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Results for “statistically designed experiments”

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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

MC performance study for an early $v_μ$ charged-current inclusive analysis with MicroBooNE

This note describes an analysis performed on Monte Carlo data to evaluate the sensitivity of MicroBooNE for an early ν µ charged-current inclusive cross section measurement. Such an analysis is intended to be done using the first three months of Booster Neutrino Beam data. The event selection is entirely based on an automated event reconstruction. The Monte Carlo prediction for a flux-integrated and single differential cross section measurement with an approximate estimation of statistical and systematic uncertainties for the MicroBooNE detector as designed is presented. This allows the comparison of the sensitivity of MicroBooNE to theory and other experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Formal Experimentation and Analysis of Handheld RFID Readers as a Tool for Nuclear Material Accounting

Commercial, off-the-shelf Radio Frequency Identification (RFID) systems have been successfully deployed for inventory tracking in numerous industries, but their viability in the tracking of complex environments containing nuclear material is less understood. Of primary interest in this setting is a RFID tracking system for nuclear material accounting which can reliably identify as many tags as possible with high accuracy, while also reducing an operator’s exposure to radiation. In this work, we develop a formal statistical approach to identify relevant handheld RFID reader settings which optimize tagging performance. To achieve this goal, we design a full factorial split-plot experiment for a static shelf configuration scene with 50 randomly placed nuclear material containers affixed with RFID tags. We use Bayesian inference to fit a second-order response surface model which expresses the probability of a successful match for each container as a function of the experimental factors. Such effects are allowed to vary across individual containers and the containers’ population in its entirety to estimate overall effects. Uncertainties of estimates and predictions are quantified via their corresponding posterior distributions. Following extensive model checking and validation, the fitted model is used to identify experimental factors which maximize matching probabilities at both the container-level and for the full shelf configuration scene. We also analyze sensitivity of performance to relevant factors.

25 ENERGY STORAGE↗
DOE OSTI2015

Plackett-Burman experimental design to facilitate syntactic foam development

The use of an eight-experiment Plackett–Burman method can assess six experimental variables and eight responses in a polysiloxane-glass microsphere syntactic foam. The approach aims to decrease the time required to develop a tunable polymer composite by identifying a reduced set of variables and responses suitable for future predictive modeling. The statistical design assesses the main effects of mixing process parameters, polymer matrix composition, microsphere density and volume loading, and the blending of two grades of microspheres, using a dummy factor in statistical calculations. Responses cover rheological, physical, thermal, and mechanical properties. The cure accelerator content of the polymer matrix and the volume loading of the microspheres have the largest effects on foam properties. These factors are the most suitable for controlling the gel point of the curing foam, and the density of the cured foam. The mixing parameters introduce widespread variability and therefore should be fixed at effective levels during follow-up testing. Some responses may require greater contrast in microsphere-related factors. As a result, compared to other possible statistical approaches, the run economy of the Plackett–Burman method makes it a valuable tool for rapidly characterizing new foams.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Making inertial confinement fusion models more predictive

Computer models of inertial confinement fusion (ICF) implosions play an essential role in experimental design and interpretation as well as our understanding of fundamental physics under the most extreme conditions that can be reached in the laboratory. Building truly predictive models is a significant challenge, with the potential to greatly accelerate progress to high yield and ignition. One path to more predictive models is to use experimental data to update the underlying physics in a way that can be extrapolated to new experiments and regimes. We describe a statistical framework for the calibration of ICF simulations using data collected at the National Ignition Facility (NIF). We perform Bayesian inferences for a series of laser shots using an approach that is designed to respect the physics simulation as much as possible and then build a second model that links the individual-shot inferences together. We show that this approach is able to match multiple X-ray and neutron diagnostics for a whole series of NIF “BigFoot” shots. Within the context of 2D radiation hydrodynamic simulations, our inference strongly favors a significant reduction in fuel compression over other known degradation mechanisms (namely, hohlraum issues and engineering perturbations). This analysis is expanded using a multifidelity technique to pick fuel-ablator mix from several candidate causes of the degraded fuel compression (including X-ray preheat and shock timing errors). Finally, we use our globally calibrated model to investigate the extra laser drive energy that would be required to overcome the inferred fuel compression issues in NIF BigFoot implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Discontinuities in effective permeability due to fracture percolation

