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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Physics-assisted generative adversarial network for X-ray tomography

X-ray tomography is capable of imaging the interior of objects in three dimensions non-invasively, with applications in biomedical imaging, materials science, electronic inspection, and other fields. The reconstruction process can be an ill-conditioned inverse problem, requiring regularization to obtain satisfactory results. Recently, deep learning has been adopted for tomographic reconstruction. Unlike iterative algorithms which require a distribution that is known a priori , deep reconstruction networks can learn a prior distribution through sampling the training distributions. In this work, we develop a Physics-assisted Generative Adversarial Network (PGAN), a two-step algorithm for tomographic reconstruction. In contrast to previous efforts, our PGAN utilizes maximum-likelihood estimates derived from the measurements to regularize the reconstruction with both known physics and the learned prior. Compared with methods with less physics assisting in training, PGAN can reduce the photon requirement with limited projection angles to achieve a given error rate. The advantages of using a physics-assisted learned prior in X-ray tomography may further enable low-photon nanoscale imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2018

Coordinated Use of Smart Inverters with Legacy Voltage Regulating Devices in Distribution Systems with High Distributed PV Penetration — Increase CVR Energy Savings

This paper studies the coordinated use of smart inverters with legacy voltage regulating devices to help increase the energy savings from conservation voltage reduction (CVR) in distribution systems with high photovoltaic penetration. Two voltage optimization algorithms are developed to evaluate the CVR benefit by considering two types of smart inverter functions: aggregated reactive power control and autonomous volt/VAR control. In each algorithm, smart inverters are coordinately controlled with the operation of legacy voltage regulating devices including load tap changers and capacitor banks. Both algorithms are tested on representative utility distribution system models. In conclusion, simulation results demonstrate that the proposed algorithms can achieve around 1.8-3.6% energy savings when only using legacy voltage regulating devices and an additional 0.3-0.9% when adding smart inverters.

14 SOLAR ENERGY↗
DOE OSTI2019

Online Stochastic Optimization of Networked Distributed Energy Resources

Our work investigates distributed control and incentive mechanisms to coordinate distributed energy resources (DERs) with both continuous and discrete decision variables as well as device dynamics in distribution grids. We formulate a multi-period social welfare maximization problem, and based on its convex relaxation propose a distributed stochastic dual gradient algorithm for managing DERs. Moreover, we extend it to an online realtime setting with time-varying operating conditions, asynchronous updates by devices, and feedback being leveraged to account for nonlinear power flows as well as reduce communication overhead. The resulting algorithm provides a general online stochastic optimization algorithm for coordinating networked DERs with discrete power setpoints and dynamics to meet operational and economic objectives and constraints. We characterize the convergence of the algorithm analytically and evaluate its performance numerically.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

A Hierarchical VLSM-Based Demand Response Strategy for Coordinative Voltage Control between Transmission and Distribution Systems

This paper presents a two-stage hierarchical voltage-load sensitivity matrix (VLSM)-based demand response (DR) algorithm for regulating the voltage at distribution feeders while fulfilling the transmission system DR requests. This allows distributed energy resources be aggregated to provide transmission-level services without causing operational issues in the distribution grids. At the beginning of each operation interval, a transmission system controller will issue DR commands to distribution system controllers. In the first stage, the distribution system controller uses a VLSM-based dispatch algorithm to dispatch the available DR resources on the distribution feeder with an objective to minimize the total voltage deviations at the lowest cost. Then, power flow studies are conducted assuming that the DR commands have been executed. If voltage violations are detected, a second-stage VLSM-based DR dispatch will be performed to remove those violations. After that, the upper and lower DR limits calculated for the next operation interval are sent back to the transmission system controller so the transmission optimization algorithm can use them as operational constraints to make subsequent decisions. The DR resources include smart photovoltaic (PV) inverters that can curtail real power and provide reactive power support, controllable loads and capacitor banks. In conclusion, the IEEE 123-bus test system with 5-minute PV and load data is used to evaluate the performance of the algorithm. In conclusion, simulation results show that the proposed algorithm can fulfill the transmission-level DR requests while maintaining the voltage in the distribution system within limits.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Critical Appraisal of Acuros XB and Anisotropic Analytic Algorithm Dose Calculation in Advanced Non-Small-Cell Lung Cancer Treatments

