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DOE OSTI2020

Simulation-driven optimization of high-order meshes in ALE hydrodynamics

Here we propose tools for high-order mesh optimization and demonstrate their benefits in the context of multi-material Arbitrary Lagrangian-Eulerian (ALE) compressible shock hydrodynamic applications. The mesh optimization process is driven by information provided by the simulation which uses the optimized mesh, such as shock positions, material regions, known error estimates, etc. These simulation features are usually represented discretely, for instance, as finite element functions on the Lagrangian mesh. The discrete nature of the input is critical for the practical applicability of the algorithms we propose and distinguishes this work from approaches that strictly require analytical information. Our methods are based on node movement through a high-order extension of the Target-Matrix Optimization Paradigm (TMOP). The proposed formulation is fully algebraic and relies only on local Jacobian matrices, so it is applicable to all types of mesh elements, in 2D and 3D, and any order of the mesh. We discuss the notions of constructing adaptive target matrices and obtaining their derivatives, reconstructing discrete data in intermediate meshes, node limiting that enables improvement of global mesh quality while preserving space-dependent local mesh features, and appropriate normalization of the objective function. The adaptivity methods are combined with automatic ALE triggers that can provide robustness of the mesh evolution and avoid excessive remap procedures. The benefits of the new high-order TMOP technology are illustrated on several simulations performed in the high-order ALE application BLAST.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2016

TH-E-209-01: Fluoroscopic Dose Monitoring and Patient Follow-Up Program at Massachusetts General Hospital

Radiation dose monitoring solutions have opened up new opportunities for medical physicists to be more involved in modern clinical radiology practices. In particular, with the help of comprehensive radiation dose data, data-driven protocol management and informed case follow up are now feasible. Significant challenges remain however and the problems faced by medical physicists are highly heterogeneous. Imaging systems from multiple vendors and a wide range of vintages co-exist in the same department and employ data communication protocols that are not fully standardized or implemented making harmonization complex. Many different solutions for radiation dose monitoring have been implemented by imaging facilities over the past few years. Such systems are based on commercial software, home-grown IT solutions, manual PACS data dumping, etc., and diverse pathways can be used to bring the data to impact clinical practice. The speakers will share their experiences with creating or tailoring radiation dose monitoring/management systems and procedures over the past few years, which vary significantly in design and scope. Topics to cover: (1) fluoroscopic dose monitoring and high radiation event handling from a large academic hospital; (2) dose monitoring and protocol optimization in pediatric radiology; and (3) development of a home-grown IT solution and dose data analysis framework. Learning Objectives: Describe the scope and range of radiation dose monitoring and protocol management in a modern radiology practice Review examples of data available from a variety of systems and how it managed and conveyed. Reflect on the role of the physicist in radiation dose awareness.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-E-209-02: Dose Monitoring and Protocol Optimization: The Pediatric Perspective

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-E-209-03: Development of An In-House CT Dose Monitoring and Management System Based On Open-Source Software Resources -- Pearls and Pitfalls

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Status of the SAS4A/SASSYS-1 Safety Analysis Code

SAS4A/SASSYS-1 is a simulation tool used to perform deterministic analysis of anticipated events as well as design basis and beyond design basis accidents for advanced reactors. This report summarizes the current status of SAS4A/SASSYS-1, including the implementation of software quality assurance procedures for configuration management, new licenses, current users, and a gap assessment of the test suite. The existing copyright has been extended for an additional five years, which was essential so that Argonne can continue developing, distributing, and supporting the software for both domestic use and international collaborations. SAS4A/SASSYS-1 Version 5.2 was completed in March 2017 and released to users in May. The importance of SAS4A/SASSYS-1 maintenance reflects its relevance to a number of U.S. Department of Energy programs as well as domestic and international collaborations. External collaborations have also produced improvements in the SAS4A/SASSYS-1 code, and these are noted in this report. SAS4A/SASSYS-1 has a growing user base that continues to strengthen the promotion of advanced non-LWR reactor concepts. Additional users will help solidify DOE’s leadership role in fast reactor safety both domestically and in international collaborations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

