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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Targeting accuracy of single-isocenter intensity-modulated radiosurgery for multiple lesions

To investigate the targeting accuracy of intensity-modulated SRS (IMRS) plans designed to simultaneously treat multiple brain metastases with a single isocenter. A home-made acrylic phantom able to support a film (EBT3) in its coronal plane was used. The phantom was CT scanned and three coplanar small targets (a central and two peripheral) were outlined in the Eclipse system. Peripheral targets were 6 cm apart from the central one. A reference IMRS plan was designed to simultaneously treat the three targets, but only a single isocenter located at the center of the central target was used. After positioning the phantom on the linac using the room lasers, a CBCT scan was acquired and the reference plan were mapped on it, by placing the planned isocenter at the intersection of the landmarks used in the film showing the linac isocenter. The mapped plan was then recalculated and delivered. The film dose distribution was derived using a cloud computing application ( (www.radiochromic.com)) that uses a triple-channel dosimetry algorithm. Comparison of dose distributions using the gamma index (5%/1 mm) were performed over a 5 × 5 cm{sup 2} region centered over each target. 2D shifts required to get the best gamma passing rates on the peripheral target regions were compared with the reported ones for the central target. The experiment was repeated ten times in different sessions. Average 2D shifts required to achieve optimal gamma passing rates (99%, 97%, 99%) were 0.7 mm (SD: 0.3 mm), 0.8 mm (SD: 0.4 mm) and 0.8 mm (SD: 0.3 mm), for the central and the two peripheral targets, respectively. No statistical differences (p > 0.05) were found for targeting accuracy between the central and the two peripheral targets. The study revealed a targeting accuracy within 1 mm for off-isocenter targets within 6 cm of the linac isocenter, when a single-isocenter IMRS plan is designed.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

A smooth contact algorithm for the combined finite discrete element method

From its inception, the combined finite discrete element method has used a distributed potential contact force algorithm to resolve interaction between finite elements. The contact interaction algorithm relies on evaluation of the contact force potential field. The problem with existing algorithms is that the potential field introduces artificial numerical non-smoothness in the contact force. This work introduces a smooth potential field based on the finite element topology, and a generalized contact interaction law is constructed on top of the smooth potential field. Further, a number of validation cases for the proposed algorithm, considering different shapes of discrete elements, are presented, and detailed aspects of the proposed contact interaction law are tested with numerical examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Optimization of an antenna array using genetic algorithms

An array of antennas is usually used in long distance communication. The observation of celestial objects necessitates a large array of antennas, such as the Giant Metrewave Radio Telescope (GMRT). Optimizing this kind of array is very important when observing a high performance system. The genetic algorithm (GA) is an optimization solution for these kinds of problems that reconfigures the position of antennas to increase the u-v coverage plane or decrease the sidelobe levels (SLLs). This paper presents how to optimize a correlator antenna array using the GA. A brief explanation about the GA and operators used in this paper (mutation and crossover) is provided. Then, the results of optimization are discussed. The results show that the GA provides efficient and optimum solutions among a pool of candidate solutions in order to achieve the desired array performance for the purposes of radio astronomy. The proposed algorithm is able to distribute the u-v plane more efficiently than GMRT with a more than 95% distribution ratio at snapshot, and to fill the u-v plane from a 20% to more than 68% filling ratio as the number of generations increases in the hour tracking observations. Finally, the algorithm is able to reduce the SLL to –21.75 dB.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

The CONTIN algorithm and its application to determine the size distribution of microgel suspensions

We review a powerful regularization method, known as CONTIN, for obtaining the size distribution of colloidal suspensions from dynamic light scattering data. We show that together with the so-called L-curve criterion for selecting the optimal regularization parameter, the method correctly describes the average size and size distribution of microgel suspensions independently characterized using small-angle neutron scattering. In contrast, we find that when using the default regularization process, where the regularizer is selected via the “probability to reject” method, the results are not as satisfactory.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Influence of computed tomography contrast agent on radiotherapy dose calculation for pancreatic carcinoma: A dosimetric study based on tomotherapy and volumetric-modulated arc therapy techniques