Purpose: To assess the clinical impact of the Acuros XB algorithm (implemented in the Varian Eclipse treatment-planning system) in non-small-cell lung cancer (NSCLC) cases. Methods and Materials: A CT dataset of 10 patients presenting with advanced NSCLC was selected and contoured for planning target volume, lungs, heart, and spinal cord. Plans were created for 6-MV and 15-MV beams using three-dimensional conformal therapy, intensity-modulated therapy, and volumetric modulated arc therapy with RapidArc. Calculations were performed with Acuros XB and the Anisotropic Analytical Algorithm. To distinguish between differences coming from the different heterogeneity management and those coming from the algorithm and its implementation, all the plans were recalculated assigning Hounsfield Unit (HU) = 0 (Water) to the CT dataset. Results: Differences in dose distributions between the two algorithms calculated in Water were <0.5%. This suggests that the differences in the real CT dataset can be ascribed mainly to the different heterogeneity management, which is proven to be more accurate in the Acuros XB calculations. The planning target dose difference was stratified between the target in soft tissue, where the mean dose was found to be lower for Acuros XB, with a range of 0.4% {+-} 0.6% (intensity-modulated therapy, 6 MV) to 1.7% {+-} 0.2% (three-dimensional conformal therapy, 6 MV), and the target in lung tissue, where the mean dose was higher for 6 MV (from 0.2% {+-} 0.2% to 1.2% {+-} 0.5%) and lower for 15 MV (from 0.5% {+-} 0.5% to 2.0% {+-} 0.9%). Mean doses to organs at risk presented differences up to 3% of the mean structure dose in the worst case. No particular or systematic differences were found related to the various modalities. Calculation time ratios between calculation time for Acuros XB and the Anisotropic Analytical Algorithm were 7 for three-dimensional conformal therapy, 5 for intensity-modulated therapy, and 0.2 for volumetric modulated arc therapy with RapidArc. Conclusion: The availability of Acuros XB could improve patient dose estimation, increasing the data consistency of clinical trials.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Performance Evaluation of Peer-to-Peer Distributed Microgrids Coordination for Voltage Regulation

This paper presents the performance evaluation of a peer-to-peer microgrids coordination algorithm for sub-transmission systems. As distributed energy resources (DERs) in distribution system start to show negative impact to the bulk power system, a paradigm shift is needed for transmission planning and operation. Because distribution substations are located far from the sub-transmission system, and it is hard to use traditional centralized control for real-time control and coordination. Thus, distributed control is a natural choice because it requires less communication and central computation. In this paper, each distribution substation is treated as a microgrid, and the peer-to-peer distributed microgrids control is formulated as a real-time optimal power flow problem to reduce the negative impact in sub-transmission systems. A distributed primal-dual optimization algorithm is adopted to solve the problem. Validation of the peer-to-peer algorithm is performed through the simulation of a real-world sub-transmission system composing of many distribution systems with high renewable penetration. Simulation results show that the peer-to-peer algorithm can achieve satisfactory performance (e.g., voltage regulation) in sub-transmission system by coordinating and controlling DERs in distribution systems.

distributed control↗
DOE OSTI2014

SU-E-J-55: Dosimetric Evaluation of Centrally Located Lung Tumors: A Monte Carlo (MC) Study of Lung SBRT Planning

