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At least 1,621 records · Page 90

A feasibility study: Selection of a personalized radiotherapy fractionation schedule using spatiotemporal optimization

Purpose: To investigate the impact of using spatiotemporal optimization, i.e., intensity-modulated spatial optimization followed by fractionation schedule optimization, to select the patient-specific fractionation schedule that maximizes the tumor biologically equivalent dose (BED) under dose constraints for multiple organs-at-risk (OARs). Methods: Spatiotemporal optimization was applied to a variety of lung tumors in a phantom geometry using a range of tumor sizes and locations. The optimal fractionation schedule for a patient using the linear-quadratic cell survival model depends on the tumor and OAR sensitivity to fraction size (α/β), the effective tumor doubling time (T{sub d}), and the size and location of tumor target relative to one or more OARs (dose distribution). The authors used a spatiotemporal optimization method to identify the optimal number of fractions N that maximizes the 3D tumor BED distribution for 16 lung phantom cases. The selection of the optimal fractionation schedule used equivalent (30-fraction) OAR constraints for the heart (D{sub mean} ≤ 45 Gy), lungs (D{sub mean} ≤ 20 Gy), cord (D{sub max} ≤ 45 Gy), esophagus (D{sub max} ≤ 63 Gy), and unspecified tissues (D{sub 05} ≤ 60 Gy). To assess plan quality, the authors compared the minimum, mean, maximum, and D{sub 95} of tumor BED, as well as the equivalent uniform dose (EUD) for optimized plans to conventional intensity-modulated radiation therapy plans prescribing 60 Gy in 30 fractions. A sensitivity analysis was performed to assess the effects of T{sub d} (3–100 days), tumor lag-time (T{sub k} = 0–10 days), and the size of tumors on optimal fractionation schedule. Results: Using an α/β ratio of 10 Gy, the average values of tumor max, min, mean BED, and D{sub 95} were up to 19%, 21%, 20%, and 19% larger than those from conventional prescription, depending on T{sub d} and T{sub k} used. Tumor EUD was up to 17% larger than the conventional prescription. For fast proliferating tumors with T{sub d} less than 10 days, there was no significant increase in tumor BED but the treatment course could be shortened without a loss in tumor BED. The improvement in the tumor mean BED was more pronounced with smaller tumors (p-value = 0.08). Conclusions: Spatiotemporal optimization of patient plans has the potential to significantly improve local tumor control (larger BED/EUD) of patients with a favorable geometry, such as smaller tumors with larger distances between the tumor target and nearby OAR. In patients with a less favorable geometry and for fast growing tumors, plans optimized using spatiotemporal optimization and conventional (spatial-only) optimization are equivalent (negligible differences in tumor BED/EUD). However, spatiotemporal optimization yields shorter treatment courses than conventional spatial-only optimization. Personalized, spatiotemporal optimization of treatment schedules can increase patient convenience and help with the efficient allocation of clinical resources. Spatiotemporal optimization can also help identify a subset of patients that might benefit from nonconventional (large dose per fraction) treatments that are ineligible for the current practice of stereotactic body radiation therapy.

60 APPLIED LIFE SCIENCES↗

An Experimental Feasibility Study on Applying Neutron Tomography to Encapsulated Spent Nuclear Fuel - 20050

