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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Short-Term Solar Forecasting Platform Using a Physics-Based Smart Persistence Model and Data Imputation Method

Electrical energy plays vital role in our socio-economic activity and therefore ensuring the reliability of the electric grid, from the generation, transmission and distribution level is critical. In order to maintain the power system parameter viz., frequency, voltage, etc., optimally, balancing of generation and consumption is very much essential. However, solar energy is infirm power by nature this is due to cloud cover / other local phenomena. Hence, Photovoltaic (PV) power generation brings a significant challenge to the grid operator due to the variability of the solar energy. The complexity of this challenge in terms of planning and dispatch ability of PV resources, aggravates with the high penetration of solar energy into the electric grid. In this setting, reliable solar radiation forecasting models based on accurate and quality input data become essential. In order to develop a suitable model for predicting solar radiation, quality historical / real time measurement is also needed. Under this study NIWE and NREL jointly developed / tested short-term solar forecasting frameworks using a smart persistence and physics-based smart persistence models for intra-hour forecasting of solar radiation (PSPI) and benchmarked 9 different data imputation techniques in 15 Solar Radiation Resource Assessment (SRRA) stations, located at different parts of India. During any measurement campaign, due to various technical reasons, we may miss few observations. However, the missing observation often reduce the performance of any forecasting model. Therefore, suitable data imputation method would assist us to obtain continuous observation of solar radiation. A station-by-station and method-by-method analysis was carried out to understand the performance of each model. Based on our analysis, among all the data imputation methods, the Kalman data imputation method is better for Indian Weather condition. In addition, Kalman StructTS, Linear, Stine and Arima methods yield slightly inferior accuracy compared to Kalman, but outperform the other methods. The extended solar radiation data are used by solar forecasting models to provide the prediction of solar radiation at 15 SRRA stations. As far as short term forecasting model is concerned, the PSPI model outperforms the Smart Persistence model. However, the forecast error is increases with the forecasting horizon.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRSDate not supplied

The Use of the BSRN Data as A Benchmark for the POWER Hourly DHI and DNI and In Validating Derived Hourly GTI

The satellite-based CERES SYN1deg hourly data is the source data of the POWER GIS solar data that covers 2001 to near present. The SYN1deg(Ed4.1) hourly GHI agrees well with the BSRN data, but the hourly DHI and DirHI (Direct Horizontal Irradiance) are positively and negatively, respectively, biased with appreciable magnitudes. The hourly DNI, derived by dividing the DirHI by cos(SZA), or the cosine of the solar zenith angle, is therefore negatively biased. Based on the statistics of comparisons with the BSRN data, we performed bias corrections on the hourly DHI and DNI. The corrections were executed in the 3-D phase space of latitude, cos(SZA), and cloud fraction (CLFR). The isotropic model is then used to derive the hourly global tilted irradiance (GTI). For validation purpose, we applied the isotropic model to the BSRN data at the original 1-, 2-, 3- or 5-minute interval. The satellite-based hourly GTI shows good agreement with their BSRN counterpart. We also examined two monthly-mean-based methods that empirically derive monthly mean GTI and DNI from monthly mean GHI and from both monthly mean GHI and DHI. The monthly-mean-based results compare favorably with the hourly-mean-based results. The GEWEX SRB (V4-IP) provides POWER with daily mean GHI for the years before the CERES era, and the data were corrected using quantile mapping by referencing the CERES SYN1deg data. We used the Kolmogorov -Smirnov test (K-S test) and Cramer-von Mises test to examine how well the results agree with the BSRN data. We found that if we set the lower limit for the daily mean GHI to 30 W m-2, the data can pass the K-S test at 0.01 significance level and the Cramer-von Mises test at 0.001 significance level. If no lower limit is set on the daily means, the data fail both tests. The satellite-based CERES SYN1deg hourly data is the source data of the POWER GIS solar data that covers 2001 to near present. The SYN1deg(Ed4.1) hourly GHI agrees well with the BSRN data, but the hourly DHI and DirHI (Direct Horizontal Irradiance) are positively and negatively, respectively, biased with appreciable magnitudes. The hourly DNI, derived by dividing the DirHI by cos(SZA), or the cosine of the solar zenith angle, is therefore negatively biased. Based on the statistics of comparisons with the BSRN data, we performed bias corrections on the hourly DHI and DNI. The corrections were executed in the 3-D phase space of latitude, cos(SZA), and cloud fraction (CLFR). The isotropic model is then used to derive the hourly global tilted irradiance (GTI). For validation purpose, we applied the isotropic model to the BSRN data at the original 1-, 2-, 3- or 5-minute interval. The satellite-based hourly GTI shows good agreement with their BSRN counterpart. We also examined two monthly-mean-based methods that empirically derive monthly mean GTI and DNI from monthly mean GHI and from both monthly mean GHI and DHI. The monthly-mean-based results compare favorably with the hourly-mean-based results. The GEWEX SRB (V4-IP) provides POWER with daily mean GHI for the years before the CERES era, and the data were corrected using quantile mapping by referencing the CERES SYN1deg data. We used the Kolmogorov -Smirnov test (K-S test) and Cramer-von Mises test to examine how well the results agree with the BSRN data. We found that if we set the lower limit for the daily mean GHI to 30 W m-2, the data can pass the K-S test at 0.01 significance level and the Cramer-von Mises test at 0.001 significance level. If no lower limit is set on the daily means, the data fail both tests.