Purpose: To compare dose distributions calculated using the iPlan XVMC algorithm and heterogeneities corrected/uncorrected Pencil Beam (PB-hete/PB-homo) algorithms for SBRT treatments of lung tumors. Methods: Ten patients with centrally located solitary lung tumors were treated using MC-based SBRT to 60Gy in 5 fractions for PTVV100%=95%. ITV was delineated on MIP-images based on 4D-CT scans. PTVs(ITV+5mm margins) ranged from 10.1–106.5cc(mean=48.6cc). MC-SBRT plans were generated with a combination of non-coplanar conformal arcs/beams using iPlan-XVMC-algorithm (BrainLABiPlan ver.4.1.2) for Novalis-TX consisting of HD-MLCs and 6MV-SRS(1000MU/min) mode, following RTOG 0813 dosimetric criteria. For comparison, PB-hete/PB-homo algorithms were used to re-calculate dose distributions using same beam configurations, MLCs/monitor units. Plans were evaluated with isocenter/maximal/mean doses to PTV. Normal lung doses were evaluated with V5/V10/V20 and mean-lung-dose(MLD), excluding PTV. Other OAR doses such as maximal spinal cord/2cc-esophagus/max bronchial tree (BT/maximal heart doses were tabulated. Results: Maximal/mean/isocenter doses to PTV calculated by PB-hete were uniformly larger than MC plans by a factors of 1.09/1.13/1.07, on average, whereas they were consistently lower by PB-homo by a factors of 0.9/0.84/0.9, respectively. The volume covered by 5Gy/10Gy/20Gy isodose-lines of the lung were comparable (average within±3%) when calculated by PB-hete compared to XVMC, but, consistently lower by PB-homo by a factors of 0.90/0.88/0.85, respectively. MLD was higher with PB-hete by 1.05, but, lower by PB-homo by 0.9, on average, compared to XVMC. XVMC max-cord/max-BT/max-heart and 2cc of esophagus doses were comparable to PB-hete; however, PB-homo underestimates by a factors of 0.82/0.89/0.88/0.86, on average, respectively. Conclusion: PB-hete significantly overestimates dose to PTV relative to XVMC -hence underdosing the target. MC is more complex and accurate with tissue-heterogeneities.The magnitude of variation significantly varies with ‘small-island-tumor’ surrounded by low-density lung tissues -PB algorithms lacks later electron scattering. Dose calculation with XVMC for lung SBRT is routinely performed in our clinic, its performance for head'neck/sinus cases will also be investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Distributed-Memory Breadth-First Search on Massive Graphs. IN: Parallel Graph Algorithms

This chapter studies the problem of traversing large graphs using the breadth-first search order on distributed-memory supercomputers. We consider both the traditional level-synchronous top-down algorithm as well as the recently discovered direction optimizing algorithm. We analyze the performance and scalability trade-offs in using different local data structures such as CSR and DCSC, enabling in-node multithreading, and graph decompositions such as 1D and 2D decomposition.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

SU-F-T-74: Experimental Validation of Monaco Electron Monte Carlo Dose Calculation for Small Fields

Purpose: To verify experimentally the accuracy of Monaco (Elekta) electron Monte Carlo (eMC) algorithm to calculate small field size depth doses, monitor units and isodose distributions. Methods: Beam modeling of eMC algorithm was performed for electron energies of 6, 9, 12 15 and 18 Mev for a Elekta Infinity Linac and all available ( 6, 10, 14 20 and 25 cone) applicator sizes. Electron cutouts of incrementally smaller field sizes (20, 40, 60 and 80% blocked from open cone) were fabricated. Dose calculation was performed using a grid size smaller than one-tenth of the R{sub 80–20} electron distal falloff distance and number of particle histories was set at 500,000 per cm{sup 2}. Percent depth dose scans and beam profiles at dmax, d{sub 90} and d{sub 80} depths were measured for each cutout and energy with Wellhoffer (IBA) Blue Phantom{sup 2} scanning system and compared against eMC calculated doses. Results: The measured dose and output factors of incrementally reduced cutout sizes (to 3cm diameter) agreed with eMC calculated doses within ± 2.5%. The profile comparisons at dmax, d{sub 90} and d{sub 80} depths and percent depth doses at reduced field sizes agreed within 2.5% or 2mm. Conclusion: Our results indicate that the Monaco eMC algorithm can accurately predict depth doses, isodose distributions, and monitor units in homogeneous water phantom for field sizes as small as 3.0 cm diameter for energies in the 6 to 18 MeV range at 100 cm SSD. Consequently, the old rule of thumb to approximate limiting cutout size for an electron field determined by the lateral scatter equilibrium (E (MeV)/2.5 in centimeters of water) does not apply to Monaco eMC algorithm.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Clustering at Massive Scale