Visual inspection makes easier to ensure the integrity and safety of spent nuclear fuel (SNF) than any classical techniques. Various classical techniques have been applied but there are no reliable methods to qualitatively and quantitatively verify spent fuel in dry storage. Thus, the present authors have developed the prototype safeguards apparatus for dry storage employing the array of He-4 gas scintillation detectors (S670E, Arktis Radiation Detectors Ltd., Switzerland), newly designed to simultaneously measure thermal and fast neutrons without any moderators. The S670E detector has a cylindrical shape with a diameter of 52 mm and active length of 600 mm (total length: 875 mm). The detector is filled by He-4 gas with an approximate pressure of 180 bar for fast neutron detection, and its inner wall is coated by Li-6 for thermal neutron detection. The scintillation lights generated via Li-6 nuclear reaction and elastic scattering are collected by 24 SiPMs linearly paired at the center of the detector. The detector delivers a TTL (Transistor-Transistor Logic) output for pulse readout and UART (Universal Asynchronous Receiver Transmitter) for device control. In order to assess feasibility of the apparatus, an experimental system has been designed, built, and optimized via computational studies. Cf-252 neutron sources and linearly arrayed detectors, working as a single detector, were occupied for this study due to the difficulties in working with SNF. The laboratory scale cask (diameter: 0.67 m, height: 1.5 m), minimized by a factor of 10 compared to the actual thickness of a commercial TN-32 cask, was also manufactured. The detector array was designed to rotate the lab-scale cask and obtain 36 image profiles at every 10 degrees. All profiles were aligned in single frame image called a sinogram, and the cross-sectional image was then fabricated by the inverse radon transform algorithm. These experiments have been repeated with different configurations and numbers of sources. Some gamma-ray sources were also measured with neutron sources in order to distinguish between neutron and gamma-ray pulses. Basically, a He-4 detector is designed to run on Linux OS so it is difficult to directly apply to Windows-based equipment widely used in S. Korea. Therefore, a new data acquisition board working on Windows OS was designed and built. The board mainly consists of FPGA (Field Programmable Gate Array) and SoC (System on Chip) for TTL pulse readout, sorting measured data, and transferring data to a user interface. In conclusion, the tomographic system at lab-scale has shown considerable potential to detect a partial or gross defect of encapsulated assemblies in dry storage. Next steps of this study will be to 1) repeatedly carry out experiments to demonstrate scientific reliability and validity, and 2) numerically integrate signals with weight factors to enhance the image quality since the suggested system based on passive interrogation method requires longer measurement time. Finally, the system will apply to a commercial dry storage phased out soon in S. Korea. (authors)

07 ISOTOPE AND RADIATION SOURCES↗

A Comparison of Control Allocation Methods in the Presence of Parametric Model Uncertainty

When allocating redundant effectors to virtual control commands, linear (generalized inverse) allocators have historically been used on aircraft and spacecraft. While simple to implement, generalized inverses are unable to realize a significant portion of the attainable moments. To address this drawback, the control allocation problem can also be formulated as a linear programming or quadratic programming problem and solved using convex optimization based solvers. These approaches have been shown to access a larger set of attainable moments, however, little work has been done to understand the performance of convex optimization-based control allocation in the presence of parametric model uncertainty. This paper seeks to compare the performance of several control allocation approaches, including two forms of generalized inverse allocators, the pseudo inverse and minimum-variance, and the linear programming and quadratic programming approach in the presence of parametric model uncertainty. The performance of these four allocators were tested on an aircraft model in the presence of realistic parametric model uncertainty and the convex optimization approaches were shown to outperform the generalized inverses.

Luke J Miller↗

A method for nonlinear optimization with discrete design variables

A numerical method is presented for the solution of nonlinear discrete optimization problems. The applicability of discrete optimization to engineering design is discussed, and several standard structural optimization problems are solved using discrete design variables. The method uses approximation techniques to create subproblems suitable for linear mixed-integer programming methods. The method employs existing software for continuous optimization and integer programming.

Olsen, Gregory R.↗

Generalized Linear Targeting For Cislunar Flight

An important element of Artemis and NASA’s campaign to explore the Moon is the autonomous onboard two-level targeter (TLT) used during all cislunar flight phases. The function of the TLT is to autonomously recompute the burn targets for the upcoming burn (or multiple burns) in response to navigation and vehicle dispersion providing a solution that meets all of the trajectory constraints. Although the TLT has been utilized previously as a ground-based planning tool, and flown onboard during the Artemis I mission, it’s complexity and iterative nature make is difficult to incorporate into and support rapid analyses such as robust optimal trajectory design applications where speed is essential. In this paper, a set of generalized linear targeting algorithms that mimics many of the properties of the TLT is derived. The generalized algorithms can handle single or multiple impulsive maneuvers, with multiple constraints at multiple fixed or variable times. A linear targeting algorithm for finite burn maneuvers is also derived. The generalized linear targeting algorithms are exceptionally fast and easy to implement in Monte Carlo analysis, linear covariance (LinCov) analysis, and robust optimal trajectory design. Several cislunar flight examples are provided.

