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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

SU-E-T-536: Inhomogeneity Correction in Planning of Gamma Knife Treatments for Acoustic Schwannoma

Purpose: To find out the dose difference on targets and organs at risk for the treatment of acoustic schwannoma if the inhomogeneity correction (Convolution algorithm) is applied. Methods: Images of patients treated for acoustic schwannoma with Gamma Knife using TMR 10 algorithm were retrieved from database and replanned with Convolution and TMR 10 algorithm respectively. These patients were treated using a preplan scheme in following: (1) Before the actual treatment day, using the MRI image that was taken without a head frame on the patient's skull, a pre-treatment plan was made based on the default skull coordinates in the Gamma Knife treatment planning system (LGP); (2) then on treatment day, a head frame was placed on the patient's skull, and a CT image was taken. The CT image with head frame was registered and fused with the completed preplan; (3) the treatment plan was finalized and the treatment was delivered. To find out the dosimetry impact of inhomogeneity correction, we used the retrieved CT images to replan the treatment using Convolution algorithm in LGP software version 10.1.1. The dose distributions and the dose volume histograms for targets and OARs were compared for these two dose calculation algorithms. Results: The dose calculated with the Convolution algorithm in general is slightly lower than the one from TMR 10 around the boney area. The effect from the inhomogeneity correction is observable but not significant, and varies with the location of the tumor. Conclusion: Inhomogeneity correction slightly improve the dose accuracy for acoustic schwannoma Gamma Knife treatments although the correction may not be very significant. Our Result provides evidence for dose prescription adjustment to treat acoustic schwannoma. The actual clinical outcome of switching from using TMR10 to using Convolution needs to be further investigated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Stochastic characterization of phase detection algorithms in phase-shifting interferometry

Phase-shifting interferometry (PSI) is the preferred non-contact method for profiling sub-nanometer surfaces. Based on monochromatic light interference, the method computes the surface profile from a set of interferograms collected at separate stepping positions. Errors in the estimated profile are introduced when these positions are not located correctly. In order to cope with this problem, various algorithms that minimize the effects of certain types of stepping errors (linear, sinusoidal, etc.) have been developed. Despite the relatively large number of algorithms suggested in the literature, there is no unified way of characterizing their performance when additional unaccounted random errors are present. Here, we suggest a procedure for quantifying the expected behavior of each algorithm in the presence of independent and identically distributed (i.i.d.) random stepping errors, which can occur in addition to the systematic errors for which the algorithm has been designed. As a result, the usefulness of this method derives from the fact that it can guide the selection of the best algorithm for specific measurement situations.

42 ENGINEERING↗
DOE OSTI2012

Influence of robust optimization in intensity-modulated proton therapy with different dose delivery techniques

Purpose: The distal edge tracking (DET) technique in intensity-modulated proton therapy (IMPT) allows for high energy efficiency, fast and simple delivery, and simple inverse treatment planning; however, it is highly sensitive to uncertainties. In this study, the authors explored the application of DET in IMPT (IMPT-DET) and conducted robust optimization of IMPT-DET to see if the planning technique's sensitivity to uncertainties was reduced. They also compared conventional and robust optimization of IMPT-DET with three-dimensional IMPT (IMPT-3D) to gain understanding about how plan robustness is achieved. Methods: They compared the robustness of IMPT-DET and IMPT-3D plans to uncertainties by analyzing plans created for a typical prostate cancer case and a base of skull (BOS) cancer case (using data for patients who had undergone proton therapy at our institution). Spots with the highest and second highest energy layers were chosen so that the Bragg peak would be at the distal edge of the targets in IMPT-DET using 36 equally spaced angle beams; in IMPT-3D, 3 beams with angles chosen by a beam angle optimization algorithm were planned. Dose contributions for a number of range and setup uncertainties were calculated, and a worst-case robust optimization was performed. A robust quantification technique was used to evaluate the plans' sensitivity to uncertainties. Results: With no uncertainties considered, the DET is less robust to uncertainties than is the 3D method but offers better normal tissue protection. With robust optimization to account for range and setup uncertainties, robust optimization can improve the robustness of IMPT plans to uncertainties; however, our findings show the extent of improvement varies. Conclusions: IMPT's sensitivity to uncertainties can be improved by using robust optimization. They found two possible mechanisms that made improvements possible: (1) a localized single-field uniform dose distribution (LSFUD) mechanism, in which the optimization algorithm attempts to produce a single-field uniform dose distribution while minimizing the patching field as much as possible; and (2) perturbed dose distribution, which follows the change in anatomical geometry. Multiple-instance optimization has more knowledge of the influence matrices; this greater knowledge improves IMPT plans' ability to retain robustness despite the presence of uncertainties.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2023