ClaMS provides hierarchical clustering technology for use on massive, high-dimensional datasets that require distributed memory for processing. The algorithm employed is inspired by the popular HDBSCAN algorithm but makes use of computational kernels better suited for distributed computing. ClaMS is built on scalable nearest neighbor graph construction, metric forest completion, and approximate minimum spanning tree techniques.

Stanley, ThomasA [Lawrence Livermore National Labo↗
DOE OSTI2022

Performance Evaluation of Peer-to-Peer Distributed Microgrids Coordination for Voltage Regulation: Preprint

This paper presents the performance evaluation of a peer-to-peer microgrids coordination algorithm for sub-transmission systems. As distributed energy resources (DERs) in distribution system start to show negative impact to the bulk power system, a paradigm shift is needed for transmission planning and operation. Because distribution substations are located far from the sub-transmission system, and it is hard to use traditional centralized control for real-time control and coordination. Thus, distributed control is a natural choice because it requires less communication and central computation. In this paper, each distribution substation is treated as a microgrid, and the peer-to-peer distributed microgrids control is formulated as a real-time optimal power flow problem to reduce the negative impact in sub-transmission systems. A distributed primal-dual optimization algorithm is adopted to solve the problem. Validation of the peer-to-peer algorithm is performed through the simulation of a real-world sub-transmission system composing of many distribution systems with high renewable penetration. Simulation results show that the peer-to-peer algorithm can achieve satisfactory performance (e.g., voltage regulation) in sub-transmission system by coordinating and controlling DERs in distribution systems.

distributed control↗
DOE OSTI2026

Particle Tracking Methods for Battery Precipitation Reactions

Precipitation and deposition reactions at solid–liquid interfaces play a key role in a number of battery chemistries, including Li-ion, so-called “anode free” batteries, zinc-based battery chemistries, and lithium–sulfur, among others. Although models with heterogeneous nucleation and growth phenomena are present in the literature, papers have not to date provided much detail on the numerical algorithms used to track the temporal evolution of the particle size distribution of deposits on electrode surfaces. In this paper we examine several approaches to discretize and track the particle size distribution, demonstrating that common approaches lead to anomalous flattening of the particle size distribution. We conclude by presenting an algorithm that preserves the appropriate particle size distribution during particle growth.

Algorithms↗
DOE OSTI2026

Beam loss modeling and mitigation due to intra-beam stripping

Intra-Beam Stripping (IBS) is a critical beam loss mechanism in high-intensity H- linacs and presents a significant limitation to increasing beam power. This work presents a computational framework to evaluate and mitigate IBS-induced beam loss along the Spallation Neutron Source (SNS) LINAC. Our calculation is based on an analytic theory and involves evaluation of a 9D integral using the Monte-Carlo technique. We first benchmarked our calculations against simplified, analytically solvable cases. We then applied our algorithm to Gaussian bunches with a known probability density function (PDF). We next expanded our algorithm to arbitrary bunch distributions using the Neural Spline Flow (NSF) models trained on PyORBIT tracking data. In the future, we plan to validate our algorithm experimentally and apply it to design IBS mitigation strategies.