A Semi-Lagrangian Spectral Method for the Vlasov–Poisson System Based on Fourier, Legendre and Hermite Polynomials

In this study, we apply a semi-Lagrangian spectral method for the Vlasov–Poisson system, previously designed for periodic Fourier discretizations, by implementing Legendre polynomials and Hermite functions in the approximation of the distribution function with respect to the velocity variable. We discuss second-order accurate-in-time schemes, obtained by coupling spectral techniques in the space–velocity domain with a BDF time-stepping scheme. The resulting method possesses good conservation properties, which have been assessed by a series of numerical tests conducted on some standard benchmark problems including the two-stream instability and the Landau damping test cases. In the Hermite case, we also investigate the numerical behavior in dependence of a scaling parameter in the Gaussian weight. Confirming previous results from the literature, our experiments for different representative values of this parameter, indicate that a proper choice may significantly impact on accuracy, thus suggesting that suitable strategies should be developed to automatically update the parameter during the time-advancing procedure.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Gaussian process-based surrogate modeling framework for process planning in laser powder-bed fusion additive manufacturing of 316L stainless steel

Here, Laser Powder-Bed Fusion (L-PBF) metal-based additive manufacturing (AM) is complex and not fully understood. Successful processing for one material, might not necessarily apply to a different material. This paper describes a workflow process that aims at creating a material data sheet standard that describes regimes where the process can be expected to be robust. The procedure consists of building a Gaussian process-based surrogate model of the L-PBF process that predicts melt pool depth in single-track experiments given a laser power, scan speed, and laser beam size combination. The predictions are then mapped onto a power versus scan speed diagram delimiting the conduction from the keyhole melting controlled regimes. This statistical framework is shown to be robust even for cases where experimental training data might be suboptimal in quality, if appropriate physics-based filters are applied. Additionally, it is demonstrated that a high-fidelity simulation model of L-PBF can equally be successfully used for building a surrogate model, which is beneficial since simulations are getting more efficient and are more practical to study the response of different materials, than to re-tool an AM machine for new material powder.

316L stainless steel↗

DOE OSTI2013

Comparison of 3 different postimplant dosimetry methods following permanent {sup 125}I prostate seed brachytherapy

Postimplant dosimetry (PID) after Iodine-125 ({sup 125}I) implant of the prostate should offer a reliable qualitative assessment. So far, there is no consensus regarding the optimum PID method, though the latest literature is in favor of magnetic resonance imaging (MRI). This study aims to simultaneously compare 3 PID techniques: (1) MRI-computed tomography (CT) fusion; (2) ultrasound (US)-CT fusion; and (3) manual target delineation on CT. The study comprised 10 patients with prostate cancer. CT/MR scans with urinary catheters in place for PID were done either on day 0 or day 1 postimplantation. The main parameter evaluated and compared among methods was target D90. The results show that CT-based D90s are lower than US-CT D90s (median difference,−6.85%), whereas MR-CT PID gives higher D90 than US-CT PID (median difference, 4.25%). Manual contouring on CT images tends to overestimate the prostate volume compared with transrectal ultrasound (TRUS) (median difference, 23.33%), whereas on US images the target is overestimated compared with MR-based contouring (median difference, 13.25%). Although there are certain differences among the results given by various PID techniques, the differences are statistically insignificant for this small group of patients. Any dosimetric comparison between 2 PID techniques should also account for the limitations of each technique, to allow for an accurate quantification of data. Given that PID after permanent radioactive seed implant is mandatory for quality assurance, any imaging method–based PID (MR-CT, US-CT, and CT) available in a radiotherapy department can be indicative of the quality of the procedure.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2026