Distributed Energy Management for Networked Microgrids with Hardware-in-the-Loop Validation

For the cooperative operation of networked microgrids, a distributed energy management considering network operational objectives and constraints is proposed in this work. Considering various ownership and privacy requirements of microgrids, utility directly interfaced distributed energy resources (DERs) and demand response, a distributed optimization is proposed for obtaining optimal network operational objectives with constraints satisfied through iteratively updated price signals. The alternating direction method of multipliers (ADMM) algorithm is utilized to solve the formulated distributed optimization. The proposed distributed energy management provides microgrids, utility-directly interfaced DERs and responsive demands the opportunity of contributing to better network operational objectives while preserving their privacy and autonomy. Results of numerical simulation using a networked microgrids system consisting of several microgrids, utility directly interfaced DERs and responsive demands validate the soundness and accuracy of the proposed distributed energy management. The proposed method is further tested on a practical two-microgrid system located in Adjuntas, Puerto Rico, and the applicability of the proposed strategy is validated through hardware-in-the-loop (HIL) testing.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Poster — Thur Eve — 11: Validation of the orthopedic metallic artifact reduction tool for CT simulations at the Ottawa Hospital Cancer Centre

Metallic implants in patients can produce image artifacts in kilovoltage CT simulation images which can introduce noise and inaccuracies in CT number, affecting anatomical segmentation and dose distributions. The commercial orthopedic metal artifact reduction algorithm (O-MAR) (Philips Healthcare System) was recently made available on CT simulation scanners at our institution. This study validated the clinical use of O-MAR by investigating its effects on CT number and dose distributions. O-MAR corrected and uncorrected images were acquired with a Philips Brilliance Big Bore CT simulator of a cylindrical solid water phantom that contained various plugs (including metal) of known density. CT number accuracy was investigated by determining the mean and standard deviation in regions of interest (ROI) within each plug for uncorrected and O-MAR corrected images and comparing with no-metal image values. Dose distributions were calculated using the Monaco treatment planning system. Seven open fields were equally spaced about the phantom around a ROI near the center of the phantom. These were compared to a “correct” dose distribution calculated by overriding electron densities a no-metal phantom image to produce an image containing metal but no artifacts. An overall improvement in CT number and dose distribution accuracy was achieved by applying the O-MAR correction. Mean CT numbers and standard deviations were found to be generally improved. Exceptions included lung equivalent media, which is consistent with vendor specified contraindications. Dose profiles were found to vary by ±4% between uncorrected or O-MAR corrected images with O-MAR producing doses closer to ground truth.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-F-19A-01: APBI Brachytherapy Treatment Planning: The Impact of Heterogeneous Dose Calculations

Purpose: To quantify the difference in dose to PTV-EVAL and OARs (skin and rib) as calculated by (TG43) and heterogeneous calculations (CCC). Methods: 25 patient plans (5 Contura and 20 SAVI) were selected for analysis. Clinical dose distributions were computed with a commercially available treatment planning algorithm (TG43-D-(w,w)) and then recomputed with a pre-clinical collapsed cone convolution algorithm (CCCD-( m,m)). PTV-EVAL coverage (V90%, V95%), and rib and skin maximum dose were compared via percent difference. Differences in dose to normal tissue (V150cc, V200cc of PTV-EVAL) were also compared. Changes in coverage and maximum dose to organs at risk are reported in percent change, (100*(TG43 − CCC) / TG43)), and changes in maximum dose to normal tissue are absolute change in cc (TG43 − CCC). Results: Mean differences in V90, V95, V150, and V200 for the SAVI cases were −0.2%, −0.4%, −0.03cc, and −0.14cc, respectively, with maximum differences of −0.78%, −1.7%, 1.28cc, and 1.01cc, respectively. Mean differences in the 0.1cc dose to the rib and skin were −1.4% and −0.22%, respectively, with maximum differences of −4.5% and 16%, respectively. Mean differences in V90, V95, V150, and V200 for the Contura cases were −1.2%, −2.1%, −1.8cc, and −0.59cc, respectively, with maximum differences of −2.0%, −3.16%, −2.9cc, and −0.76cc, respectively. Mean differences in the 0.1cc dose to the rib and skin were −2.6% and −3.9%, respectively, with maximum differences of −3.2% and −5.7%, respectively. Conclusion: The effects of translating clinical knowledge based on D-(w,w) to plans reported in D-(m,m) are minimal (2% or less) on average, but vary based on the type and placement of the device, source, and heterogeneity information.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Scalable FBP decomposition for cone-beam CT reconstruction

