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DOE OSTI2014

TH-E-9A-01: Medical Physics 1.0 to 2.0, Session 4: Computed Tomography, Ultrasound and Nuclear Medicine

Medical Physics 2.0 is a bold vision for an existential transition of clinical imaging physics in face of the new realities of value-based and evidencebased medicine, comparative effectiveness, and meaningful use. It speaks to how clinical imaging physics can expand beyond traditional insular models of inspection and acceptance testing, oriented toward compliance, towards team-based models of operational engagement, prospective definition and assurance of effective use, and retrospective evaluation of clinical performance. Organized into four sessions of the AAPM, this particular session focuses on three specific modalities as outlined below. CT 2.0: CT has been undergoing a dramatic transition in the last few decades. While the changes in the technology merits discussions of their own, an important question is how clinical medical physicists are expected to effectively engage with the new realities of CT technology and practice. Consistent with the upcoming paradigm of Medical Physics 2.0, this CT presentation aims to provide definitions and demonstration of the components of the new clinical medical physics practice pertaining CT. The topics covered include physics metrics and analytics that aim to provide higher order clinicallyrelevant quantification of system performance as pertains to new (and not so new) technologies. That will include the new radiation and dose metrics (SSDE, organ dose, risk indices), image quality metrology (MTF/NPS/d’), task-based phantoms, and the effect of patient size. That will follow with a discussion of the testing implication of new CT hardware (detectors, tubes), acquisition methods (innovative helical geometries, AEC, wide beam CT, dual energy, inverse geometry, application specialties), and image processing and analysis (iterative reconstructions, quantitative CT, advanced renditions). The presentation will conclude with a discussion of clinical and operational aspects of Medical Physics 2.0 including training and communication, use optimization (dose and technique factors), automated analysis and data management (automated QC methods, protocol tracking, dose monitoring, issue tracking), and meaningful QC considerations. US 2.0: Ultrasound imaging is evolving at a rapid pace, adding new imaging functions and modes that continue to enhance its clinical utility and benefits to patients. The ultrasound talk will look ahead 10–15 years and consider how medical physicists can bring maximal value to the clinical ultrasound practices of the future. The roles of physics in accreditation and regulatory compliance, image quality and exam optimization, clinical innovation, and education of staff and trainees will all be considered. A detailed examination of expected technology evolution and impact on image quality metrics will be presented. Clinical implementation of comprehensive physics services will also be discussed. Nuclear Medicine 2.0: Although the basic science of nuclear imaging has remained relatively unchanged since its inception, advances in instrumentation continue to advance the field into new territories. With a great number of these advances occurring over the past decade, the role and testing strategies of clinical nuclear medicine physicists must evolve in parallel. The Nuclear Medicine 2.0 presentation is designed to highlight some of the recent advances from a clinical medical physicist perspective and provide ideas and motivation for designing better evaluation strategies. Topics include improvement of traditional physics metrics and analytics, testing implications of hybrid imaging and advanced detector technologies, and strategies for effective implementation into the clinic. Learning Objectives: Become familiar with new physics metrics and analytics in nuclear medicine, CT, and ultrasound. To become familiar with the major new developments of clinical physics support. To understand the physics testing implications of new technologies, hardware, software, and applications. Identify approaches for implementing comprehensive medical physics services in future imaging practices.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Joint reconstruction of x-ray fluorescence and transmission tomography

X-ray fluorescence tomography is based on the detection of fluorescence x-ray photons produced following x-ray absorption while a specimen is rotated; it provides information on the 3D distribution of selected elements within a sample. One limitation in the quality of sample recovery is the separation of elemental signals due to the finite energy resolution of the detector. Another limitation is the effect of self-absorption, which can lead to inaccurate results with dense samples. To recover a higher quality elemental map, we combine x-ray fluorescence detection with a second data modality: conventional x-ray transmission tomography using absorption. By using these combined signals in a nonlinear optimization-based approach, we demonstrate the benefit of our algorithm on real experimental data and obtain an improved quantitative reconstruction of the spatial distribution of dominant elements in the sample. Furthermore, compared with single-modality inversion based on x-ray fluorescence alone, this joint inversion approach reduces ill-posedness and should result in improved elemental quantification and better correction of self-absorption.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1985

Optimal Sensor Locations for Structural Identification

The optimum sensor location problem, OSLP, may be thought of in terms of the set of systems, S, the class of input time functions, I, and the identification algorithm (estimator) used, E. Thus, for a given time history of input, the technique of determining the OSL requires, in general, the solution of the optimization and the identification problems simultaneously. A technique which uncouples the two problems is introduced. This is done by means of the concept of an efficient estimator for which the covariance of the parameter estimates is inversely proportional to the Fisher Information Matrix.

