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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2008

A Process for Assessing NASA's Capability in Aircraft Noise Prediction Technology

An acoustic assessment is being conducted by NASA that has been designed to assess the current state of the art in NASA s capability to predict aircraft related noise and to establish baselines for gauging future progress in the field. The process for determining NASA s current capabilities includes quantifying the differences between noise predictions and measurements of noise from experimental tests. The computed noise predictions are being obtained from semi-empirical, analytical, statistical, and numerical codes. In addition, errors and uncertainties are being identified and quantified both in the predictions and in the measured data to further enhance the credibility of the assessment. The content of this paper contains preliminary results, since the assessment project has not been fully completed, based on the contributions of many researchers and shows a select sample of the types of results obtained regarding the prediction of aircraft noise at both the system and component levels. The system level results are for engines and aircraft. The component level results are for fan broadband noise, for jet noise from a variety of nozzles, and for airframe noise from flaps and landing gear parts. There are also sample results for sound attenuation in lined ducts with flow and the behavior of acoustic lining in ducts.

Dahl, Milo D.↗
NASA NTRS2009

Identifying Galactic Cosmic Ray Origins With Super-TIGER

Super-TIGER (Super Trans-Iron Galactic Element Recorder) is a new long-duration balloon-borne instrument designed to test and clarify an emerging model of cosmic-ray origins and models for atomic processes by which nuclei are selected for acceleration. A sensitive test of the origin of cosmic rays is the measurement of ultra heavy elemental abundances (Z > or equal 30). Super-TIGER is a large-area (5 sq m) instrument designed to measure the elements in the interval 30 < or equal Z < or equal 42 with individual-element resolution and high statistical precision, and make exploratory measurements through Z = 60. It will also measure with high statistical accuracy the energy spectra of the more abundant elements in the interval 14 < or equal Z < or equal 30 at energies 0.8 < or equal E < or equal 10 GeV/nucleon. These spectra will give a sensitive test of the hypothesis that microquasars or other sources could superpose spectral features on the otherwise smooth energy spectra previously measured with less statistical accuracy. Super-TIGER builds on the heritage of the smaller TIGER, which produced the first well-resolved measurements of elemental abundances of the elements Ga-31, Ge-32, and Se-34. We present the Super-TIGER design, schedule, and progress to date, and discuss the relevance of UH measurements to cosmic-ray origins.

deNolfo, Georgia↗
NASA NTRS2007

An Array of Optical Receivers for Deep-Space Communications

An array of small optical receivers is proposed as an alternative to a single large optical receiver for high-data-rate communications in NASA s Deep Space Network (DSN). Because the telescope for a single receiver capable of satisfying DSN requirements must be greater than 10 m in diameter, the design, building, and testing of the telescope would be very difficult and expensive. The proposed array would utilize commercially available telescopes of 1-m or smaller diameter and, therefore, could be developed and verified with considerably less difficulty and expense. The essential difference between a single-aperture optical-communications receiver and an optical-array receiver is that a single-aperture receiver focuses all of the light energy it collects onto the surface of an optical detector, whereas an array receiver focuses portions of the total collected energy onto separate detectors, optically detects each fractional energy component, then combines the electrical signal from the array of detector outputs to form the observable, or "decision statistic," used to decode the transmitted data. A conceptual block diagram identifying the key components of the optical-array receiver suitable for deep-space telemetry reception is shown in the figure. The most conspicuous feature of the receiver is the large number of small- to medium-size telescopes, with individual apertures and number of telescopes selected to make up the desired total collecting area. This array of telescopes is envisioned to be fully computer- controlled via the user interface and prediction-driven to achieve rough pointing and tracking of the desired spacecraft. Fine-pointing and tracking functions then take over to keep each telescope pointed toward the source, despite imperfect pointing predictions, telescope-drive errors, and vibration caused by wind.