Illinois Storage Corridor, CarbonSAFE Phase III: UIC Class VI Permitting Plan

The Illinois Storage Corridor (ISC) project evaluated two distinct sites to determine the feasibility of commercial-scale CO₂ storage at each. The project leveraged the region's exceptional geological characteristics, particularly the well-characterized Cambro-Ordovician Storage Complex, to enable permanent geological storage of more than 50 million tonnes of CO₂ over 30 years. The two storage sites are located at One Earth Energy (OEE) facility in northcentral Illinois and Prairie State Generating Company (PSGC) in southcentral Illinois. Once operational, these facilities will combine to capture and store more than 6.5 million tonnes of CO₂ per year, positioning the ISC among the largest carbon storage regions globally. Preliminary homogeneous dynamic modeling based on regional and site-specific reservoir characteristics indicates promising injection capabilities at both locations. For the OEE site, modeling predicts a maximum allowable injection rate of 3.7 MTPA, with a baseline scenario of 1.7 MTPA over 30 years producing a CO₂ plume radius of 1.4 miles at end of injection. For the PSGC site, incorporating recent well data, modeling indicates a single-well maximum injection rate of 2.1 MTPA, with a plume radius of 4.2 miles at end of injection for the 60 MT over 30 years scenario. The primary objective of this CarbonSAFE Phase III project is to develop and submit Class VI Underground Injection Control (UIC) permit applications to the U.S. Environmental Protection Agency Region 5. The permitting plan outlines comprehensive site characterization, Area of Review delineation, monitoring programs, well construction designs, financial responsibility provisions, and post-injection site care procedures necessary to demonstrate safe, permanent CO₂ storage protective of underground sources of drinking water. Three UIC Class VI permit applications for the OEE site were submitted to EPA in October 2022 and are progressing through technical review, with final permit decision projected by June 2026. Through five rounds of Requests for Additional Information and responses, the applications have been refined to address computational modeling, area of review delineation, well integrity, monitoring protocols, and financial assurance requirements. For the PSGC site, finalized characterization and permitting documentation was delivered directly to the facility in July 2023 due to business constraints precluding formal federal regulatory submission. This comprehensive permitting effort builds upon extensive prior subsurface evaluations and demonstration projects that have confirmed the feasibility of widespread commercial-scale carbon storage in the region.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2012

Stochastic sampling method with MCNPX for nuclear data uncertainty propagation in criticality safety applications

In the domain of criticality safety, the efficient propagation of uncertainty in nuclear data to uncertainty in k{sub eff} is an important area of current research. In this paper, a method based on stochastic sampling is presented for uncertainty propagation in MCNPX calculations. To that aim, the nuclear data (i.e. cross sections) are assumed to have a multivariate normal distribution and simple random sampling is performed following this presumed probability distribution. A verification of the developed stochastic sampling procedure with MCNPX is then conducted using the {sup 239}Pu Jezebel experiment as well as the PB-2 BWR and TMI-1 PWR pin cell models from the Uncertainty Analysis in Modeling (UAM) exercises. For the Jezebel case, it is found that the developed stochastic sampling approach predicts similar k{sub eff} uncertainties compared to conventional sensitivity and uncertainty methods. For the UAM models, slightly lower uncertainties are obtained when comparing to existing preliminary results. Further details of these verification studies are discussed and directions for future work are outlined. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Hydrogen Leak Modeling for Development of Smart Distributed Monitoring Under Unintended Releases