Udwadia, F. E.↗

NASA NTRS1986

A methodology for designing robust multivariable nonlinear control systems

A new methodology is described for the design of nonlinear dynamic controllers for nonlinear multivariable systems providing guarantees of closed-loop stability, performance, and robustness. The methodology is an extension of the Linear-Quadratic-Gaussian with Loop-Transfer-Recovery (LQG/LTR) methodology for linear systems, thus hinging upon the idea of constructing an approximate inverse operator for the plant. A major feature of the methodology is a unification of both the state-space and input-output formulations. In addition, new results on stability theory, nonlinear state estimation, and optimal nonlinear regulator theory are presented, including the guaranteed global properties of the extended Kalman filter and optimal nonlinear regulators.

Grunberg, D. B.↗

NASA NTRS1988

Viscous induced drag

A fundamentally new approach to the aircraft minimum induced drag problem is presented. The method, a 'viscous lifting line', is based on the minimum entropy production principle and does not require the planar wake assumption. An approximate, closed form solution is obtained and compared with several classical results. In addition, the problem of optimizing in-plane wing sweep with constant wing root bending moment is considered. Like the classical lifting line theory, this theory predicts that induced drag is proportional to the square of the lift coefficient and inversely proportional to the wing aspect ratio. Unlike the classical theory, it predicts that in-plane wing sweep may significantly reduce induced drag, that induced drag is Reynolds number dependent, and that the optimum spanwise circulation distribution is non-elliptic.

Greene, George C.↗

NASA NTRS1994

From neural-based object recognition toward microelectronic eyes

Engineering neural network systems are best known for their abilities to adapt to the changing characteristics of the surrounding environment by adjusting system parameter values during the learning process. Rapid advances in analog current-mode design techniques have made possible the implementation of major neural network functions in custom VLSI chips. An electrically programmable analog synapse cell with large dynamic range can be realized in a compact silicon area. New designs of the synapse cells, neurons, and analog processor are presented. A synapse cell based on Gilbert multiplier structure can perform the linear multiplication for back-propagation networks. A double differential-pair synapse cell can perform the Gaussian function for radial-basis network. The synapse cells can be biased in the strong inversion region for high-speed operation or biased in the subthreshold region for low-power operation. The voltage gain of the sigmoid-function neurons is externally adjustable which greatly facilitates the search of optimal solutions in certain networks. Various building blocks can be intelligently connected to form useful industrial applications. Efficient data communication is a key system-level design issue for large-scale networks. We also present analog neural processors based on perceptron architecture and Hopfield network for communication applications. Biologically inspired neural networks have played an important role towards the creation of powerful intelligent machines. Accuracy, limitations, and prospects of analog current-mode design of the biologically inspired vision processing chips and cellular neural network chips are key design issues.

Sheu, Bing J.↗

NASA NTRS1999

Circadian Entrainment, Sleep-Wake Regulation and Neurobehavioral Performance During Extended Duration Space Flight