Nln, Shivam [ORNL]↗
DOE OSTI2013

Adaptation of the CVT algorithm for catheter optimization in high dose rate brachytherapy

Purpose: An innovative, simple, and fast method to optimize the number and position of catheters is presented for prostate and breast high dose rate (HDR) brachytherapy, both for arbitrary templates or template-free implants (such as robotic templates).Methods: Eight clinical cases were chosen randomly from a bank of patients, previously treated in our clinic to test our method. The 2D Centroidal Voronoi Tessellations (CVT) algorithm was adapted to distribute catheters uniformly in space, within the maximum external contour of the planning target volume. The catheters optimization procedure includes the inverse planning simulated annealing algorithm (IPSA). Complete treatment plans can then be generated from the algorithm for different number of catheters. The best plan is chosen from different dosimetry criteria and will automatically provide the number of catheters and their positions. After the CVT algorithm parameters were optimized for speed and dosimetric results, it was validated against prostate clinical cases, using clinically relevant dose parameters. The robustness to implantation error was also evaluated. Finally, the efficiency of the method was tested in breast interstitial HDR brachytherapy cases.Results: The effect of the number and locations of the catheters on prostate cancer patients was studied. Treatment plans with a better or equivalent dose distributions could be obtained with fewer catheters. A better or equal prostate V100 was obtained down to 12 catheters. Plans with nine or less catheters would not be clinically acceptable in terms of prostate V100 and D90. Implantation errors up to 3 mm were acceptable since no statistical difference was found when compared to 0 mm error (p > 0.05). No significant difference in dosimetric indices was observed for the different combination of parameters within the CVT algorithm. A linear relation was found between the number of random points and the optimization time of the CVT algorithm. Because the computation time decrease with the number of points and that no effects were observed on the dosimetric indices when varying the number of sampling points and the number of iterations, they were respectively fixed to 2500 and to 100. The computation time to obtain ten complete treatments plans ranging from 9 to 18 catheters, with the corresponding dosimetric indices, was 90 s. However, 93% of the computation time is used by a research version of IPSA. For the breast, on average, the Radiation Therapy Oncology Group recommendations would be satisfied down to 12 catheters. Plans with nine or less catheters would not be clinically acceptable in terms of V100, dose homogeneity index, and D90.Conclusions: The authors have devised a simple, fast and efficient method to optimize the number and position of catheters in interstitial HDR brachytherapy. The method was shown to be robust for both prostate and breast HDR brachytherapy. More importantly, the computation time of the algorithm is acceptable for clinical use. Ultimately, this catheter optimization algorithm could be coupled with a 3D ultrasound system to allow real-time guidance and planning in HDR brachytherapy.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2017

Probabilistic Cosmological Mass Mapping from Weak Lensing Shear

We infer gravitational lensing shear and convergence fields from galaxy ellipticity catalogs under a spatial process prior for the lensing potential. We demonstrate the performance of our algorithm with simulated Gaussian-distributed cosmological lensing shear maps and a reconstruction of the mass distribution of the merging galaxy cluster Abell 781 using galaxy ellipticities measured with the Deep Lens Survey. Given interim posterior samples of lensing shear or convergence fields on the sky, we describe an algorithm to infer cosmological parameters via lens field marginalization. In the most general formulation of our algorithm we make no assumptions about weak shear or Gaussian-distributed shape noise or shears. Because we require solutions and matrix determinants of a linear system of dimension that scales with the number of galaxies, we expect our algorithm to require parallel high-performance computing resources for application to ongoing wide field lensing surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

External beam planning module of Eclipse for external beam radiation therapy

Eclipse is a 3-dimensional (3D) treatment planning system for radiation therapy offered by Varian Medical Systems, Inc. The system has the network connectivity for the electronic transfer of image datasets and digital data communication among different equipment. The scope of this project for this special issue of Medical Dosimetry on 3D treatment planning systems is the assessment of planning tools in the external beam planning module of Eclipse to generate optimized treatment plans for patients undergoing external beam radiation therapy. This treatment planning system is relatively mature to be able to generate (1) simple treatment plans, (2) conformal radiation therapy plans, (3) static intensity-modulated radiation therapy (IMRT) plans, (4) volumetric-modulated arc therapy (VMAT) plans, and (5) treatment plans for electron beam therapy. The treatment planning tools are relatively plentiful to assist in the radiation therapy treatment planning. Some new features have been incorporated in the latest version and are helpful for making high-quality treatment plans. However, the location of the tools is not intuitive, and hence, familiarity with the user interface is essential to the efficient use of the treatment planning system. In addition, there are a number of dose algorithms available for the computation of dose distributions. The understanding of each dose computation algorithm is essential for the optimal use of this treatment planning system.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