Hydrogen is a versatile and clean energy carrier that can be produced from various renewable sources such as wind, solar, and hydropower. Hydrogen has the potential to play a crucial role in decarbonizing industrial processes that are currently reliant on fossil fuels and provide long-duration and/or seasonal energy storage to enable electricity decarbonization. Hydrogen can also be used as a fuel for fuel cell vehicles, providing a zero-emission alternative to traditional internal combustion engines. DOE launched the Hydrogen Energy Earthshot (Hydrogen Shot) in June 2021 to reduce the cost of clean hydrogen by 80% to $1 per 1 kilogram in 1 decade ("1 1 1"). While promising, Hydrogen is highly-flammable, and in the presence of oxygen, it can form explosive mixtures. . Therefore, understanding leak scenarios is essential to evaluate and mitigate the safety risks associated with potential hydrogen leaks. An increased understanding of leak behavior, and having tools to model leaks, can help assess how hydrogen would disperse in different environments, influencing emergency response plans and safety measures, and identify potential issues with materials and design systems that can withstand the challenges posed by hydrogen. Recently, researchers have attempted to study hydrogen leaks for development of risk management strategies. However, the focus has been on closed or semi-closed spaces like storage rooms, vehicles, garages, and fueling stations - all promising locations for future hydrogen infrastructure. In this presentation, the modeling environment extends the span of research further by modeling hydrogen leak in an outdoor, open space. We will present the key challenges with modeling hydrogen leaks in an uncontrollable environment, how they were handled, and how modeling results informed sensor selection and placement. A Hydrogen research facility at the National Renewable Energy Laboratory (NREL) was used as a case study to model hydrogen leaks. In the future, Hydrogen wide area detection methodologies will be developed and tested at this site to monitor for unintended and operational hydrogen releases. The data generated from modeling will be used to develop a predictive model to detect hydrogen leak location based on concentration measured by sensors in this open space. Furthermore, the facility was also chosen because controlled hydrogen releases can be performed. A computational fluid dynamics (CFD) based modeling approach was taken to model hydrogen leak. The full-scale hydrogen facility was modeled with a large ambient domain. The electrolyzer at the facility can produce a controlled release rate of 27 kg-H2/hr. Site-specific atmospheric and weather condition data such as wind direction, wind speed at various altitudes, and temperature were used as inputs to the model. To capture the variability of weather conditions, a subset of the weather conditions experienced during daytime hours without precipitation over the course of three months was generated; using established data clustering techniques, a total of 100 condition sets were chosen. The results show statistical distributions and ranges of hydrogen concentrations at locations throughout the domain. These distributions are compared to experimental data from a constant mass flow, controlled hydrogen release at the facility. The stochastic wind conditions of the release make direct validation difficult, therefore, statistical comparison approaches were used. Wind conditions are found to significantly impact the release behavior, including direction and concentration. Sensor selection and placement is proposed for the facility and is now based on release behavior predicted for the facility given its weather patterns; this is much more informed than without the modeling results. The methodology and analysis procedure can be translated to other facilities using modified geometries and site-specific weather conditions. Hydrogen holds great promise as a renewable energy fuel, but ensuring safety in its production, storage, and use is paramount. Studying potential leak scenarios in an open space will help develop sensors to detect hydrogen on a large spectrum of concentration and eventually build a smart distributed monitoring system.

CFD↗

DOE OSTI2022

The use of subchondral bone topography to approximate the center of rotation of the elbow joint in dogs

Abstract Objectives The aim of this study was to compare the approximate center of rotation in normal and diseased elbows in dogs. Study design Cross‐sectional study Sample population Computer tomography scans of nine dogs with unilateral fragmented medial coronoid process (FMCP). Methods A board certified radiologist confirmed that each dog had unilateral FMCP, and a normal contralateral elbow. Digital 3D models of all elbow joints were uploaded into a surgical planning software package. Four axes approximating the center of rotation (COR) of elbow joints were generated using five geometric shapes based on subchondral topography of the humeral condyle radius and ulna. Images showing the locations where axes exited the medial and lateral cortex of the humeral condyle were captured and imported into a second software package, for measurement of distances between exit points and the origin of a system of axes. Results In normal joints 20/27 (74%) axes exited the medial cortex, and 25/27 (93%) axes exited the lateral cortex cranial and distal to the medial and lateral epicondyles, respectively. In diseased joints 22/27 (81%) axes exited medial cortex and 19/27 (70%) axes exited the lateral cortex, caudal and distal to the medial and lateral epicondyles, respectively. Conclusion Based on CT‐ derived geometry, the COR of elbow affected with FMCP was generally more caudal than normal. Clinical significance External landmarks approximating the location of the elbow COR are provided, and while not validated, may assist in planning, creation, and assessment of procedures for FMCP.