Filtered Back-Projection (FBP) is a fundamental compute intense algorithm used in tomographic image reconstruction. Cone-Beam Computed Tomography (CBCT) devices use a cone-shaped X-ray beam, in comparison to the parallel beam used in older CT generations. Distributed image reconstruction of cone-beam datasets typically relies on dividing batches of images into different nodes. This simple input decomposition, however, introduces limits on input/output sizes and scalability.We propose a novel decomposition scheme and reconstruction algorithm for distributed FPB. This scheme enables arbitrarily large input/output sizes, eliminates the redundancy arising in the end-to-end pipeline and improves the scalability by replacing two communication collectives with only one segmented reduction. Finally, we implement the proposed decomposition scheme in a framework that is useful for all current-generation CT devices (7th gen). In our experiments using up to 1024 GPUs, our framework can construct 40963 volumes, for real-world datasets, in under 16 seconds (including I/O).

Chen, Peng↗
DOE OSTI2021

Identifying and tracking bubbles and drops in simulations: A toolbox for obtaining sizes, lineages, and breakup and coalescence statistics

Knowledge of bubble and drop size distributions in two-phase flows is important for characterizing a wide range of phenomena, including combustor ignition, sonar communication, and cloud formation. The physical mechanisms driving the background flow also drive the time evolution of these distributions. Accurate and robust identification and tracking algorithms for the dispersed phase are necessary to reliably measure this evolution and thereby quantify the underlying mechanisms in interface-resolving flow simulations. The identification of individual bubbles and drops traditionally relies on an algorithm used to identify connected regions. This traditional algorithm can be sensitive to the presence of spurious structures. A cost-effective refinement is proposed to maximize volume accuracy while minimizing the identification of spurious bubbles and drops. An accurate identification scheme is crucial for distinguishing bubble and drop pairs with large size ratios. The identified bubbles and drops need to be tracked in time to obtain breakup and coalescence statistics that characterize the evolution of the size distribution, including breakup and coalescence frequencies, and the probability distributions of parent and child bubble and drop sizes. An algorithm based on mass conservation is proposed to construct bubble and drop lineages using simulation snapshots that are not necessarily from consecutive time steps. These lineages are then used to detect breakup and coalescence events, and obtain the desired statistics. Accurate identification of large-size-ratio bubble and drop pairs enables accurate detection of breakup and coalescence events over a large size range. Accurate detection of successive breakup and coalescence events requires that the snapshot interval be an order of magnitude smaller than the characteristic breakup and coalescence times to capture these successive events while minimizing the identification of repeated confounding events. Together, these algorithms serve as a toolbox for detailed analysis of two-phase simulations, and enable insights into the mechanisms behind bubble and drop formation and evolution in flows of practical importance.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2012

Spreader-Bar Radiation Detection System Enhancements: A Modeling and Simulation Study