The main purpose of our investigation was to quantify the dosimetric influence of intravenous contrast agent for pancreatic cancer radiotherapy treatment. This study focused on complex modulated irradiation techniques of tomotherapy (TOMO) and volumetric-modulated arc therapy (VMAT) to investigate if novel conformal treatment methods could reduce the influence of contrast agent. In our study, patients with pancreatic cancer were enrolled to have 2 computed tomography (CT) scans in the same position without and with intravenous contrast agent for treatment planning. Then tumors and organ at risks were countered on contrast-enhanced CT (CECT) images. Each patient's CECT was assigned a TOMO plan and a VMAT plan. Then these plans were copied onto the non-CECT image and dose distribution was calculated with the same algorithm and structure sets. Finally, the dose distribution and the dose difference were analyzed for the target volume and organs at risk between the 2 sets of images. The statistic dosimetric result showed that for both TOMO and VMAT, no significant dose difference between CECT and non-CECT-based plan was observed. Dose difference was clinically negligible because the average relative percentage dose difference was 1% ± 1% for target volume, except a blurring effect at the higher dose region of the target volume. It implied that intravenous contrast agent will not affect dose calculation for pancreatic cancer radiotherapy significantly. Also the dose deviation based on TOMO showed no statistical difference compared with that on VMAT. For both superposition/conversation algorithm used by TOMO and Monte Carlo algorithm used by VMAT, the dosimetric difference was nonsignificant. A full analysis demonstrated a negligible dose difference of less than 1% between CECT-based plan and non-CECT-based plan. Therefore, contrast-enhanced CT image can be used directly for dose calculation of TOMO and VMAT plans for pancreatic cancer. It is unnecessary to scan twice then make a fusion of CECT and non-CECT, which would result to additional unnecessary radiation dose to patient and decrease work efficiency.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2019

A VSM-Based DER Dispatch MINLP for Volt-VAR Control in Unbalanced Power Distribution Systems

This paper presents an optimal dispatch algorithm to coordinate customer-owned controllable loads and smart solar inverters with utility-owned voltage regulators and capacitors to meet voltage control objectives. The optimization problem is formulated as a mixed-integer nonlinear programming (MINLP) problem. A voltage sensitivity matrix (VSM) is used to linearize the effect of control actions on the voltage at customer nodes when solving the MINLP. The VSM is recalculated at each time step to improve the computational accuracy. Both discrete switching actions of the capacitor and VRs and the continuous adjustment of real and reactive power from load and smart inverters are considered in the MINLP volt-var problem formulation. The objective function minimizes the cost of all control actions and the magnitude of voltage fluctuations from the previous time period. Constraints ensure that the voltage at each node is maintained within ANSI limits and the feeder power factor is controlled within the desired range. The algorithm is tested using an actual 3-phase unbalanced distribution feeder model. Simulation results demonstrate that the proposed algorithm is computationally feasible on real circuits and improves voltage control while minimizing operational costs.

McEntee, Catie↗
DOE OSTI2016

TH-AB-202-09: Direct-Aperture Optimization for Combined MV+kV Dose Planning in Fluoroscopic Real-Time Tumor-Tracking Radiation Therapy

Purpose: Real-time kV fluoroscopic tumor tracking has the benefit of direct tumor position monitoring. However, there is clinical concern over the excess kV imaging dose cost to the patient when imaging in continuous fluoroscopic mode. This work addresses this specific issue by proposing a combined MV+kV direct-aperture optimization (DAO) approach to integrate the kV imaging beam into a treatment planning such that the kV radiation is considered as a contributor to the overall dose delivery. Methods: The combined MV+kV DAO approach includes three algorithms. First, a projected Quasi-Newton algorithm (L-BFGS) is used to find optimized fluence with MV+kV dose for the best possible dose distribution. Then, Engel’s algorithm is applied to optimize the total number of monitor units and heuristically optimize the number of apertures. Finally, an aperture shape optimization (ASO) algorithm is applied to locally optimize the leaf positions of MLC. Results: Compared to conventional DAO MV plans with continuous kV fluoroscopic tracking, combined MV+kV DAO plan leads to a reduction in the total number of MV monitor units due to inclusion of kV dose as part of the PTV, and was also found to reduce the mean and maximum doses on the organs at risk (OAR). Compared to conventional DAO MV plan without kV tracking, the OAR dose in the combined MV+kV DAO plan was only slightly higher. DVH curves show that combined MV+kV DAO plan provided about the same PTV coverage as that in the conventional DAO plans without kV imaging. Conclusion: We report a combined MV+kV DAO approach that allows real time kV imager tumor tracking with only a trivial increasing on the OAR doses while providing the same coverage to PTV. The approach is suitable for clinic implementation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Graph Algorithms in PGAS: Chapel and UPC++