Berger, Chen↗

DOE OSTI2015

SU-C-304-04: A Compact Modular Computational Platform for Automated On-Board Imager Quality Assurance

Purpose: Traditionally, the assessment of X-ray tube output and detector positioning accuracy of on-board imagers (OBI) has been performed manually and subjectively with rulers and dosimeters, and typically takes hours to complete. In this study, we have designed a compact modular computational platform to automatically analyze OBI images acquired with in-house designed phantoms as an efficient and robust surrogate. Methods: The platform was developed as an integrated and automated image analysis-based platform using MATLAB for easy modification and maintenance. Given a set of images acquired with the in-house designed phantoms, the X-ray output accuracy was examined via cross-validation of the uniqueness and integration minimization of important image quality assessment metrics, while machine geometric and positioning accuracy were validated by utilizing pattern-recognition based image analysis techniques. Results: The platform input was a set of images of an in-house designed phantom. The total processing time is about 1–2 minutes. Based on the data acquired from three Varian Truebeam machines over the course of 3 months, the designed test validation strategy achieved higher accuracy than traditional methods. The kVp output accuracy can be verified within +/−2 kVp, the exposure accuracy within 2%, and exposure linearity with a coefficient of variation (CV) of 0.1. Sub-millimeter position accuracy was achieved for the lateral and longitudinal positioning tests, while vertical positioning accuracy within +/−2 mm was achieved. Conclusion: This new platform delivers to the radiotherapy field an automated, efficient, and stable image analysis-based procedure, for the first time, acting as a surrogate for traditional tests for LINAC OBI systems. It has great potential to facilitate OBI quality assurance (QA) with the assistance of advanced image processing techniques. In addition, it provides flexible integration of additional tests for expediting other OBI quality assurance tests, such as 2D/3D image quality, making completely automated QA possible. Research Funding from Varian Medical Systems Inc. . Dr. Sasa Mutic receives compensation for providing patient safety training services from Varian Medical Systems, the sponsor of this study.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2014

DISCRETE ELEMENT MODELING OF BLADE–STRIKE FREQUENCY AND SURVIVAL OF FISH PASSING THROUGH HYDROKINETIC TURBINES

Evaluating the consequences from blade-strike of fish on marine hydrokinetic (MHK) turbine blades is essential for incorporating environmental objectives into the integral optimization of machine performance. For instance, experience with conventional hydroelectric turbines has shown that innovative shaping of the blade and other machine components can lead to improved designs that generate more power without increased impacts to fish and other aquatic life. In this work, we used unsteady computational fluid dynamics (CFD) simulations of turbine flow and discrete element modeling (DEM) of particle motion to estimate the frequency and severity of collisions between a horizontal axis MHK tidal energy device and drifting aquatic organisms or debris. Two metrics are determined with the method: the strike frequency and survival rate estimate. To illustrate the procedure step-by-step, an exemplary case of a simple runner model was run and compared against a probabilistic model widely used for strike frequency evaluation. The results for the exemplary case showed a strong correlation between the two approaches. In the application case of the MHK turbine flow, turbulent flow was modeled using detached eddy simulation (DES) in conjunction with a full moving rotor at full scale. The CFD simulated power and thrust were satisfactorily comparable to experimental results conducted in a water tunnel on a reduced scaled (1:8.7) version of the turbine design. A cloud of DEM particles was injected into the domain to simulate fish or debris that were entrained into the turbine flow. The strike frequency was the ratio of the count of colliding particles to the crossing sample size. The fish length and approaching velocity were test conditions in the simulations of the MHK turbine. Comparisons showed that DEM-based frequencies tend to be greater than previous results from Lagrangian particles and probabilistic models, mostly because the DEM scheme accounts for both the geometric aspects of the passage event ---which the probabilistic method does--- as well as the fluid-particle interactions ---which the Lagrangian particle method does. The DEM-based survival rates were comparable to laboratory results for small fish but not for mid-size fish because of the considerably different turbine diameters. The modeling framework can be used for applications that aim at evaluating the biological performance of MHK turbine units during the design phase and to provide information to regulatory agencies needed for the environmental permitting process.