Vilnrotter, Chi-Wung↗
NASA NTRS2011

Space-Time Data fusion for Remote Sensing Applications

NASA has been collecting massive amounts of remote sensing data about Earth's systems for more than a decade. Missions are selected to be complementary in quantities measured, retrieval techniques, and sampling characteristics, so these datasets are highly synergistic. To fully exploit this, a rigorous methodology for combining data with heterogeneous sampling characteristics is required. For scientific purposes, the methodology must also provide quantitative measures of uncertainty that propagate input-data uncertainty appropriately. We view this as a statistical inference problem. The true but notdirectly- observed quantities form a vector-valued field continuous in space and time. Our goal is to infer those true values or some function of them, and provide to uncertainty quantification for those inferences. We use a spatiotemporal statistical model that relates the unobserved quantities of interest at point-level to the spatially aggregated, observed data. We describe and illustrate our method using CO2 data from two NASA data sets.

carbon dioxide↗
NASA NTRS2017

Classifying Multi-Model Wheat Yield Impact Response Surfaces Showing Sensitivity to Temperature and Precipitation Change

Crop growth simulation models can differ greatly in their treatment of key processes and hence in their response to environmental conditions. Here, we used an ensemble of 26 process-based wheat models applied at sites across a European transect to compare their sensitivity to changes in temperature (minus 2 to plus 9 degrees Centigrade) and precipitation (minus 50 to plus 50 percent). Model results were analysed by plotting them as impact response surfaces (IRSs), classifying the IRS patterns of individual model simulations, describing these classes and analysing factors that may explain the major differences in model responses. The model ensemble was used to simulate yields of winter and spring wheat at four sites in Finland, Germany and Spain. Results were plotted as IRSs that show changes in yields relative to the baseline with respect to temperature and precipitation. IRSs of 30-year means and selected extreme years were classified using two approaches describing their pattern. The expert diagnostic approach (EDA) combines two aspects of IRS patterns: location of the maximum yield (nine classes) and strength of the yield response with respect to climate (four classes), resulting in a total of 36 combined classes defined using criteria pre-specified by experts. The statistical diagnostic approach (SDA) groups IRSs by comparing their pattern and magnitude, without attempting to interpret these features. It applies a hierarchical clustering method, grouping response patterns using a distance metric that combines the spatial correlation and Euclidian distance between IRS pairs. The two approaches were used to investigate whether different patterns of yield response could be related to different properties of the crop models, specifically their genealogy, calibration and process description. Although no single model property across a large model ensemble was found to explain the integrated yield response to temperature and precipitation perturbations, the application of the EDA and SDA approaches revealed their capability to distinguish: (i) stronger yield responses to precipitation for winter wheat than spring wheat; (ii) differing strengths of response to climate changes for years with anomalous weather conditions compared to period-average conditions; (iii) the influence of site conditions on yield patterns; (iv) similarities in IRS patterns among models with related genealogy; (v) similarities in IRS patterns for models with simpler process descriptions of root growth and water uptake compared to those with more complex descriptions; and (vi) a closer correspondence of IRS patterns in models using partitioning schemes to represent yield formation than in those using a harvest index. Such results can inform future crop modelling studies that seek to exploit the diversity of multi-model ensembles, by distinguishing ensemble members that span a wide range of responses as well as those that display implausible behaviour or strong mutual similarities.

Classification; Climate change; Crop model; Ensemb↗
NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6 reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped over time for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1 reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

water-related ecosystems; surface water extent; ma↗
NASA NTRS2020

Monitoring Water-Related Ecosystems with Earth Observation Data in Support of Sustainable Development Goal (SDG) 6 Reporting