The Partitioned Global Address Space (PGAS) programming model can be implemented «««< HEAD either with programming language features or with runtime library APIs, each implementation favoring different aspects (e.g., productivity, abstraction, flexibility, or performance). Certain language and runtime features, such as collectives, explicit and asynchronous communication primitives, and constructs facilitating overlap of communication and computation (such as futures and conjoined futures) can enable better performance and scaling for irregular applications, in particular for distributed graph analytics. We compare graph algorithms in one of each of these environments: the Chapel PGAS programming language and the UPC++ PGAS runtime library. We implement algorithms for breadth-first search and triangle counting graph kernels in both environments. We discuss the code in each of the environments, and compile performance data on a Cray Aries and an Infiniband platform. Our results show that the library-based approach of UPC++ currently provides strong performance while Chapel provides a high-level abstraction that, harder to optimize, still provides comparable performance. We argue that various language primitives and runtime library features should be considered in conjunction with each other to design future graph analytics libraries so as to incorporate the best of both worlds.

Distributed Algorithms, Graph algorithms, HPC↗
DOE OSTI2017

A hybrid optimization algorithm to explore atomic configurations of TiO 2 nanoparticles

Here in this paper we present a hybrid algorithm comprised of differential evolution, coupled with the Broyden–Fletcher–Goldfarb–Shanno quasi-Newton optimization algorithm, for the purpose of identifying a broad range of (meta)stable Ti n O 2 n nanoparticles, as an example system, described by Buckingham interatomic potential. The potential and its gradient are modified to be piece-wise continuous to enable use of these continuous-domain, unconstrained algorithms, thereby improving compatibility. To measure computational effectiveness a regression on known structures is used. This approach defines effectiveness as the ability of an algorithm to produce a set of structures whose energy distribution follows the regression as the number of Ti n O 2n increases such that the shape of the distribution is consistent with the algorithm’s stated goals. Our calculation demonstrates that the hybrid algorithm finds global minimum configurations more effectively than the differential evolution algorithms, widely employed in the field of materials science. Specifically, the hybrid algorithm is shown to reproduce the global minimum energy structures reported in the literature up to n = 5, and retains good agreement with the regression up to n = 25. For 25 < n < 100, where literature structures are unavailable, the hybrid effectively obtains structures that are in lower energies per TiO 2 unit as the system size increases.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Adaptive Linear State Estimation for Unbalanced Distribution System

The inclusion of PMU functionality in distribution relays enables the implementation of a linear state estimator (LSE) in Distribution Systems (DS). However, the unbalanced topology and phase coupling in distribution lines necessitate modifications to the LSE formulation. Additionally, the higher fault frequency in distribution systems requires a state estimation approach that is resilient to contingencies. This work proposes an adaptive linear state estimation algorithm tailored for unbalanced distribution systems with single-phase and two-phase laterals. Furthermore, a modified Optimal PMU Placement (OPP) strategy is introduced to ensure full observability in distribution systems with single-phase and two-phase buses. To maintain adaptability to topology changes, the state estimator incorporates circuit breaker status data provided by PMUs, ensuring robust performance during topology changes triggered by faults. The performance of the algorithm is verified on the IEEE 13-bus, 34-bus, and 123-bus systems.