An investigation of radiation detectors on crane-mounted platforms was performed to understand the limitations and optimal capability of these types of systems. Crane-mounted systems are primarily focused on crane-mounted radiation detector systems, where the detectors are mounted on a spreader-bar platform. Spreader bars are attached with cables to a crane at seaports to load and unload containers from cargo ships. The bars can spread from 20 feet to 53 feet using hydraulics, allowing a single bar to move a variety of container lengths. Spreader-bars are also used on straddle carriers, which move containers around the laydown yard in the port. Spreader bar radiation detection (SBRD) systems are commercially available from at least two companies. These systems employ a set of spectroscopic sensors placed on the underside of a gantry crane and held near the top of a cargo container for detection. These systems have been previously tested and some issues and limitations observed. Radiation detectors mounted on spreader-bars are single sided systems (observing cargo only from the top) and it is therefore challenging to obtain the same sensitivity as double-sided systems (for example, portal monitors) especially when considering the possible amounts of intervening cargo that could be present. The approximately exponential attenuation of gamma rays in intervening dense cargo presents an inherent limitation to detection. However, SBRD systems hold detectors closer to the container, have a longer dwell time, and may have lower background (over the ship); all of these aspects help mitigate the single-sided issue. In addition, there are operational considerations that make spreader-bar radiation systems attractive. These include scanning for radiation during other operations (loading, unloading or container movement) which minimizes additional time for scanning, incorporating the radiation detection into existing equipment to minimize initial cost, and in the case of ship unloading, scanning the containers before reaching the laydown yard. This study is focused on researching optimized configurations of SBRD systems, including number of detectors, locations, and best use of detector data, to determine a reasonable limit on the capability of these types of systems. The results will help support decisions on where and how these systems might be effectively deployed, and could be used for future specification development for SBRD acquisition. The next phase of this research and investigation into SBRD systems and quantification of the possible improved capability with an enhanced SBRD is the focus of this report. Supporting this investigation, detailed models of an enhanced SBRD system were created using a 3D radiation transport code, and models were run to simulate the data from sources and background for a realistic cargo-loading port environment. The enhanced SBRD had increased detector material (numbers of detectors) compared to the commercial systems, with a distribution providing more uniform coverage. Measurements using small industrial sources were made with an enhanced SBRD system developed by Sandia National Laboratory to support model validation to establish credibility for the simulations of these threat and background scenarios. A significant simulation effort was undertaken to simulate sources of interest within a 40-foot cargo container. In order to estimate the performance of a generalized SBRD system in scenarios including background and cargo, a highly enriched uranium (HEU) test source (with 3x10 -8 232 U by weight) within a wood cargo model was simulated for a 40-foot cargo container. This source was placed at a variety of locations, and the flux from the source was multiplied as necessary to create estimated minimal detectable quantities (MDQ) figures for various quantities of HEU. Simulated data sets were produced corresponding to a complete container offloading scenario for a large number of statistical realizations. Significant work was performed on both the algorithm development and the container cargo distributions entering the US, and the result of this modeling, validation, and simulation effort was a set of estimates of the performance of a variety of radiation detection algorithms in this cargo-screening environment. In the case of algorithms, a variety of contemporary radiation detection and identification approaches were employed, and the optimal approaches to selecting time and location subsets of detector data were explored. In all cases, algorithm performance was compared, and the best approaches were suggested along with the best expected performance from the enhanced SBRD. In general, template-matching schemes employing a limited set of regression parameters tend to provide best results. The improvements of an enhanced SBRD with increased detector material and improved algorithms result in an effective MDQ of 10 kg of HEU in ~50 percent of the imported cargo in 40-foot containers, assuming a random source location. This is approximately two times the capability of the estimated performance of the commercial systems. For an MDQ of the 10 kg HEU source located in the worst location (bottom of the 40-foot container), the volume of cargo scanned drops to 10% for the enhanced SBRD, again a factor of two or more larger than the commercial systems. Enhancing the SBRD systems by adding more detectors, providing a more uniform coverage, and incorporating more advanced algorithms will result in a significant increase in capability. Although this investigation provided some indication of the performance capabilities of an enhanced SBRD system, additional work is needed to estimate the capability for other container configurations, such as the 20 and 45 foot containers. Since the 20-foot container weight limit is similar to the 40-foot, more dense cargo is typically shipped in 20-foot containers. This will result in a smaller percentage of cargo scanned for the 20-foot containers (for a particular source quantity) compared to the 40-foot containers. In addition to other configuration, other source material needs to be investigated to understand the capabilities for the entire threat space, where only HEU is considered in this work.