Lack of national data on water-related ecosystems is a major challenge to achieving the Sustainable Development Goal (SDG) 6 targets by 2030. Monitoring surface water extent, wetlands, and water quality from space can be an important asset for many countries in support of SDG 6reporting. We demonstrate the potential for Earth observation (EO) data to support country reporting for SDG Indicator 6.6.1, ‘Change in the extent of water-related ecosystems over time’ and identify important considerations for countries using these data for SDG reporting. The spatial extent of water-related ecosystems, and the partial quality of water within these ecosystems is investigated for seven countries. Data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat 5, 7, and 8 with Shuttle Radar Topography Mission (SRTM) are used to measure surface water extent at 250 m and 30 m spatial resolution, respectively, in Cambodia, Jamaica, Peru, the Philippines, Senegal, Uganda, and Zambia. The extent of mangroves is mapped at 30 m spatial resolution using Landsat 8 Operational Land Imager (OLI), Sentinel-1, and SRTM data for Jamaica, Peru, and Senegal. Using Landsat 8 and Sentinel 2A imagery, total suspended solids and chlorophyll-a are mapped overtime for a select number of large surface water bodies in Peru, Senegal, and Zambia. All of the EO datasets used are of global coverage and publicly available at no cost. The temporal consistency and long time-series of many of the datasets enable replicability over time, making reporting of change from baseline values consistent and systematic. We find that statistical comparisons between different surface water data products can help provide some degree of confidence for countries during their validation process and highlight the need for accuracy assessments when using EO-based land change data for SDG reporting. We also raise concern that EO data in the context of SDG Indicator 6.6.1reporting may be more challenging for some countries, such as small island nations, than others to use in assessing the extent of water-related ecosystems due to scale limitations and climate variability. Country-driven validation of the EO data products remains a priority to ensure successful data integration in support of SDG Indicator 6.6.1 reporting. Multi-country studies such as this one can be valuable tools for helping to guide the evolution of SDG monitoring methodologies and provide a useful resource for countries reporting on water-related ecosystems. The EO data analyses and statistical methods used in this study can be easily replicated for country-driven validation of EO data products in the future.

Raha Hakimdavar↗
NASA NTRSDate not supplied

Large Scale Volcanism: An Explanation for the Heat-death of Venus-like Worlds

Large scale volcanism has played a critical role in the long-term habitability of Earth and possibly Venus. Large Igneous Provinces (LIPs) are in fact the cause of most major extinction events in Earth’s history, contrary to the popular belief about the devastation from large bolides. We examine the timing of Large Igneous Provinces (LIPs) through Earth’s history [1] to estimate the likelihood of nearly simultaneous events that could drive a planet into an extreme moist or runaway greenhouse, quenching subductive plate tectonics. Such events would end volatile cycling and may have driven Venus from a cool temperate state into the heat-death we see today. Using the Earth's LIP record [1] we have found that LIP events are distributed randomly throughout the past 3 billion years. A conservative estimate of the rate of LIPs in a random history statistically the same as Earth’s, pairs and triplets of LIPs closer in time than 0.1-1 million years are likely. This simultaneity threshold is significant to the extent that it is less than the time over which environmental effects have been shown to persist, for example in the Siberian Traps record [2,3]. With the recent mission selections of VERITAS and EnVision it may be possible for their high resolution radar maps to distinguish LIPs in the surface record we can see today on Venus.

Large Igneous Provinces↗
DOE OSTI2017

Resolved Stellar Streams around NGC 4631 from a Subaru/Hyper Suprime-Cam Survey

We present the first results of the Subaru/Hyper Suprime-Cam survey of the interacting galaxy system, NGC 4631 and NGC 4656. From the maps of resolved stellar populations, we identify 11 dwarf galaxies (including already-known dwarfs) in the outer region of NGC 4631 and the two tidal stellar streams around NGC 4631, named Stream SE and Stream NW, respectively. This paper describes the fundamental properties of these tidal streams. Based on the tip of the red giant branch method and the Bayesian statistics, we find that Stream SE (7.10 Mpc in expected a posteriori, EAP, with 90% credible intervals of [6.22, 7.29] Mpc) and Stream NW (7.91 Mpc in EAP with 90% credible intervals of [6.44, 7.97] Mpc) are located in front of and behind NGC 4631, respectively. We also calculate the metallicity distribution of stellar streams by comparing the member stars with theoretical isochrones on the color–magnitude diagram. We find that both streams have the same stellar population based on the Bayesian model selection method, suggesting that they originated from a tidal interaction between NGC 4631 and a single dwarf satellite. The expected progenitor has a positively skewed metallicity distribution function with [M/H]{sub EAP}=−0.92, with 90% credible intervals of [−1.46, −0.51]. The stellar mass of the progenitor is estimated as 3.7×10{sup 8} M{sub ⊙}, with 90% credible intervals of [5.8×10{sup 6},8.6×10{sup 9}] M{sub ⊙} based on the mass–metallicity relation for Local group dwarf galaxies. This is in good agreement with the initial stellar mass of the progenitor that was presumed in the previous N-body simulation.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2013