Long-duration manned space flight requires crew members to maintain a high level of cognitive performance and vigilance while operating and monitoring sophisticated instrumentation. However, the reduction in the strength of environmental synchronizers in the space environment leads to misalignment of circadian phase among crew members, coupled with restricted time available to sleep, results in sleep deprivation and consequent deterioration of neurobehavioral function. Crew members are provided, and presently use, long-acting benzodiazepine hypnotics on board the current, relatively brief space shuttle missions to counteract such sleep disruption, a situation that is only likely to worsen during extended duration missions. Given the known carry-over effects of such compounds on daytime performance, together with the reduction in emergency readiness associated with their use at night, NASA has recognized the need to develop effective but safe countermeasures to allow crew members to obtain an adequate amount of sleep. Over the past eight years, we have successfully implemented a new technology for shuttle crew members involving bright light exposure during the pre-launch period to facilitate adaptation of the circadian timing system to the inversions of the sleep-wake schedule often required during dual shift missions. However for long duration space station missions it will be necessary to develop effective and attainable countermeasures that can be used chronically to optimize circadian entrainment. Our current research effort is to study the effects of light-dark cycles with reduced zeitgeber strength, such as are anticipated during long-duration space flight, on the entrainment of the endogenous circadian timing system and to study the effects of a countermeasure that consists of scheduled brief exposures to bright light on the human circadian timing system. The proposed studies are designed to address the following Specific Aims: (1) test the hypothesis that synchronization of the human circadian pacemaker will be disturbed in men and women by the reduction in LD cycle strength. (2) test the hypothesis that this disturbed circadian synchronization will result in the secretion of the sleep-promoting hormone melatonin during the waking day, disturbed sleep, reduced growth hormone secretion, and impaired performance and daytime alertness; (3) as a countermeasure, test the hypothesis that brief daily exposures to bright light (10,000 lux) will reestablish normal entrained circadian phase, resulting in improved sleep consolidation, normalized sleep structure and endogenous growth hormone secretion and enhanced daytime performance. To date, we have carried out twelve experiments to address Hypotheses I and 2 and data analyses are in progress. The results of the current research may have important implications for the treatment of circadian rhythm sleep disorders, such as delayed sleep phase syndrome and shift-work dyssomnia, which are anticipated to have a high incidence and prevalence during extended duration space flight such as planned for the International Space Station and manned missions to Mars.

Czeisler, Charles A.↗

NASA NTRS2019

Thermal Property Estimation of Fibrous Insulation: Heat Transfer Modeling and the Continuous Genetic Algorithm

Thermal properties of high-temperature fibrous insulation materials were estimated from transient thermal tests using an inverse heat transfer technique. Transient temperature data from an experimental set up was collected and a simple, one-dimensional numerical model was constructed to replicate the temperatures within the test assembly. The Continuous Genetic Algorithm optimization technique in conjunction with a numerical thermal model and transient test data was used to estimate coefficients of a functional representation of the thermal property. The thermal properties, i.e., thermal conductivity and specific heat, of an alumina insulation felt were estimated over the temperature range of 300 K to 1700 K at various constant static pressures in nitrogen gas and compared with published data. The resulting thermal property estimates were within 10% of published values over the entire temperature range at various pressures. The methodology, application, and results are presented.

Frye, Elora↗

DOE OSTI2023

Inverse reinforcement learning control for building energy management

Reinforcement learning (RL) based control is widely considered a promising approach in building automation and control as it has demonstrated the potential to deal with complex objectives in adjacent domains like robotics, autonomous vehicles, gaming applications, and advertisement recommendations. When applied to any environment, model-free RL learns to improve its control performance over time without requiring a control model, by receiving and then analyzing feedback from the building environment after each control action. Operational objectives are becoming increasingly complex through the simultaneous consideration of thermal comfort, carbon emissions, grid services, and indoor air quality. In this context, conventional rule-based control approaches are proving sub-optimal, mostly heuristic, and inadequate. The model-free and self learning nature of RL appears promising and attractive as it may address the scalability issues associated with advanced control approaches. However, it suffers from long training times and unstable control behavior during the early stages of its learning process, which makes it unsuitable to be applied directly to buildings. This paper addresses these issues using an inverse reinforcement learning approach (IRL), a technique utilized to learn the objective of a controller agent which is considered an expert in its respective domain. Here, we consider a rule-based control as the expert demonstrator. IRL is different from a direct imitation (i.e., direct mapping of states to actions) of control actions as it tries to find the underlying intent of an expert's policy, providing the controller with a better-generalized policy for unseen states or environments with slightly different dynamics. This approach propels the RL controller's policy to levels similar to or better than that of a rule-based policy before it starts learning by interacting with the building. This makes RL for building energy management applications more practical as it prevents the erratic and exploratory behavior in the initial training period, simultaneously speeding up the learning process when compared to applying an untrained RL agent directly to a building environment.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2015