Taiping Zhang↗
DOE OSTI2015

SU-E-J-114: A Practical Hybrid Method for Improving the Quality of CT-CBCT Deformable Image Registration for Head and Neck Radiotherapy

Purpose: Accurate deformable image registration (DIR) between CT and CBCT in H&N is challenging. In this study, we propose a practical hybrid method that uses not only the pixel intensities but also organ physical properties, structure volume of interest (VOI), and interactive local registrations. Methods: Five oropharyngeal cancer patients were selected retrospectively. For each patient, the planning CT was registered to the last fraction CBCT, where the anatomy difference was largest. A three step registration strategy was tested; Step1) DIR using pixel intensity only, Step2) DIR with additional use of structure VOI and rigidity penalty, and Step3) interactive local correction. For Step1, a public-domain open-source DIR algorithm was used (cubic B-spline, mutual information, steepest gradient optimization, and 4-level multi-resolution). For Step2, rigidity penalty was applied on bony anatomies and brain, and a structure VOI was used to handle the body truncation such as the shoulder cut-off on CBCT. Finally, in Step3, the registrations were reviewed on our in-house developed software and the erroneous areas were corrected via a local registration using level-set motion algorithm. Results: After Step1, there were considerable amount of registration errors in soft tissues and unrealistic stretching in the posterior to the neck and near the shoulder due to body truncation. The brain was also found deformed to a measurable extent near the superior border of CBCT. Such errors could be effectively removed by using a structure VOI and rigidity penalty. The rest of the local soft tissue error could be corrected using the interactive software tool. The estimated interactive correction time was approximately 5 minutes. Conclusion: The DIR using only the image pixel intensity was vulnerable to noise and body truncation. A corrective action was inevitable to achieve good quality of registrations. We found the proposed three-step hybrid method efficient and practical for CT/CBCT registrations in H&N. My department receives grant support from Industrial partners: (a) Varian Medical Systems, Palo Alto, CA, and (b) Philips HealthCare, Best, Netherlands.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2012

Equivalent Source Method Applied to Launch Acoustic Simulations

Aeroacoustic simulations of the launch environment are described. A hybrid computational fluid dynamics (CFD)/computational aeroacoustic (CAA) approach is developed in order to accurately and efficiently predict the sound pressure level spectrum on the launch vehicle and surrounding structures. The high-fidelity CFD code LAVA (Launch Ascent and Vehicle Analysis), is used to generate pressure time history at select locations in the flow field. A 3D exterior Helmholtz solver is then used to iteratively determine a set of monopole sources which mimic the noise generating mechanisms identified by the CFD solver. The acoustic pressure field generated from the Helmholtz solver is then used to evaluate the sound pressure levels.