blade strike↗

DOE OSTI2024

Elliptically-Contoured Tensor-variate Distributions with Application to Image Learning

Statistical analysis of tensor-valued data has largely used the tensor-variate normal (TVN) distribution that may be inadequate for data arising from distributions with heavier or lighter tails. We study a general family of elliptically contoured (EC) TV distributions and derive its characterizations, moments, marginal, and conditional distributions. We describe procedures for maximum likelihood estimation from data that are (1) uncorrelated draws from an EC distribution, (2) from a scale mixture of the TVN distribution, and (3) from an underlying but unknown EC distribution, for which we extend Tyler’s robust estimator. A detailed simulation study highlights the benefits of choosing an EC distribution over the TVN for heavier-tailed data. We develop TV classification rules using discriminant analysis and EC errors and show that they better predict cats and dogs from images in the Animal Faces-HQ dataset than the TVN-based rules. A novel tensor-on-tensor regression and TV analysis of variance (TANOVA) framework under EC errors is also demonstrated to better characterize gender, age, and ethnic origin than the usual TVN-based TANOVA in the celebrated labeled faces of the wild dataset.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2013

Preliminary Examination of Ethanol Fuel Effects on EPA’s R-factor for Vehicle Fuel Economy

The U.S. Department of Energy (DOE) supported a test program from 2007 through 2012 to evaluate the potential impacts of intermediate ethanol blends (also known as mid-level blends) on legacy vehicles and other engines. The purpose of the program was to assess the viability of using intermediate ethanol blends as a contributor to meeting national goals for the use of renewable fuels. Appendix A lists a bibliography of related studies. The catalyst durability program involved aging and emissions testing vehicles on a range of ethanol blends. The study was completed in 2011 and a final report issued shortly after. This report describes a preliminary analysis of the fuel economy data from the catalyst durability study, to determine the proper value for the R factor which is called out in the Code of Federal Regulations (CFR) for computing vehicle fuel economy on the certification cycle. The fuel economy equation that is specified in CFR for gasoline-fuelled vehicles is based on a carbon mass balance (CMB) approach to determine the amount of fuel consumed during the test by measuring the carbon-bearing emissions that are produced; however, it also incorporates a scaling factor (R factor) based on the net heating value of the fuel and the sensitivity of fuel economy to changes in the heating value. The impact of the R factor is a fixed ratio in the resultant fuel economy that is dependent upon fuel properties other than those required for a typical CMB calculation. This equation was put in place in 1988 to correct for differences between certification fuels to address corporate average fuel economy (CAFE) credit issues associated with fuel property variations. The algorithm adjusts the calculated fuel economy to compute what would have been measured had the 1975 certification fuel been used for the test. The R factor was defined as the sensitivity of the fuel economy result to changes in fuel energy content. When R equals 1.0, the fuel economy change exactly tracks the energy density difference between the fuels. If R is less than 1.0, the fuel economy change is smaller than the change in energy density. The R factor was defined to be 0.6 based on tests using 1980s vehicles. Since that time, the Auto/Oil test program has established that the R factor for 1990s vehicles is higher (about 0.93). More recently EPA analyzed the EPAct/V2/E-89 dataset to compute the R factor, resulting in an average of 0.82 to 0.86. It is important to note that the EPAct/V2/E89 test program used the LA92 test cycle, a cycle known to contain more aggressive accelerations than the FTP. To date, EPA has only required emissions and fuel economy testing of gasoline vehicles with a certification fuel that does not contain ethanol. However in 2013 EPA issued a Proposed Rule seeking comment on the establishment of an emissions certification fuel containing ethanol, such as E10 or E15. Calculating modern vehicle fuel economy with the existing CFR equation with an R factor of 0.6 when ethanol blends are used produces significant errors. For the catalyst durability program, a straightforward CMB approach was used to compute fuel economy, thereby allowing a straightforward evaluation of the impact of ethanol content on fuel economy. However, if an ethanol-containing fuel is to become the new certification fuel for light-duty vehicles, consistent application of the CFR equation needs to be considered for the benefit of manufacturers’ CAFE compliance. Analysis of city cycle Federal Test Procedure (FTP) fuel economy test results and fuel analyses from the catalyst durability study indicates that the average R-factor for modern vehicles is very close to unity at about 0.94±0.04. This result is very similar to the results of the 1993 Auto/Oil test program. Future work should examine other drive cycles, and advanced vehicle technologies which may reveal sensitivities to properties other than heating value.