Motivated by a triaxial coreflood experiment with a sample of Utica shale where an abrupt jump in permeability was observed, possibly due to the creation of a percolating fracture network through the sample, we perform numerical simulations based on the experiment to characterize how the effective permeability of otherwise low-permeability porous media depends on fracture formation, connectivity, and the contrast between the fracture and matrix permeabilities. While a change in effective permeability due to fracture formation is expected, the dependence of its magnitude upon the contrast between the matrix permeability and fracture permeability and the fracture network structure is poorly characterized. We use two different high-fidelity fracture network models to characterize how effective permeability changes as percolation occurs. The first is a dynamic two-dimensional fracture propagation model designed to mimic the laboratory settings of the experiment. The second is a static three-dimensional discrete fracture network (DFN) model, whose fracture and network statistics are based on the fractured sample of Utica shale. Once the network connects the inflow and outflow boundaries, the effective permeability increases non-linearly with network density. In most networks considered, a jump in the effective permeability was observed when the embedded fracture network percolated. We characterize how the magnitude of the jump, should it occur, depends on the contrast between the fracture and matrix permeabilities. For small contrasts between the matrix and fracture permeabilities the change is insignificant. However, for larger contrasts, there is a substantial jump whose magnitude depends non-linearly on the difference between matrix and fracture permeabilities. A power-law relationship between the size of the jump and the difference between the matrix and fracture permeabilities is observed. In conclusion, the presented results underscore the importance of fracture network topology on the upscaled properties of the porous medium in which it is embedded.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Data mining graphene: Correlative analysis of structure and electronic degrees of freedom in graphenic monolayers with defects

The link between changes in the material crystal structure and its mechanical, electronic, magnetic, and optical functionalities known as the structure-property relationship is the cornerstone of the contemporary materials science research. The recent advances in scanning transmission electron and scanning probe microscopies (STEM and SPM) have opened an unprecedented path towards examining the materials structure property relationships on the single-impurity and atomic-configuration levels. Lacking, however, are the statistics-based approaches for cross-correlation of structure and property variables obtained in different information channels of the STEM and SPM experiments. Here we have designed an approach based on a combination of sliding window Fast Fourier Transform, Pearson correlation matrix, linear and kernel canonical correlation, to study a relationship between lattice distortions and electron scattering from the SPM data on graphene with defects. Our analysis revealed that the strength of coupling to strain is altered between different scattering channels which can explain coexistence of several quasiparticle interference patterns in the nanoscale regions of interest. In addition, the application of the kernel functions allowed us extracting a non-linear component of the relationship between the lattice strain and scattering intensity in graphene. Lastly, the outlined approach can be further utilized to analyzing correlations in various multi-modal imaging techniques where the information of interest is spatially distributed and has usually a complex multidimensional nature.

36 MATERIALS SCIENCE↗
NASA NTRS1986

Graduate engineering research participation in aeronautics

The Aeronautics Graduate Research Program commenced in 1971, with the primary goal of engaging students who qualified for regular admission to the Graduate School of Engineering at Old Dominion University in a graduate engineering research and study program in collaboration with NASA Langley Research Center, Hampton, Virginia. The format and purposes of this program are discussed. Student selection and program statistics are summarized. Abstracts are presented in the folowing areas: aircraft design, aerodynamics, lift/drag characteristics; avionics; fluid mechanics; solid mechanics; instrumentation and measurement techniques; thermophysical properties experiments; large space structures; earth orbital dynamics; and environmental engineering.

Roberts, A. S., Jr.↗
NASA NTRS1997

CARES/Life Software for Designing More Reliable Ceramic Parts

Products made from advanced ceramics show great promise for revolutionizing aerospace and terrestrial propulsion, and power generation. However, ceramic components are difficult to design because brittle materials in general have widely varying strength values. The CAPES/Life software eases this task by providing a tool to optimize the design and manufacture of brittle material components using probabilistic reliability analysis techniques. Probabilistic component design involves predicting the probability of failure for a thermomechanically loaded component from specimen rupture data. Typically, these experiments are performed using many simple geometry flexural or tensile test specimens. A static, dynamic, or cyclic load is applied to each specimen until fracture. Statistical strength and SCG (fatigue) parameters are then determined from these data. Using these parameters and the results obtained from a finite element analysis, the time-dependent reliability for a complex component geometry and loading is then predicted. Appropriate design changes are made until an acceptable probability of failure has been reached.