Linear Covariance Analysis↗

WE-A-BRF-01: Dual-Energy CT Imaging in Diagnostic Imaging and Radiation Therapy

The quantification accuracy of dual-energy imaging is influenced by the fundamentals of x-ray physics, system geometry, data acquisition hardware/protocol, system calibration, and image processing technique. This symposium will provide updates on the following advanced application areas: Mammography. Volumetric breast density techniques based on standard mammograms require estimation of breast thickness, which is difficult to accurately measure. By comparison, calculation of breast density using dual energy mammography does not require measurement of breast thickness. Dual energy mammography has been implemented using both energy integrating flat panel detectors in conjunction with beam energy switching and energy resolved photon counting detectors. These techniques have been optimized using simulation studies and validated using physical phantoms and postmortem breasts. Chemical decomposition was used as the gold standard for volumetric breast density measurement in postmortem breasts. Breast density measurements have also been compared with results from four-category BI-RADS density rankings, standard image thresholding and Fuzzy k-mean clustering techniques. These studies indicate that dual energy mammography can be used to accurately measure volumetric breast density. Cardiovascular CT. The predicative accuracy of risk models for recurrent stroke and cardiac arrest depends heavily on accurate differentiation of thrombus or calcium from iodine in left atrial appendage or coronary arteries. The amount of energy separation is constrained by image noise; therefore, optimal kVp, beam filtration, and balanced flux are essential for the quantification accuracy of iodine and calcium. The basis materials are combined linearly to generate monochromatic energy images, where CT# accuracy and CNR are energy dependent. With optimal monochromatic energy, the mean iodine concentration for the thrombus, circulatory stasis, and control groups are significantly different. Risk classification based on calcium scores shows excellent agreement with classification on the basis of conventional coronary artery calcium scoring. These studies demonstrate dual-energy cardiovascular CT can potentially be a noninvasive and sensitive modality in high risk patients. On-board KV/MV Imaging. To enhance soft tissue contrast and reduce metal artifacts, we have developed a dual-energy CBCT technique and a novel on-board kV/MV imaging technique based on hardware available on modern linear accelerators. We have also evaluated the feasibility of these two techniques in various phantom studies. Optimal techniques (energy, beam filtration, # of overlapping projections, etc) have been investigated with unique calibration procedures, which leads to successful decomposition of imaged material into acrylic-aluminum basis material pair. This enables the synthesis of virtual monochromatic (VM) CBCT images that demonstrate much less beam hardening, significantly reduced metal artifacts, and/or higher soft tissue CNR compared to single-energy CBCT. Adaptive Radiation Therapy. DECT could actually contribute to the area of Dose-Guided Radiation Therapy (or Adaptive Therapy). The application of DECT imaging using 80kV and 140 kV combinations could potentially increase the image quality by reducing the bone or high density material artifacts and also increase the soft tissue contrast by a light contrast agent. The result of this higher contrast / quality images is beneficial for deformable image registration / segmentation algorithm to improve its accuracy hence to make adaptive therapy less time consuming in its recontouring process. The real time re-planning prior to per treatment fraction could become more realistic with this improvement especially in hypofractional SBRT cases. Learning Objectives: Learn recent developments of dual-energy imaging in diagnosis and radiation therapy; Understand the unique clinical problem and required quantification accuracy in each application; Understand the different approaches to optimize dual-energy imaging techniques for different applications.

60 APPLIED LIFE SCIENCES↗

CERN’s Linac4 H{sup −} sources: Status and operational results

Two volume sources equipped with DESY and CERN plasma generators and a low voltage electron dump were operated at 45 kV in the Linac4 tunnel and on a dedicated test stand. These volume sources delivered approximately 20 mA and ensured the commissioning of the Radio Frequency Quadrupole accelerator and of the first section of the Drift Tube Linac. CERN’s prototype of a cesiated surface source equipped with this electron dump was operated continuously from November 2013 to April 2014 on the ion source test stand and is being commissioned in the Linac4 tunnel. Before cesiation, the prototype conditioned in volume mode provided up to 30 mA H{sup −} beam. Short cesiations, of the order of 10 mg effectively reduced the intensity of co-extracted electrons down to 2 - 8 times the H{sup −} current; this cesiated surface operation mode delivered up to 60 mA H{sup −} beam. An H{sup −} beam of the order of 40 mA was sustained up to four weeks operation with 500 μs pulses at 1.2s spacing. A new extraction was designed to match these beam properties. A copy of BNL’s magnetron produced at CERN was tested at BNL and delivered at 40 kV H{sup −} beam exceeding Linac4’s nominal intensity of 80 mA. In this contribution, the performances, dynamic response to cesiation, stability and availability of these prototypes are described. The needed optimization of the emittance of H{sup −} beam above 40 mA is presented, which requires an evolution of the front end that encompasses implementation of a large ceramic insulator.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

SU-F-T-591: SBRT Treatment of Multiple Extracranial Oligometastases Using a Single-Isocenter with Distinct Optimizations (SIDO)