intermediate ethanol blends↗

DOE OSTI2015

SU-E-T-421: Failure Mode and Effects Analysis (FMEA) of Xoft Electronic Brachytherapy for the Treatment of Superficial Skin Cancers

Purpose: To perform a failure mode and effects analysis (FMEA) of the process for treating superficial skin cancers with the Xoft Axxent electronic brachytherapy (eBx) system, given the recent introduction of expanded quality control (QC) initiatives at our institution. Methods: A process map was developed listing all steps in superficial treatments with Xoft eBx, from the initial patient consult to the completion of the treatment course. The process map guided the FMEA to identify the failure modes for each step in the treatment workflow and assign Risk Priority Numbers (RPN), calculated as the product of the failure mode’s probability of occurrence (O), severity (S) and lack of detectability (D). FMEA was done with and without the inclusion of recent QC initiatives such as increased staffing, physics oversight, standardized source calibration, treatment planning and documentation. The failure modes with the highest RPNs were identified and contrasted before and after introduction of the QC initiatives. Results: Based on the FMEA, the failure modes with the highest RPN were related to source calibration, treatment planning, and patient setup/treatment delivery (Fig. 1). The introduction of additional physics oversight, standardized planning and safety initiatives such as checklists and time-outs reduced the RPNs of these failure modes. High-risk failure modes that could be mitigated with improved hardware and software interlocks were identified. Conclusion: The FMEA analysis identified the steps in the treatment process presenting the highest risk. The introduction of enhanced QC initiatives mitigated the risk of some of these failure modes by decreasing their probability of occurrence and increasing their detectability. This analysis demonstrates the importance of well-designed QC policies, procedures and oversight in a Xoft eBx programme for treatment of superficial skin cancers. Unresolved high risk failure modes highlight the need for non-procedural quality initiatives such as improved planning software and more robust hardware interlock systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

An optimal FFT-based anisotropic power spectrum estimator

Measurements of line-of-sight dependent clustering via the galaxy power spectrum's multipole moments constitute a powerful tool for testing theoretical models in large-scale structure. Recent work shows that this measurement, including a moving line-of-sight, can be accelerated using Fast Fourier Transforms (FFTs) by decomposing the Legendre polynomials into products of Cartesian vectors. Here, we present a faster, optimal means of using FFTs for this measurement. We avoid redundancy present in the Cartesian decomposition by using a spherical harmonic decomposition of the Legendre polynomials. With this method, a given multipole of order ℓ requires only 2ℓ+1 FFTs rather than the (ℓ+1)(ℓ+2)/2 FFTs of the Cartesian approach. For the hexadecapole (ℓ = 4), this translates to 40% fewer FFTs, with increased savings for higher ℓ. The reduction in wall-clock time enables the calculation of finely-binned wedges in P ( k ,μ), obtained by computing multipoles up to a large ℓ{sub max} and combining them. This transformation has a number of advantages. We demonstrate that by using non-uniform bins in μ, we can isolate plane-of-sky (angular) systematics to a narrow bin at 0μ ≅ while eliminating the contamination from all other bins. We also show that the covariance matrix of clustering wedges binned uniformly in μ becomes ill-conditioned when combining multipoles up to large values of ℓ{sub max}, but that the problem can be avoided with non-uniform binning. As an example, we present results using ℓ{sub max}=16, for which our procedure requires a factor of 3.4 fewer FFTs than the Cartesian method, while removing the first μ bin leads only to a 7% increase in statistical error on f σ{sub 8}, as compared to a 54% increase with ℓ{sub max}=4.

79 ASTRONOMY AND ASTROPHYSICS↗