Nemeth, Noel N.↗
DOE OSTI2016

Probing Flavor Asymmetry of Anti-quarks in the Proton by Drell-Yan Experiment SeaQuest

A new measurement on the avor asymmetry between d and u in the proton is reported in this thesis. The proton contains a substantial number of antiquarks which arise from dynamical interactions of gluons such as gluon dissociation to a quark-antiquark pair, g ! q + q, and from non-perturbative processes as described by the pion-cloud model, for example. The antiquarks in the proton undertake an important role in determining the dynamic characteristics of the internal structure of the proton, although its distribution in the proton and its origin are not fully understood. Understanding sea quarks in hadron is an important subject for QCD. The SeaQuest experiment at Fermi National Accelerator Laboratory (Fermilab) is a xed target experiment using the 120 GeV proton beam extracted from the Fermilab Main Injector. One of the goals of the experiment is to measure the avor asymmetry between d quark and u quark in the proton as a function of the target Bjorken x using the Drell-Yan process in the p-p or p-d reactions. This process takes place in hadron-hadron collisions when a quark in one hadron in the beam and an antiquark in other hadron in the target annihilate into a virtual photon that decays into a lepton pair. The avor asymmetry between d and u quarks was found by deep-inelastic scattering experiment NMC at CERN. The E866/NuSea experiment at Fermilab obtained the avor asymmetry in the proton for 0:015 < x < 0:35 using the 800 GeV proton beam extracted from the Fermilab Tevatron. The result indicates the dominance of d; it is 70% larger than u at lower x. The SeaQuest experiment was planned to do a new precise measurement at higher x region. The lower energy beam (120 GeV) increases the Drell-Yan cross section and suppresses the background primarily arising from J/ decays. Therefore, SeaQuest will obtain more statistics in a shorter time than the E866 experiment. After detector construction, detector commissioning and accelerator upgrade, physics data taking started in 2013. The SeaQuest spectrometer is designed to detect dimuon from the Drell-Yan process. It consists of targets, two di-pole magnets, and four tracking detector groups. The third tracking detector group has two drift chambers. One was newly fabricated in Japan by the Japanese group in SeaQuest collaboration and was shipped to Fermilab. The other one was constructed by SeaQuest collaborator in Fermilab under the initiative of the Japanese group. I worked on the construction and installation of the detectors, data taking and data analysis in SeaQuest. I extracted the avor asymmetry as a function of Bjorken x using the SeaQuest data for the rst time. This thesis shows the results using a part of data taken in 2014 and 2015. The asymmetry was extracted for much wider Bjorken x region than the previous experiment. The measured Bjorken x range covers up to 0.58. The result shows that the ratio of d=u is always higher than 1 at 0:1 < x < 0:45, in contrast to the E866 result. For 0:45 < x < 0:58, the result shows that the ratio is close to unity. Predictions made by current PDF parameterizations are in agreement with the present result. Also, a prediction obtained by one of the non-perturbative models, pion-cloud model, is closer to the SeaQuest result than the E866 result. This result of d=u asymmetry at the wide Bjorken x region, 0:1 < x < 0:58, is very important information to understand the inner structure of the proton and the origin of the sea quarks in the proton.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1985

Aerospace spacecraft-charging guidelines document

A short summary document on spacecraft charging was prepared for use by engineers in the various Aerospace Corporation program offices that support Air Force Space Division programs. The magnetospheric charging environment at near-geosynchronous altitudes is outlined and the mechanisms of charging and discharging are discussed. Statistical results from the P78-2 (SCATHA) satellite engineering experiments are given. The document is intended to be a layman's source for charging information and for design guidance and criteria.

Fennell, J. F.↗
NASA NTRS1999

Moisture Forecast Bias Correction in GEOS DAS

Data assimilation methods rely on numerous assumptions about the errors involved in measuring and forecasting atmospheric fields. One of the more disturbing of these is that short-term model forecasts are assumed to be unbiased. In case of atmospheric moisture, for example, observational evidence shows that the systematic component of errors in forecasts and analyses is often of the same order of magnitude as the random component. we have implemented a sequential algorithm for estimating forecast moisture bias from rawinsonde data in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The algorithm is designed to remove the systematic component of analysis errors and can be easily incorporated in an existing statistical data assimilation system. We will present results of initial experiments that show a significant reduction of bias in the GEOS DAS moisture analyses.