crane-mounted↗
DOE OSTI2014

Stochastic simulation of electron avalanches on supercomputers

In the paper, we present a three-dimensional parallel Monte Carlo algorithm named ELSHOW which is developed for simulation of electron avalanches in gases. Parallel implementation of the ELSHOW was made on supercomputers with different architectures (massive parallel and hybrid ones). Using the ELSHOW, calculations of such integral characteristics as the number of particles in an avalanche, the coefficient of impact ionization, the drift velocity, and the others were made. Also, special precise computations were made to select an appropriate size of the time step using the technique of dependent statistical tests. Particularly, the algorithm consists of special methods of distribution modeling, a lexicographic implementation scheme for “branching” of trajectories, justified estimation of functionals. A comparison of the obtained results for nitrogen with previously published theoretical and experimental data was made.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

HIGH-RESOLUTION LINEAR POLARIMETRIC IMAGING FOR THE EVENT HORIZON TELESCOPE

Images of the linear polarizations of synchrotron radiation around active galactic nuclei (AGNs) highlight their projected magnetic field lines and provide key data for understanding the physics of accretion and outflow from supermassive black holes. The highest-resolution polarimetric images of AGNs are produced with Very Long Baseline Interferometry (VLBI). Because VLBI incompletely samples the Fourier transform of the source image, any image reconstruction that fills in unmeasured spatial frequencies will not be unique and reconstruction algorithms are required. In this paper, we explore some extensions of the Maximum Entropy Method (MEM) to linear polarimetric VLBI imaging. In contrast to previous work, our polarimetric MEM algorithm combines a Stokes I imager that only uses bispectrum measurements that are immune to atmospheric phase corruption, with a joint Stokes Q and U imager that operates on robust polarimetric ratios. We demonstrate the effectiveness of our technique on 7 and 3 mm wavelength quasar observations from the VLBA and simulated 1.3 mm Event Horizon Telescope observations of Sgr A* and M87. Consistent with past studies, we find that polarimetric MEM can produce superior resolution compared to the standard CLEAN algorithm, when imaging smooth and compact source distributions. As an imaging framework, MEM is highly adaptable, allowing a range of constraints on polarization structure. Polarimetric MEM is thus an attractive choice for image reconstruction with the EHT.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Differentially Private K -Means Clustering Applied to Meter Data Analysis and Synthesis

The proliferation of smart meters has resulted in a large amount of data being generated. It is increasingly apparent that methods are required for allowing a variety of stakeholders to leverage the data in a manner that preserves the privacy of the consumers. The sector is scrambling to define policies, such as the so called ‘15/15 rule’, to respond to the need. However, the current policies fail to adequately guarantee privacy. Here, in this paper, we address the problem of allowing third parties to apply K-means clustering, obtaining customer labels and centroids for a set of load time series by applying the framework of differential privacy. We leverage the method to design an algorithm that generates differentially private synthetic load data consistent with the labeled data. We test our algorithm’s utility by answering summary statistics such as average daily load profiles for a 2-dimensional synthetic dataset and a real-world power load dataset.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Robust Reconfiguration of A Distribution System

In this paper, a robust reconfiguration approach based on Mixed Integer Programming (MIP) is proposed to minimize loss in distribution systems. A Depth-First Search (DFS) algorithm to enumerate possible loops provides radiality constraint. This provides a general solution to the radiality constraint for distribution system reconfiguration/expansion problems. Still, imprecision and ambiguity in net loads, i.e. load minus renewable generation, due to lack of sufficient measurements and high utilization of demand response programs and renewable resources, creates challenges for effective reconfiguration. Deterministic optimization of reconfiguration may no lead to optimal/feasible results. Two methods to address these uncertainties are introduced in this paper: one, based on a stochastic MIP (SMIP) formulation and two, based on a fuzzy MIP (FMIP) formulation. Case studies demonstrate the robustness and efficiency of the proposed reconfiguration methods.