Housman, Jeffrey A.↗
NASA NTRS2020

Aircraft Engine Run-To-Failure Data Set Under Real Flight Conditions

The generation of data-driven prognostics models requires the availability of datasets with run-to-failure trajectories. In order to contribute to the development of these methods, the dataset provides a new realistic dataset of run-to-failure trajectories for a small fleet of aircraft engines under realistic flight conditions. The damage propagation modelling used for the generation of this synthetic dataset builds on the modelling strategy from previous work [1] and incorporates two new levels of fidelity. First, it considers real flight conditions as recorded on board of a commercial jet [2]. Secondly, it extends the degradation modelling by relating the degradation process to the operation history. The dataset was generated with the Commercial Modular Aero-Propulsion System Simulation (C-MAPSS) dynamical model [3]. More details about the generation process can be found in [4].

CMAPSS↗
DOE OSTI2025

DOME: Directional medical embedding vectors from Electronic Health Records

Motivation: The increasing availability of Electronic Health Record (EHR) systems has created enormous potential for translational research. Recent developments in representation learning techniques have led to effective large-scale representations of EHR concepts along with knowledge graphs that empower downstream EHR studies. However, most existing methods require training with patient-level data, limiting their abilities to expand the training with multi-institutional EHR data. On the other hand, scalable approaches that only require summary-level data do not incorporate temporal dependencies between concepts. Methods: We introduce a DirectiOnal Medical Embedding (DOME) algorithm to encode temporally directional relationships between medical concepts, using summary-level EHR data. Specifically, DOME first aggregates patient-level EHR data into an asymmetric co-occurrence matrix. Then it computes two Positive Pointwise Mutual Information (PPMI) matrices to correspondingly encode the pairwise prior and posterior dependencies between medical concepts. Following that, a joint matrix factorization is performed on the two PPMI matrices, which results in three vectors for each concept: a semantic embedding and two directional context embeddings. They collectively provide a comprehensive depiction of the temporal relationship between EHR concepts. Results: We highlight the advantages and translational potential of DOME through three sets of validation studies. First, DOME consistently improves existing direction-agnostic embedding vectors for disease risk prediction in several diseases, for example achieving a relative gain of 5.5% in the area under the receiver operating characteristic (AUROC) for lung cancer. Second, DOME excels in directional drug-disease relationship inference by successfully differentiating between drug side effects and indications, correspondingly achieving relative AUROC gain over the state-of-the-art methods by 10.8% and 6.6%. Finally, DOME effectively constructs directional knowledge graphs, which distinguish disease risk factors from comorbidities, thereby revealing disease progression trajectories. The source codes are provided at https://github.com/celehs/Directional-EHRembedding.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Multivariate moment closure techniques for stochastic kinetic models

Stochastic effects dominate many chemical and biochemical processes. Their analysis, however, can be computationally prohibitively expensive and a range of approximation schemes have been proposed to lighten the computational burden. These, notably the increasingly popular linear noise approximation and the more general moment expansion methods, perform well for many dynamical regimes, especially linear systems. At higher levels of nonlinearity, it comes to an interplay between the nonlinearities and the stochastic dynamics, which is much harder to capture correctly by such approximations to the true stochastic processes. Moment-closure approaches promise to address this problem by capturing higher-order terms of the temporally evolving probability distribution. Here, we develop a set of multivariate moment-closures that allows us to describe the stochastic dynamics of nonlinear systems. Multivariate closure captures the way that correlations between different molecular species, induced by the reaction dynamics, interact with stochastic effects. We use multivariate Gaussian, gamma, and lognormal closure and illustrate their use in the context of two models that have proved challenging to the previous attempts at approximating stochastic dynamics: oscillations in p53 and Hes1. In addition, we consider a larger system, Erk-mediated mitogen-activated protein kinases signalling, where conventional stochastic simulation approaches incur unacceptably high computational costs.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