Purpose: A new development in linac-based intracranial radiosurgery is treatment of multiple targets using single isocenter VMAT, which dramatically reduces treatment time while maintaining high conformality and dose gradient. Our purpose is to translate this technique to extracranial SBRT of oligometastases and address additional challenges such as interplay from motion and setup uncertainties. Methods: We propose SIDO (Single Isocenter with Distinct Optimizations) planning in which all VMAT arcs share an isocenter but each arc treats only one target. Setup uncertainties from rotations and deformations are mitigated by applying a couch translation between VMAT arcs, while interplay is minimized by using dynamic conformal arcs (DCAs) as the starting point for VMAT optimization. We compared SIDO to single (VMAT) and dual (VMAT & DCA) isocenter plans for phantom and patient (N=2) cases. Dose statistics included conformity index (CI), gradient index (GI), and modulation factor (MLC opening & total MU). Finally, we determined likelihood of needing a translational shift between SIDO arcs to correct rotational uncertainties using CBCTs from eleven previous SBRT cases. Results: For phantoms with target separations of 5–15cm, CI was 0.87±0.02, 0.89±0.05, and 0.91±0.02, for SIDO, single, and dual-isocenter VMAT respectively. GI was 6.83±1.0, 7.45±1.0 and 5.94±0.7 respectively. SIDO conformity did not trend with increasing distance between PTVs, while gradient decreased for all planning techniques. Using DCAs as the starting point of VMAT optimization decreased modulation, with a 39.4% reduction in monitor units. SIDO had 4.9% and 39% less MU than single and dual-isocenter VMAT respectively. A translational shift between SIDO arcs would be required in 10–28% of cases due to rotational uncertainties to stay within a 5mm margin, for targets separated by ≥10cm. Conclusion: SIDO for extracranial oligometastases has comparable dosimetry to traditional VMAT with low modulation similar to DCAs. Future work will quantify decrease in dosimetric interplay.

60 APPLIED LIFE SCIENCES↗

Martian Aerocapture Terminal Point Guidance: A Reference Path Optimization Study

An effective method of terminal point guidance is to employ influence coefficients, which are solved from a set of differential equations adjoint to the linearized perturbations of the equations of motion about a reference trajectory. Hence, to optimize this type of guidance, one must first optimize the reference trajectory that the guidance is based upon. This study concentrates on various methods to optimize a reference trajectory for a Martian aerocapture maneuver, including a parametric analysis and first order gradient method. Resulting reference trajectories were tested in separate 2000 6-DOF Monte Carlo runs, using the Atmospheric Guidance Algorithm Testbed for the Mars Surveyor Program 2001 (MSP '01) Orbiter. These results were compared to an August 1998 study using the same terminal point control guidance algorithm and simulation testbed. Satisfactory improvements over the 1998 study are amply demonstrated.

Ro, Theodore U.↗

Dynamic implicit 3D adaptive mesh refinement for non-equilibrium radiation diffusion

The time dependent non-equilibrium radiation diffusion equations are important for solving the transport of energy through radiation in optically thick regimes and find applications in several fields including astrophysics and inertial confinement fusion. The associated initial boundary value problems that are encountered often exhibit a wide range of scales in space and time and are extremely challenging to solve. To efficiently and accurately simulate these systems we describe our research on combining techniques that will also find use more broadly for long term time integration of nonlinear multi-physics systems: implicit time integration for efficient long term time integration of stiff multi-physics systems, local control theory based step size control to minimize the required global number of time steps while controlling accuracy, dynamic 3D adaptive mesh refinement (AMR) to minimize memory and computational costs, Jacobian Free Newton–Krylov methods on AMR grids for efficient nonlinear solution, and optimal multilevel preconditioner components that provide level independent solver convergence.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

A Solar-assisted Voltage Optimization Method for Transmission Solar Network Power System

This paper proposes a new formulation and solution algorithm that uses transmission level solar inverters to address the security-constrained optimal power flow (SCOPF) problem. The goal is to stabilize voltage fluctuations in transmission networks in base case and contingency scenarios, by using bulk solar power plant with a minimal number of post-contingency corrections. To achieve this goal, a two-stage volt/var optimization method is proposed to first correct all voltage violations with the volt-var alternating current optimal power flow (ACOPF) algorithm for a base case. Then a linearized SCOPF volt-var control algorithm is proposed to identify the corrective actions for all potential voltage violations in all contingency scenarios. The proposed method was tested and validated on a modified IEEE 118-bus system with solar photovoltaic (PV) data.