Stochastic inverse problems: Models and metrics

In past work, we introduced model-based inverse methods, and applied them to problems in which the anomaly could be reasonably modeled by simple canonical shapes, such as rectangular solids. In these cases the parameters to be inverted would be length, width and height, as well as the occasional probe lift-off or rotation. We are now developing a formulation that allows more flexibility in modeling complex flaws. The idea consists of expanding the flaw in a sequence of basis functions, and then solving for the expansion coefficients of this sequence, which are modeled as independent random variables, uniformly distributed over their range of values. There are a number of applications of such modeling: 1. Connected cracks and multiple half-moons, which we have noted in a POD set. Ideally we would like to distinguish connected cracks from one long shallow crack. 2. Cracks of irregular profile and shape which have appeared in cold work holes during bolt-hole eddy-current inspection. One side of such cracks is much deeper than other. 3. L or C shaped crack profiles at the surface, examples of which have been seen in bolt-hole cracks. By formulating problems in a stochastic sense, we are able to leverage the stochastic global optimization algorithms in NLSE, which is resident in VIC-3D®, to answer questions of global minimization and to compute confidence bounds using the sensitivity coefficient that we get from NLSE. We will also address the issue of surrogate functions which are used during the inversion process, and how they contribute to the quality of the estimation of the bounds.

36 MATERIALS SCIENCE↗

DOE OSTI2017

Dual-Polarity Ion Trap Mass Spectrometry: Dynamic Monitoring and Controlling Gas-phase Ion–Ion Reactions

A dual-polarity linear ion trap (LIT) mass spectrometer was developed in this study, and the method for simultaneously controlling and detecting cations and anions was proposed and realized in the LIT. With the application of an additional dipolar DC field on the ejection electrodes of an LIT, dual-polarity mass spectra could be obtained, which include both the mass-to-charge (m/z) ratio and charge polarity information of an ion. Compared with conventional method, the ion ejection and detection efficiency could also be improved by about one-fold. Furthermore, ion–ion reactions within the LIT could be dynamically controlled and monitored by manipulating the distributions of ions with opposite charge polarities. This method was then used to control and study the reaction kinetics of ion–ion reactions, including electron transfer dissociation (ETD) and charge inversion reactions. A dual-polarity collision-induced dissociation (CID) experiment was proposed and performed to enhance the sequence coverage of a peptide ion. Ion trajectory simulations were also carried out for concept validation and system optimization. .

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2015

Thermal analysis for laser selective removal of metallic single-walled carbon nanotubes

Single-walled carbon nanotubes (SWNTs) have been envisioned as one of the best candidates for future semiconductors due to their excellent electrical properties and ample applications. However, SWNTs grow as mixture of both metallic and semiconducting tubes and this heterogeneity hampers their practical applications. Laser radiation shows promises to remove metallic SWNTs (m-SWNTs) in air under an appropriate condition. We established a scaling law, validated by finite element simulations, for the temperature rise of m-SWNTs under a pulsed laser with a Gaussian spot. It is shown that the maximum normalized m-SWNT temperature rise only depends on two non-dimensional parameters: the normalized pulse duration time and the normalized interfacial thermal resistance. In addition, the maximum temperature rise is inversely proportional to the square of spot size and proportional to the incident laser power. These results are very helpful to understand the underlying physics associated with the removal process and provides easily interpretable guidelines for further optimizations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2015

TU-AB-201-01: A Comprehensive Planning Comparison Study Between a Novel Direction Modulated Brachytherapy Tandem Applicator and Conventional T&R Applicator for Image Guided Cervical Cancer Brachytherapy

Purpose: To demonstrate that utilization of a novel, intensity modulation capable, direction modulated brachytherapy (DMBT) tandem applicator can improve plan quality compared with conventional T&R applicator during an image guided cervical cancer brachytherapy. Methods: 45 cervical cancer patients treated with PDR brachytherapy were reviewed. Of them, a) 27 were treated using T&R only, b) 9 were treated using T&R with needles attached to the ring, and c) the remaining 9 were treated using T&R with needles attached to the ring (AN) as well as additional free-hand-loaded needles (FN). The DMBT tandem design has 6 peripheral holes of 1.3-mm diameter, grooved along a nonmagnetic tungsten alloy rod, enclosed in a plastic sheath with total 6.0-mm diameter. An in-house-coded inverse planning system was used for planning DMBT and T&R cases. All typical clinical constraints including OAR dose limits, dwell times, and loading patterns were respected. For the DMBT and T&R applicators, the plans were optimized with the same conventional ring in place, but repeatedly planned with and without AN/FN needles. All generated plans were normalized to the same D90 of the clinically treated plans. Results: For the plans in category a), DMBT generally outperformed T&R with average reduction in D2cc of −2.39%, −5.21%, and −2.69% for bladder, rectum, and sigmoid, respectively. For the plans in category b) and c), DMBT generally outperformed T&R if the same needles in AN/FN were utilized in both cases with average reduction in D2cc of −1.82%, −3.40%, and −6.04%, respectively. For the cases where the needles were not utilized for both applicators, an average D2cc reduction of −7.45%, −7.61%, and 17.47% were observed, respectively. Conclusions: Under the same clinical conditions, with/without needles, the DMBT applicator tends to generate more favorable plans compared with the conventional T&R applicator, and hence, is a promising technology.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