OzDES reverberation mapping program: Lag recovery reliability for 6-yr C iv analysis

ABSTRACT We present the statistical methods that have been developed to analyse the OzDES reverberation mapping sample. To perform this statistical analysis we have created a suite of customizable simulations that mimic the characteristics of each source in the OzDES sample. These characteristics include: the variability in the photometric and spectroscopic light curves, the measurement uncertainties, and the observational cadence. By simulating the sources in the OzDES sample that contain the C iv emission line, we developed a set of criteria that rank the reliability of a recovered time-lag depending on the agreement between different recovery methods, the magnitude of the uncertainties, and the rate at which false positives were found in the simulations. These criteria were applied to simulated light curves and these results used to estimate the quality of the resulting Radius–Luminosity relation. We grade the results using three quality levels (gold, silver, and bronze). The input slope of the R–L relation was recovered within 1σ for each of the three quality samples, with the gold standard having the lowest dispersion with a recovered a R–L relation slope of 0.454 ± 0.016 with an input slope of 0.47. Future work will apply these methods to the entire OzDES sample of 771 AGN.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

The impact of tomographic redshift bin width errors on cosmological probes

ABSTRACT Systematic errors in the galaxy redshift distribution n(z) can propagate to systematic errors in the derived cosmology. We characterize how the degenerate effects in tomographic bin widths and galaxy bias impart systematic errors on cosmology inference using observational data from the Deep Lens Survey. For this we use a combination of galaxy clustering and galaxy–galaxy lensing. We present two end-to-end analyses from the catalogue level to parameter estimation. We produce an initial cosmological inference using fiducial tomographic redshift bins derived from photometric redshifts, then compare this with a result where the redshift bins are empirically corrected using a set of spectroscopic redshifts. We find that the derived parameter S8 ≡ σ8(Ωm/.3)1/2 decreases from $0.841^{+0.062}_{-0.061}$ to $0.781^{0.061}_{0.054}$ upon correcting the n(z) errors in the second method.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Multienergy CT acquisition and reconstruction with a stepped tube potential scan

Purpose: Based on an energy-dependent property of matter, one may obtain a pseudomonochromatic attenuation map, a material composition image, an electron-density distribution, and an atomic number image using a dual- or multienergy computed tomography (CT) scan. Dual- and multienergy CT scans broaden the potential of x-ray CT imaging. The development of such systems is very useful in both medical and industrial investigations. In this paper, the authors propose a new dual- and multienergy CT system design (segmental multienergy CT, SegMECT) using an innovative scanning scheme that is conveniently implemented on a conventional single-energy CT system. The two-step-energy dual-energy CT can be regarded as a special case of SegMECT. A special reconstruction method is proposed to support SegMECT. Methods: In their SegMECT, a circular trajectory in a CT scan is angularly divided into several arcs. The x-ray source is set to a different tube voltage for each arc of the trajectory. Thus, the authors only need to make a few step changes to the x-ray energy during the scan to complete a multienergy data acquisition. With such a data set, the image reconstruction might suffer from severe limited-angle artifacts if using conventional reconstruction methods. To solve the problem, they present a new prior-image-based reconstruction technique using a total variance norm of a quotient image constraint. On the one hand, the prior extracts structural information from all of the projection data. On the other hand, the effect from a possibly imprecise intensity level of the prior can be mitigated by minimizing the total variance of a quotient image. Results: The authors present a new scheme for a SegMECT configuration and establish a reconstruction method for such a system. Both numerical simulation and a practical phantom experiment are conducted to validate the proposed reconstruction method and the effectiveness of the system design. The results demonstrate that the proposed SegMECT can provide both attenuation images and material decomposition images of reasonable image quality. Compared to existing methods, the new system configuration demonstrates advantages in simplicity of implementation, system cost, and dose control. Conclusions: This proposed SegMECT imaging approach has great potential for practical applications. It can be readily realized on a conventional CT system.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1995