Photovoltaic, Volt/Var Control↗

Optimal orbital rendezvous using high and low thrust

Optimal control theory is used to examine a specific class of spacecraft trajectory problems where high- and low-thrust propulsion systems are utilized. These problems assume a spacecraft is in an established orbit about a planet. It is desired to execute an intercept of a pre-determined position in space in a specified amount of time using an optimal high-thrust program. The spacecraft then returns to the original orbit station using the low-thrust propulsion system in an optimal fashion. A minimum fuel solution is sought using the linearized equations of motion, known as the CW equations, which simplify the necessary computations. Solutions are obtained for problems with a fixed final time. However, for the time-open case, the optimal solution is for the final time to be infinite. With a weighted function of the final time in the performance index, a limited range of optimal single impulse solutions for the time -open case can also be found.

Prussing, John E.↗

An interpretation and solution of ill-conditioned linear equations

Data insufficiency, poorly conditioned matrices and singularities in equations occur regularly in complex optimization, correlation, and interdisciplinary model studies. This work concerns itself with two methods of obtaining certain physically realistic solutions to ill-conditioned or singular algebraic systems of linear equations arising from such studies. Two efficient computational solution procedures that generally lead to locally unique solutions are presented when there is insufficient data to completely define the model, or a least-squares error formulation of this system results in an ill-conditioned system of equations. If it is assumed that a reasonable estimate of the uncertain data is available in both cases cited above, then we shall show how to obtain realistic solutions efficiently, in spite of the insufficiency of independent data. The proposed methods of solution are more efficient than singular-value decomposition for dealing with such systems, since they do not require solutions for all the non-zero eigenvalues of the coefficient matrix.

Ojalvo, I. U.↗

Optimizing HVAC Operations in Multi-unit Buildings for Grid Demand Response

The thermal inertia of buildings, along with the flexibility associated with thermostatically controlled loads (TCL) allows heating ventilation and cooling (HVAC) systems to be used for grid demand response (DR). In this work, we consider an HVAC system that serves multiple units in a residential building to meet their space heating requirements. We aim to determine the optimal power flow to each unit that minimizes the power costs incurred by the building's occupants while keeping in consideration their thermal comfort. The DR program is assumed to allow the building temperatures to deviate from the set-points up to a maximum limit. Despite the complex, non-linear structure of the problem, we show how the optimal solutions can be obtained efficiently using quadratic programming. Since HVAC systems can run on either electricity or natural gas, we study the efficacy of the DR regime for both hourly electricity prices and flat gas prices over the course of 24 hours. Finally, we run simulations to determine the optimal thermal power and the evolution of unit temperatures for various energy pricing schemes.

Naqvi, Syed A.↗

An Approach to Reasoning Service Migration in Data and Reasoning Fabric (DRF) Implementation

In this paper we consider service migration problem for Data and Reasoning Fabric (DRF) enabled airspace operations assuming a fixed cloud/edge infrastructure with allocated computing, storage and power resources, where cloud/edge servers, and communication stations are in a wired connected network, while vehicles use a wireless network for communication. The objective is to automatically select the best location for the requested service execution, which achieves minimum cost while satisfying the user quality of service (QoS) and available resources constraints. To this end, estimates of the response time, consumed energy and total cost are defined for each potential compute location. A mixed-integer linear program is then formulated and solved to identify optimal compute locations given QoS constraints, network infrastructure limitations, with worst-case vehicle positioning. The approach is applied to trajectory re-planning use case to avoid a collision with an emergency vehicle in real time.

Air mobility↗

Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization

High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.

Drake, R. L.↗

A genetic technique for planning a control sequence to navigate the state space with a quasi-minimum-cost output trajectory for a non-linear multi-dimnensional system

There are many multi-stage optimization problems that are not easily solved through any known direct method when the stages are coupled. For instance, we have investigated the problem of planning a vehicle's control sequence to negotiate obstacles and reach a goal in minimum time. The vehicle has a known mass, and the controlling forces have finite limits. We have developed a technique that finds admissible control trajectories which tend to minimize the vehicle's transit time through the obstacle field. The immediate applications is that of a space robot which must rapidly traverse around 2-or-3 dimensional structures via application of a rotating thruster or non-rotating on-off for such vehicles is located at the Marshall Space Flight Center in Huntsville Alabama. However, it appears that the development method is applicable to a general set of optimization problems in which the cost function and the multi-dimensional multi-state system can be any nonlinear functions, which are continuous in the operating regions. Other applications included the planning of optimal navigation pathways through a transversability graph; the planning of control input for under-water maneuvering vehicles which have complex control state-space relationships; the planning of control sequences for milling and manufacturing robots; the planning of control and trajectories for automated delivery vehicles; and the optimization and athletic training in slalom sports.

Hein, C.↗