Community Project for Accelerator Science and Simulation (ComPASS)

After concluding our initial exercise (solving a simplified statistical inverse problem with unknown parameter laser intensity) of coupling Vorpal and our parallel statistical library QUESO, we shifted the application focus to DLA. Our efforts focused on developing a Gaussian process (GP) emulator within QUESO for efficient optimization of power couplers within woodpiles. The smaller simulation size (compared with LPA) allows for sufficient “training runs” to develop a reasonable GP statistical emulator for a parameter space of moderate dimension.

43 PARTICLE ACCELERATORS↗

NASA NTRS1988

Control strategies

Techniques for improving the performance of robotic-manipulator path-control systems comprising independent SISO feedback controllers for each joint are discussed and illustrated with block diagrams, reviewing the results of recent analytical investigations. Topics examined include the servo design for a single link, the equations of motion for manipulators, SISO servo design for multiple links, inverse methods, pole placement with compensation of the gravity terms, linear state-feedback control based on the perturbation equations, and adaptive control methods. Consideration is given to variable-structure systems, suboptimal controllers, and the optimal-design-strategy approach.

Wang, J. C.↗

NASA NTRS1995

Contribution to the optimal shape design of two-dimensional internal flows with embedded shocks

We explore the practicability of optimal shape design for flows modeled by the Euler equations. We define a functional whose minimum represents the optimality condition. The gradient of the functional with respect to the geometry is calculated with the Lagrange multipliers, which are determined by solving a co-state equation. The optimization problem is then examined by comparing the performance of several gradient-based optimization algorithms. In this formulation, the flow field can be computed to an arbitrary order of accuracy. Finally, some results for internal flows with embedded shocks are presented, including a case for which the solution to the inverse problem does not belong to the design space.

Iollo, Angelo↗

NASA NTRS2001

Maximally Informative Statistics for Localization and Mapping

This paper presents an algorithm for localization and mapping for a mobile robot using monocular vision and odometry as its means of sensing. The approach uses the Variable State Dimension filtering (VSDF) framework to combine aspects of Extended Kalman filtering and nonlinear batch optimization. This paper describes two primary improvements to the VSDF. The first is to use an interpolation scheme based on Gaussian quadrature to linearize measurements rather than relying on analytic Jacobians. The second is to replace the inverse covariance matrix in the VSDF with its Cholesky factor to improve the computational complexity. Results of applying the filter to the problem of localization and mapping with omnidirectional vision are presented.

Deans, Matthew C.↗

NASA NTRS2001

Computationally efficient control allocation

A computationally efficient method for calculating near-optimal solutions to the three-objective, linear control allocation problem is disclosed. The control allocation problem is that of distributing the effort of redundant control effectors to achieve some desired set of objectives. The problem is deemed linear if control effectiveness is affine with respect to the individual control effectors. The optimal solution is that which exploits the collective maximum capability of the effectors within their individual physical limits. Computational efficiency is measured by the number of floating-point operations required for solution. The method presented returned optimal solutions in more than 90% of the cases examined; non-optimal solutions returned by the method were typically much less than 1% different from optimal and the errors tended to become smaller than 0.01% as the number of controls was increased. The magnitude of the errors returned by the present method was much smaller than those that resulted from either pseudo inverse or cascaded generalized inverse solutions. The computational complexity of the method presented varied linearly with increasing numbers of controls; the number of required floating point operations increased from 5.5 i, to seven times faster than did the minimum-norm solution (the pseudoinverse), and at about the same rate as did the cascaded generalized inverse solution. The computational requirements of the method presented were much better than that of previously described facet-searching methods which increase in proportion to the square of the number of controls.

Durham, Wayne↗