An innovative approach to the development of a portable unit for analytical flame characterization in a microgravity environment

The availability of manned laboratory facilities in space offers wonderful opportunities and challenges in microgravity combustion science and technology. In turn, the fundamentals of microgravity combustion science can be studied via spectroscopic characterization of free radicals generated in flames. The laser-induced fluorescence (LIF) technique is a noninvasive method of considerable utility in combustion physics and chemistry suitable for monitoring not only specific species and their kinetics, but it is also important for imaging of flames. This makes LIF one of the most important tools for microgravity combustion science. Flame characterization under microgravity conditions using LIF is expected to be more informative than other methods aimed at searching for effects like pumping phenomenon that can be modeled via ground level experiments. A primary goal of our work consisted in working out an innovative approach to devising an LIF-based analytical unit suitable for in-space flame characterization. It was decided to follow two approaches in tandem: (1) use the existing laboratory (non-portable) equipment and determine the optimal set of parameters for flames that can be used as analytical criteria for flame characterization under microgravity conditions; and (2) use state-of-the-art developments in laser technology and concentrate some effort in devising a layout for the portable analytical equipment. This paper presents an up-to-date summary of the results of our experiments aimed at the creation of the portable device for combustion studies in a microgravity environment, which is based on a portable UV tunable solid-state laser for excitation of free radicals normally present in flames in detectable amounts. A systematic approach has allowed us to make a convenient choice of species under investigation, as well as the proper tunable laser system, and also enabled us to carry out LIF experiments on free radicals using a solid-state laser tunable in the UV.

Dubinskiy, Mark A.↗
NASA NTRS2000

A New Clinical Instrument for The Early Detection of Cataract Using Dynamic Light Scattering and Corneal Topography

A growing cataract can be detected at the molecular level using the technique of dynamic light scattering (DLS). However, the success of this method in clinical use depends upon the precise control of the scattering volume inside a patient's eye and especially during patient's repeat visits. This is important because the scattering volume (cross-over region between the scattered fight and incident light) inside the eye in a high-quality DLS set-up is very small (few microns in dimension). This precise control holds the key for success in the longitudinal studies of cataract and during anti-cataract drug screening. We have circumvented these problems by fabricating a new DLS fiber optic probe with a working distance of 40 mm and by mounting it inside a cone of a corneal analyzer. This analyzer is frequently used in mapping the corneal topography during PRK (photorefractive keratectomy) and LASIK (laser in situ keratomileusis) procedures in shaping of the cornea to correct myopia. This new instrument and some preliminary clinical tests on one of us (RRA) showing the data reproducibility are described.

Ansari, Rafat R.↗
NASA NTRS2008

Deep Space Network Scheduling Using Multi-Objective Optimization with Uncertainty

We have developed a novel technique to incorporate uncertainty modeling within an evolutionary algorithm approach to multi-objective scheduling, with the goal of identifying a Pareto frontier (tradeoff curve) that recognizes the likelihood of events that can impact the schedule outcome. Our approach is particularly applicable to the generation of multiobjective optimized robust schedules, where objectives are assigned a service level, for example that we require an objective value to be greater than or equal to X with Y% confidence. We have demonstrated that such an approach can, for example, minimize scheduling on less reliable resources, based solely on a resource reliability model and not on any ad hoc heuristics. We have also investigated an alternative method of optimizing for robustness, in which we add to the set of objectives a failure risk objective to minimize. We compare the advantages and disadvantages of these two approaches. Future plans for further developing this technology include its application to space-based observatory scheduling problems.