Depth-First Search (DFS)↗
DOE OSTI2014

SU-E-T-51: Bayesian Network Models for Radiotherapy Error Detection

Purpose: To develop a probabilistic model of radiotherapy plans using Bayesian networks that will detect potential errors in radiation delivery. Methods: Semi-structured interviews with medical physicists and other domain experts were employed to generate a set of layered nodes and arcs forming a Bayesian Network (BN) which encapsulates relevant radiotherapy concepts and their associated interdependencies. Concepts in the final network were limited to those whose parameters are represented in the institutional database at a level significant enough to develop mathematical distributions. The concept-relation knowledge base was constructed using the Web Ontology Language (OWL) and translated into Hugin Expert Bayes Network files via the the RHugin package in the R statistical programming language. A subset of de-identified data derived from a Mosaiq relational database representing 1937 unique prescription cases was processed and pre-screened for errors and then used by the Hugin implementation of the Estimation-Maximization (EM) algorithm for machine learning all parameter distributions. Individual networks were generated for each of several commonly treated anatomic regions identified by ICD-9 neoplasm categories including lung, brain, lymphoma, and female breast. Results: The resulting Bayesian networks represent a large part of the probabilistic knowledge inherent in treatment planning. By populating the networks entirely with data captured from a clinical oncology information management system over the course of several years of normal practice, we were able to create accurate probability tables with no additional time spent by experts or clinicians. These probabilistic descriptions of the treatment planning allow one to check if a treatment plan is within the normal scope of practice, given some initial set of clinical evidence and thereby detect for potential outliers to be flagged for further investigation. Conclusion: The networks developed here support the use of probabilistic models into clinical chart checking for improved detection of potential errors in RT plans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-428: An Optimization-Based Commissioning Tool for Finite Size Pencil Beam Dose Calculations

Purpose: Finite size pencil beam (FSPB) algorithms are commonly used to pre-calculate the beamlet dose distribution for IMRT treatment planning. FSPB commissioning, which usually requires fine tuning of the FSPB kernel parameters, is crucial to the dose calculation accuracy and hence the plan quality. Yet due to the large number of beamlets, FSPB commissioning could be very tedious. This abstract reports an optimization-based FSPB commissioning tool we have developed in MatLab to facilitate the commissioning. Methods: A FSPB dose kernel generally contains two types of parameters: the profile parameters determining the dose kernel shape, and a 2D scaling factors accounting for the longitudinal and off-axis corrections. The former were fitted using the penumbra of a reference broad beam’s dose profile with Levenberg-Marquardt algorithm. Since the dose distribution of a broad beam is simply a linear superposition of the dose kernel of each beamlet calculated with the fitted profile parameters and scaled using the scaling factors, these factors could be determined by solving an optimization problem which minimizes the discrepancies between the calculated dose of broad beams and the reference dose. Results: We have commissioned a FSPB algorithm for three linac photon beams (6MV, 15MV and 6MVFFF). Dose of four field sizes (6*6cm2, 10*10cm2, 15*15cm2 and 20*20cm2) were calculated and compared with the reference dose exported from Eclipse TPS system. For depth dose curves, the differences are less than 1% of maximum dose after maximum dose depth for most cases. For lateral dose profiles, the differences are less than 2% of central dose at inner-beam regions. The differences of the output factors are within 1% for all the three beams. Conclusion: We have developed an optimization-based commissioning tool for FSPB algorithms to facilitate the commissioning, providing sufficient accuracy of beamlet dose calculation for IMRT optimization.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2019

Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids

Power distribution grids are structurally operated radially, such that energized lines form a collection of trees with a substation at the root of each tree. The operational topology may change from time to time, however tracking these changes, even though important for the distribution grid operation and control, is hindered by limited real-time monitoring. This work develops a learning framework to reconstruct the radial operational structure of the distribution grid from synchronized voltage measurements. To detect operational lines our learning algorithm uses conditional independence tests for continuous random variables that is applicable to a wide class of probability distributions and Gaussian injections in particular. Furthermore, our algorithm applies to the practical case of unbalanced three-phase power flow. The performance is validated on AC power flow simulations over three phase IEEE distribution grid test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Enabling Efficient Sparse Computations using Linear Algebra Aware Compilers