SU-C-204-01: A Fast Analytical Approach for Prompt Gamma and PET Predictions in a TPS for Proton Range Verification

Purpose: We describe and demonstrate a fast analytical tool for prompt-gamma emission prediction based on filter functions applied on the depth dose profile. We present the implementation in a treatment planning system (TPS) of the same algorithm for positron emitter distributions. Methods: The prediction of the desired observable is based on the convolution of filter functions with the depth dose profile. For both prompt-gammas and positron emitters, the results of Monte Carlo simulations (MC) are compared with those of the analytical tool. For prompt-gamma emission from inelastic proton-induced reactions, homogeneous and inhomogeneous phantoms alongside with patient data are used as irradiation targets of mono-energetic proton pencil beams. The accuracy of the tool is assessed in terms of the shape of the analytically calculated depth profiles and their absolute yields, compared to MC. For the positron emitters, the method is implemented in a research RayStation TPS and compared to MC predictions. Digital phantoms and patient data are used and positron emitter spatial density distributions are analyzed. Results: Calculated prompt-gamma profiles agree with MC within 3 % in terms of absolute yield and reproduce the correct shape. Based on an arbitrary reference material and by means of 6 filter functions (one per chemical element), profiles in any other material composed of those elements can be predicted. The TPS implemented algorithm is accurate enough to enable, via the analytically calculated positron emitters profiles, detection of range differences between the TPS and MC with errors of the order of 1–2 mm. Conclusion: The proposed analytical method predicts prompt-gamma and positron emitter profiles which generally agree with the distributions obtained by a full MC. The implementation of the tool in a TPS shows that reliable profiles can be obtained directly from the dose calculated by the TPS, without the need of full MC simulation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

MO-FG-CAMPUS-TeP2-05: Optimizing Stereotactic Radiosurgery Treatment of Multiple Brain Metastasis Lesions with Individualized Rotational Arc Trajectories

Purpose: Radiosurgery of multiple (n>4) brain metastasis lesions requires 3–4 noncoplanar VMAT arcs with excessively high monitor units and long delivery time. We investigated whether an improved optimization technique would decrease the needed arc numbers and increase the delivery efficiency, while improving or maintaining the plan quality. Methods: The proposed 4pi arc space optimization algorithm consists of two steps: automatic couch angle selection followed by aperture generation for each arc with optimized control points distribution. We use a greedy algorithm to select the couch angles. Starting from a single coplanar arc plan we search through the candidate noncoplanar arcs to pick a single noncoplanar arc that will bring the best plan quality when added into the existing treatment plan. Each time, only one additional noncoplanar arc is considered making the calculation time tractable. This process repeats itself until desired number of arc is reached. The technique is first evaluated in coplanar arc delivery scheme with testing cases and then applied to noncoplanar treatments of a case with 12 brain metastasis lesions. Results: Clinically acceptable plans are created within minutes. For the coplanar testing cases the algorithm yields singlearc plans with better dose distributions than that of two-arc VMAT, simultaneously with a 12–17% reduction in the delivery time and a 14–21% reduction in MUs. For the treatment of 12 brain mets while Paddick conformity indexes of the two plans were comparable the SCG-optimization with 2 arcs (1 noncoplanar and 1 coplanar) significantly improved the conventional VMAT with 3 arcs (2 noncoplanar and 1 coplanar). Specifically V16 V10 and V5 of the brain were reduced by 11%, 11% and 12% respectively. The beam delivery time was shortened by approximately 30%. Conclusion: The proposed 4pi arc space optimization technique promises to significantly reduce the brain toxicity while greatly improving the treatment efficiency.

60 APPLIED LIFE SCIENCES↗