Johnston, Mark D.↗
DOE OSTI2016

Cementitious Grouts for ILW Encapsulation - Hydration and Continuity of Supply within the UK - 16184

In the UK the preferred route to disposal for the majority of intermediate level nuclear waste (ILW) streams is encapsulation within a cementitious matrix, accounting for 83% of waste conditioned to date (NDA, 2013). The method is well-defined and produces a waste package that is both chemically and physically stable, providing a multi-layered barrier to the release of the waste species contained within. Due to the process of treatment, facilitated via remote operation, it is necessary for the grouting matrices to meet strict performance limits in terms of their flow, setting time and avoidance of the formation of bleed water or segregation. To this end, the limits on composition of the anhydrous materials (a mixture of ordinary Portland cement [OPC] and blast furnace slag [BFS]) are tight to ensure conformity. Whilst these limits on composition are well understood, their impact upon grout hydration, and hence performance, is poorly defined. This study investigates the effects of modifying the physical and chemical composition of both the OPC and the BFS components of the matrix in order to identify the sensitivity or otherwise of the system to ensure that a continuity of supply is maintained. A number of techniques, scanning electron microscopy - image analysis (SEM-IA), chemical shrinkage (measured via dilatometry), isothermal conduction calorimetry (ICC), thermogravimetric analysis (TGA) and X-ray diffraction (XRD), have been applied to assess the rate and degree of hydration (DoH) of a range of grouts prepared with OPC and BFS with a range of chemical and physical compositions. This has been coupled with subsequent engineering performance testing, with additional analysis to understand the impact of a fire scenario within a storage or disposal facility, to provide an indication towards the resilience of the waste packages to a potential catastrophic event. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Complexity of many-body interactions in transition metals via machine-learned force fields from the TM23 data set

Abstract This work examines challenges associated with the accuracy of machine-learned force fields (MLFFs) for bulk solid and liquid phases ofd-block elements. In exhaustive detail, we contrast the performance of force, energy, and stress predictions across the transition metals for two leading MLFF models: a kernel-based atomic cluster expansion method implemented using sparse Gaussian processes (FLARE), and an equivariant message-passing neural network (NequIP). Early transition metals present higher relative errors and are more difficult to learn relative to late platinum- and coinage-group elements, and this trend persists across model architectures. Trends in complexity of interatomic interactions for different metals are revealed via comparison of the performance of representations with different many-body order and angular resolution. Using arguments based on perturbation theory on the occupied and unoccupieddstates near the Fermi level, we determine that the large, sharpddensity of states both above and below the Fermi level in early transition metals leads to a more complex, harder-to-learn potential energy surface for these metals. Increasing the fictitious electronic temperature (smearing) modifies the angular sensitivity of forces and makes the early transition metal forces easier to learn. This work illustrates challenges in capturing intricate properties of metallic bonding with current leading MLFFs and provides a reference data set for transition metals, aimed at benchmarking the accuracy and improving the development of emerging machine-learned approximations.

Chemistry↗
NASA NTRS2005

Exploring Diverse Data Sets and Developing New Theories and Ideas With Project Integration Architecture

The development of new ideas is the essence of scientific research. This is frequently done by developing models of physical processes and comparing model predictions with results from experiments. With models becoming ever more complex and data acquisition systems becoming more powerful, the researcher is burdened with wading through data ranging in volume up to a level of many terabytes and beyond. These data often come from multiple, heterogeneous sources and usually the methods for searching through it are at or near the manual level. In addition, current documentation methods are generally limited to researchers pen-and-paper style notebooks. Researchers may want to form constraint-based queries on a body of existing knowledge that is, itself, distributed over many different machines and environments and from the results of such queries then spawn additional queries, simulations, and data analyses in order to discover new insights into the problem being investigated. Currently, researchers are restricted to working within the boundaries of tools that are inefficient at probing current and legacy data to extend the knowledge of the problem at hand and reveal innovative and efficient solutions. A framework called the Project Integration Architecture is discussed that can address these desired functionalities.