This project developed the LAPIS compiler framework, built on the Multilevel Intermediate Representation (MLIR), to optimize sparse linear algebra operations and support performance portability across diverse architectures. The main innovation of LAPIS is the Kokkos dialect, which allows for lowering codes from a high productivity language to different architectures in an elegant way. The dialect also allows the conversion of lower-level MLIR code to C++ Kokkos code, facilitating the integration of scientific machine learning (SciML) models into applications. To extend LAPIS for distributed memory architectures, a new partition dialect was created to manage the distribution of sparse tensors and express communication patterns for sparse linear algebra operations. This dialect also supports the distributed execution of operators and includes algorithmic optimizations to minimize communication to improve performance. The project also demonstrates that MLIR can enable effective linear algebra-level optimizations, improving performance on different GPUs for both sparse and dense linear algebra kernels. Key applications of LAPIS include sparse linear algebra and graph kernels, TenSQL, a relational database management solution built on GraphBLAS, and the development of subgraph isomorphism and monomorphism kernels, showcasing performance portability. In summary, the LAPIS framework supports productivity, performance, portability, and distributed memory execution, while also enabling linear algebra-level optimizations that are challenging in traditional programming languages, with successful applications ranging from simple sparse linear algebra to complex graph kernels.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Oxygen distribution in tumors: A qualitative analysis and modeling study providing a novel Monte Carlo approach

Purpose: To construct a Monte Carlo (MC)-based simulation model for analyzing the dependence of tumor oxygen distribution on different variables related to tumor vasculature [blood velocity, vessel-to-vessel proximity (vessel proximity), and inflowing oxygen partial pressure (pO{sub 2})]. Methods: A voxel-based tissue model containing parallel capillaries with square cross-sections (sides of 10 μm) was constructed. Green's function was used for diffusion calculations and Michaelis-Menten's kinetics to manage oxygen consumption. The model was tuned to approximately reproduce the oxygenational status of a renal carcinoma; the depth oxygenation curves (DOC) were fitted with an analytical expression to facilitate rapid MC simulations of tumor oxygen distribution. DOCs were simulated with three variables at three settings each (blood velocity, vessel proximity, and inflowing pO{sub 2}), which resulted in 27 combinations of conditions. To create a model that simulated variable oxygen distributions, the oxygen tension at a specific point was randomly sampled with trilinear interpolation in the dataset from the first simulation. Six correlations between blood velocity, vessel proximity, and inflowing pO{sub 2} were hypothesized. Variable models with correlated parameters were compared to each other and to a nonvariable, DOC-based model to evaluate the differences in simulated oxygen distributions and tumor radiosensitivities for different tumor sizes. Results: For tumors with radii ranging from 5 to 30 mm, the nonvariable DOC model tended to generate normal or log-normal oxygen distributions, with a cut-off at zero. The pO{sub 2} distributions simulated with the six-variable DOC models were quite different from the distributions generated with the nonvariable DOC model; in the former case the variable models simulated oxygen distributions that were more similar to in vivo results found in the literature. For larger tumors, the oxygen distributions became truncated in the lower end, due to anoxia, but smaller tumors showed undisturbed oxygen distributions. The six different models with correlated parameters generated three classes of oxygen distributions. The first was a hypothetical, negative covariance between vessel proximity and pO{sub 2} (VPO-C scenario); the second was a hypothetical positive covariance between vessel proximity and pO{sub 2} (VPO+C scenario); and the third was the hypothesis of no correlation between vessel proximity and pO{sub 2} (UP scenario). The VPO-C scenario produced a distinctly different oxygen distribution than the two other scenarios. The shape of the VPO-C scenario was similar to that of the nonvariable DOC model, and the larger the tumor, the greater the similarity between the two models. For all simulations, the mean oxygen tension decreased and the hypoxic fraction increased with tumor size. The absorbed dose required for definitive tumor control was highest for the VPO+C scenario, followed by the UP and VPO-C scenarios. Conclusions: A novel MC algorithm was presented which simulated oxygen distributions and radiation response for various biological parameter values. The analysis showed that the VPO-C scenario generated a clearly different oxygen distribution from the VPO+C scenario; the former exhibited a lower hypoxic fraction and higher radiosensitivity. In future studies, this modeling approach might be valuable for qualitative analyses of factors that affect oxygen distribution as well as analyses of specific experimental and clinical situations.

60 APPLIED LIFE SCIENCES↗