Dee, D.↗
NASA NTRS2019

Refinement of Vortex Generators in a Streamline-Traced, External-Compression Supersonic Inlet

Computational simulations of the flow within a streamline-traced, external-compression supersonic inlet for Mach 1.664 without and with vortex generators were performed to refine the characterization of the inlet performance as measured by the total pressure recovery and the radial and circumferential total pressure distortion indices at the engine face. The refinement of the simulations concerned two aspects: 1) refinement of the grid for the simulations to evaluate and reduce uncertainty, and 2) refinement of the modeling and design of the vortex generators. The vortex generators studied were rectangular vane-type vortex generators arranged in co-rotating arrays within the subsonic diffuser. The vortex generator geometric factors of interest included the height, circumferential spacing, and angle-of-incidence. The flow through the inlet was simulated numerically through the solution of the steady-state, Reynolds-averaged Navier-Stokes equations on multi-block, structured grids using the Wind-US flow solver. The vortex generators were simulated using either a vortex generator model or with grids generated about each vortex generator. Statistical methods were used to compute confidence intervals and grid convergence indices to establish the uncertainties of the analyses with respect to grid refinement. Design-of-experiments methods were applied to quantify the effects of the geometric factors of the vortex generators. The analyses of the computed results illustrate the complexities of quantifying the uncertainties of the inlet performance and the implications of the uncertainties for the design of a vortex generator array for the STEX inlet.

Slater, John W.↗
DOE OSTI2015

TU-CD-BRD-00: Incident Learning / RO-ILS

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-CD-BRD-01: Making Incident Learning Practical and Useful: Challenges and Previous Experiences

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-CD-BRD-02: Henry Ford Hospital System Experience, with Focus On Motivating and Reviewing

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-CD-BRD-03: UCSD Experience, with Focus On Implementing Change

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

TU-CD-BRD-04: UCLA Experience, with Focus On Developing Metrics and Using RO-ILS

It has long been standard practice in radiation oncology to report internally when a patient’s treatment has not gone as planned and to report events to regulatory agencies when legally required. Most potential errors are caught early and never affect the patient. Quality assurance steps routinely prevent errors from reaching the patient, and these “near misses” are much more frequent than treatment errors. A growing number of radiation oncology facilities have implemented incident learning systems to report and analyze both errors and near misses. Using the term “incident learning” instead of “event reporting” emphasizes the need to use these experiences to change the practice and make future errors less likely and promote an educational, non-punitive environment. There are challenges in making such a system practical and effective. Speakers from institutions of different sizes and practice environments will share their experiences on how to make such a system work and what benefits their clinics have accrued. Questions that will be addressed include: How to create a system that is easy for front line staff to access How to motivate staff to report How to promote the system as positive and educational and not punitive or demeaning How to organize the team for reviewing and responding to reports How to prioritize which reports to discuss in depth How not to dismiss the rest How to identify underlying causes How to design corrective actions and implement change How to develop useful statistics and analysis tools How to coordinate a departmental system with a larger risk management system How to do this without a dedicated quality manager Some speakers’ experience is with in-house systems and some will share experience with the AAPM/ASTRO national Radiation Oncology Incident Learning System (RO-ILS). Reports intended to be of value nationally need to be comprehensible to outsiders; examples of useful reports will be shown. There will be ample time set aside for audience members to contribute to the discussion. Learning Objectives: Learn how to promote the use of an incident learning system in a clinic. Learn how to convert “event reporting” into “incident learning”. See examples of practice changes that have come out of learning systems. Learn how the RO-ILS system can be used as a primary internal learning system. Learn how to create succinct, meaningful reports useful to outside readers. Gary Ezzell chairs the AAPM committee overseeing RO-ILS and has received an honorarium from ASTRO for working on the committee reviewing RO-ILS reports. Derek Brown is a director of http://TreatSafely.org . Brett Miller has previously received travel expenses and an honorarium from Varian. Phillip Beron has nothing to report.

60 APPLIED LIFE SCIENCES↗