Benyo, Theresa L.↗
DOE OSTI2023

Generative adversarial networks for scintillation signal simulation in EXO-200

Generative Adversarial Networks trained on samples of simulated or actual events have been proposed as a way of generating large simulated datasets at a reduced computational cost. In this work, a novel approach to perform the simulation of photodetector signals from the time projection chamber of the EXO-200 experiment is demonstrated. The method is based on a Wasserstein Generative Adversarial Network — a deep learning technique allowing for implicit non-parametric estimation of the population distribution for a given set of objects. Our network is trained on real calibration data using raw scintillation waveforms as input. We find that it is able to produce high-quality simulated waveforms an order of magnitude faster than the traditional simulation approach and, importantly, generalize from the training sample and discern salient high-level features of the data. In particular, the network correctly deduces position dependency of scintillation light response in the detector and correctly recognizes dead photodetector channels. Furthermore, the network output is then integrated into the EXO-200 analysis framework to show that the standard EXO-200 reconstruction routine processes the simulated waveforms to produce energy distributions comparable to that of real waveforms. Finally, the remaining discrepancies and potential ways to improve the approach further are highlighted.

47 OTHER INSTRUMENTATION↗
DOE OSTI2011

Measured and Monte Carlo calculated k{sub Q} factors: Accuracy and comparison

Purpose: The journal Medical Physics recently published two papers that determine beam quality conversion factors, k{sub Q}, for large sets of ion chambers. In the first paper [McEwen Med. Phys. 37, 2179-2193 (2010)], k{sub Q} was determined experimentally, while the second paper [Muir and Rogers Med. Phys. 37, 5939-5950 (2010)] provides k{sub Q} factors calculated using Monte Carlo simulations. This work investigates a variety of additional consistency checks to verify the accuracy of the k{sub Q} factors determined in each publication and a comparison of the two data sets. Uncertainty introduced in calculated k{sub Q} factors by possible variation of W/e with beam energy is investigated further. Methods: The validity of the experimental set of k{sub Q} factors relies on the accuracy of the NE2571 reference chamber measurements to which k{sub Q} factors for all other ion chambers are correlated. The stability of NE2571 absorbed dose to water calibration coefficients is determined and comparison to other experimental k{sub Q} factors is analyzed. Reliability of Monte Carlo calculated k{sub Q} factors is assessed through comparison to other publications that provide Monte Carlo calculations of k{sub Q} as well as an analysis of the sleeve effect, the effect of cavity length and self-consistencies between graphite-walled Farmer-chambers. Comparison between the two data sets is given in terms of the percent difference between the k{sub Q} factors presented in both publications. Results: Monitoring of the absorbed dose calibration coefficients for the NE2571 chambers over a period of more than 15 yrs exhibit consistency at a level better than 0.1%. Agreement of the NE2571 k{sub Q} factors with a quadratic fit to all other experimental data from standards labs for the same chamber is observed within 0.3%. Monte Carlo calculated k{sub Q} factors are in good agreement with most other Monte Carlo calculated k{sub Q} factors. Expected results are observed for the sleeve effect and the effect of cavity length on k{sub Q}. The mean percent differences between experimental and Monte Carlo calculated k{sub Q} factors are -0.08, -0.07, and -0.23% for the Elekta 6, 10, and 25 MV nominal beam energies, respectively. An upper limit on the variation of W/e in photon beams from cobalt-60 to 25 MV is determined as 0.4% with 95% confidence. The combined uncertainty on Monte Carlo calculated k{sub Q} factors is reassessed and amounts to between 0.40 and 0.49% depending on the wall material of the chamber. Conclusions: Excellent agreement (mean percent difference of only 0.13% for the entire data set) between experimental and calculated k{sub Q} factors is observed. For some chambers, k{sub Q} is measured for only one chamber of each type--the level of agreement observed in this study would suggest that for those chambers the measured k{sub Q} values are generally representative of the chamber type.

61 RADIATION PROTECTION AND DOSIMETRY↗