliminary Effect of Synthetic Vision Systems Displays to Reduce Low-Visibility Loss of Control and Controlled Flight Into Terrain Accidents

An experimental investigation was conducted to study the effectiveness of Synthetic Vision Systems (SVS) flight displays as a means of eliminating Low Visibility Loss of Control (LVLOC) and Controlled Flight Into Terrain (CFIT) accidents by low time general aviation (GA) pilots. A series of basic maneuvers were performed by 18 subject pilots during transition from Visual Meteorological Conditions (VMC) to Instrument Meteorological Conditions (IMC), with continued flight into IMC, employing a fixed-based flight simulator. A total of three display concepts were employed for this evaluation. One display concept, referred to as the Attitude Indicator (AI) replicated instrumentation common in today's General Aviation (GA) aircraft. The second display concept, referred to as the Electronic Attitude Indicator (EAI), featured an enlarged attitude indicator that was more representative of a glass display that also included advanced flight symbology, such as a velocity vector. The third concept, referred to as the SVS display, was identical to the EAI except that computer-generated terrain imagery replaced the conventional blue-sky/brown-ground of the EAI. Pilot performance parameters, pilot control inputs and physiological data were recorded for post-test analysis. Situation awareness (SA) and qualitative pilot comments were obtained through questionnaires and free-form interviews administered immediately after the experimental session. Initial pilot performance data were obtained by instructor pilot observations. Physiological data (skin temperature, heart rate, and muscle flexure) were also recorded. Preliminary results indicate that far less errors were committed when using the EAI and SVS displays than when using conventional instruments. The specific data example examined in this report illustrates the benefit from SVS displays to avoid massive loss of SA conditions. All pilots acknowledged the enhanced situation awareness provided by the SVS display concept. Levels of pilot stress appear to be correlated with skin temperature measurements.

Glaab, Louis J.↗
DOE OSTI2019

Machine learning framework for assessment of microbial factory performance

Metabolic models can estimate intrinsic product yields for microbial factories, but such frameworks struggle to predict cell performance (including product titer or rate) under suboptimal metabolism and complex bioprocess conditions. On the other hand, machine learning, complementary to metabolic modeling necessitates large amounts of data. Building such a database for metabolic engineering designs requires significant manpower and is prone to human errors and bias. We propose an approach to integrate data-driven methods with genome scale metabolic model for assessment of microbial bio-production (yield, titer and rate). Using engineered E. coli as an example, we manually extracted and curated a data set comprising about 1200 experimentally realized cell factories from ~100 papers. We furthermore augmented the key design features (e.g., genetic modifications and bioprocess variables) extracted from literature with additional features derived from running the genome-scale metabolic model iML1515 simulations with constraints that match the experimental data. Then, data augmentation and ensemble learning (e.g., support vector machines, gradient boosted trees, and neural networks in a stacked regressor model) are employed to alleviate the challenges of sparse, non-standardized, and incomplete data sets, while multiple correspondence analysis/principal component analysis are used to rank influential factors on bio-production. The hybrid framework demonstrates a reasonably high cross-validation accuracy for prediction of E.coli factory performance metrics under presumed bioprocess and pathway conditions (Pearson correlation coefficients between 0.8 and 0.93 on new data not seen by the model).

59 BASIC BIOLOGICAL SCIENCES↗