PMUs↗
DOE OSTI2020

Distributed Cooperative Control of Hybrid AC/DC Microgrid

This paper presents a distributed cooperative control-based power management algorithm for a hybrid AC/DC microgrid. The proposed algorithm for a hybrid microgrid system controls the power flow through the interface converter between the AC and DC microgrids. This algorithm allows power sharing between the distributed generators in the microgrid according to their power ratings. Moreover, it enables the fixed scheduled power delivery through the interface converters in both directions at different operating conditions while maintaining voltage regulation and improving the frequency profile. The effectiveness of the controller is confirmed by simulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Optimal Operation and Impact Assessment of Distributed Wind for Improving Efficiency and Resilience of Rural Electricity Systems

This project aims to empower rural utilities by developing advanced optimization models and algorithms for effectively integrating distributed wind energy alongside battery storage and other distributed energy resources (DERs). The primary objectives are to reduce peak demand, ensure reliable emergency power supply, and regulate voltage and frequency. To address operational challenges, the project introduces innovative mitigation strategies and ultrafast assessment frameworks to evaluate the impacts of distributed wind and DERs on rural grids, offering actionable solutions to potential issues. Economic viability is assessed through cost-benefit analysis using real rural utility data, ensuring the practical application of the project outcomes.

17 WIND ENERGY↗
DOE OSTI2019

Distributed Cooperative Control of Hybrid AC/DC Microgrid: Preprint

This paper presents a distributed cooperative control-based power management algorithm for a hybrid AC/DC microgrid. The proposed algorithm for a hybrid microgrid system controls the power flow through the interface converter between the AC and DC microgrids. This algorithm allows power sharing between the distributed generators in the microgrid according to their power ratings. Moreover, it enables the fixed scheduled power delivery through the interface converters in both directions at different operating conditions while maintaining voltage regulation and improving the frequency profile. The effectiveness of the controller is confirmed by simulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

MO-FG-BRA-01: Development of An Image-Guided Dosimetric Planning System for Injectable Brachytherapy Using ELP Nanoparticles

Purpose: To develop, validate, and evaluate a methodology for determining dosimetry for intratumoral injections of elastin-like-polypeptide (ELP) brachytherapy nanoparticles. These organic-polymer-based nanoparticles are injectable, biodegradable, and genetically tunable. We present a genetically encoded polymer-solution, composed of novel radiolabeled-ELP nanoparticles that are custom-designed to self-assemble into a local source upon intratumoral injection. Our preliminary results of a small animal study demonstrate 100% tumor response, effective radionuclide retention-rates, strong in vivo stability, and no polymer-induced toxicities. While our approach is therefore highly promising for improved brachytherapy, the current workflow lacks a dosimetry framework. Methods: We are developing a robust software framework that provides image-guided dosimetric-planning capabilities for ELP brachytherapy. The user graphically places ELP injection sites within a µCT-planning-image, and independently defines each injection volume, concentration, and radioisotope to be used. The resulting internal dosimetry is then pre-determined by first modeling post-injection ELP advection-diffusion, and then calculating the resulting dose distribution based on a point- dose-kernel-convolution algorithm. We have experimentally measured ELP steady-state concentrations via µSPECT acquisition, and validated our dose calculation algorithm against Monte Carlo simulations of several radioactivity distributions. Finally, we have investigated potential advantages and limitations of various ELP injection parameters. Results: The µSPECT results demonstrated inhomogeneous steady-state distributions of ELP in tissue, and Monte Carlo radioactivity distributions were designed accordingly. Our algorithm yielded a root-mean-square-error of less than 2% for each distribution tested (average root-mean-square-error was 0.73%). Dose-Volume-Histogram analysis of five different plans showed how strategic injection placement, and an injection volume-tapering technique, could be used to achieve D95% target coverage. Conclusion: We have preliminarily developed a novel planning framework for ELP brachytherapy. Its dosimetry accuracy has been validated against Monte Carlo, and we have started to investigate the potential advantages of injection-based planning. This system, once fully developed, will serve as the technical foundation for our novel approach.

60 APPLIED LIFE SCIENCES↗