SynGenics Optimization System (SynOptSys)

The SynGenics Optimization System (SynOptSys) software application optimizes a product with respect to multiple, competing criteria using statistical Design of Experiments, Response-Surface Methodology, and the Desirability Optimization Methodology. The user is not required to be skilled in the underlying math; thus, SynOptSys can help designers and product developers overcome the barriers that prevent them from using powerful techniques to develop better pro ducts in a less costly manner. SynOpt-Sys is applicable to the design of any product or process with multiple criteria to meet, and at least two factors that influence achievement of those criteria. The user begins with a selected solution principle or system concept and a set of criteria that needs to be satisfied. The criteria may be expressed in terms of documented desirements or defined responses that the future system needs to achieve. Documented desirements can be imported into SynOptSys or created and documented directly within SynOptSys. Subsequent steps include identifying factors, specifying model order for each response, designing the experiment, running the experiment and gathering the data, analyzing the results, and determining the specifications for the optimized system. The user may also enter textual information as the project progresses. Data is easily edited within SynOptSys, and the software design enables full traceability within any step in the process, and facilitates reporting as needed. SynOptSys is unique in the way responses are defined and the nuances of the goodness associated with changes in response values for each of the responses of interest. The Desirability Optimization Methodology provides the basis of this novel feature. Moreover, this is a complete, guided design and optimization process tool with embedded math that can remain invisible to the user. It is not a standalone statistical program; it is a design and optimization system.

Ventresca, Carol↗
DOE OSTI2018

Dose‐response relationships between internally‐deposited uranium and select health outcomes in gaseous diffusion plant workers, 1948‐2011

Objective To examine dose‐response relationships between internal uranium exposures and select outcomes among a cohort of uranium enrichment workers. Methods Cox regression was conducted to examine associations between selected health outcomes and cumulative internal uranium with consideration for external ionizing radiation, work‐related medical X‐rays and contaminant radionuclides technetium ( 99 Tc) and plutonium ( 239 Pu) as potential confounders. Results Elevated and monotonically increasing mortality risks were observed for kidney cancer, chronic renal diseases, and multiple myeloma, and the association with internal uranium absorbed organ dose was statistically significant for multiple myeloma. Adjustment for potential confounders had minimal impact on the risk estimates. Conclusion Kidney cancer, chronic renal disease, and multiple myeloma mortality risks were elevated with increasing internal uranium absorbed organ dose. The findings add to evidence of an association between internal exposure to uranium and cancer. Future investigation includes a study of cancer incidence in this cohort.

Yiin, James H.↗
DOE OSTI2019

Droplet size distributions in turbulent clouds: experimental evaluation of theoretical distributions

Precipitation efficiency and optical properties of clouds, both central to determining Earth's weather and climate, depend on the size distribution of cloud particles. Here in this paper, theoretical expressions for cloud droplet size distribution shape are evaluated using measurements from controlled experiments in a convective-cloud chamber. The experiments are a unique opportunity to constrain theory because they are in steady-state and because the initial and boundary conditions are well characterized compared to typical atmospheric measurements. Three theoretical distributions obtained from a Langevin drift-diffusion approach to cloud formation via stochastic condensation are tested: (a) stochastic condensation with a constant removal time-scale; (b) stochastic condensation with a size-dependent removal time-scale; (c) droplet growth in a fixed supersaturation condition and with size-dependent removal. In addition, a similar Weibull distribution that can be obtained from the drift-diffusion approach, as well as from mechanism-independent probabilistic arguments (e.g., maximum entropy), is tested as a fourth hypothesis. Statistical techniques such as the χ2 test, sum of squared errors of prediction, and residual analysis are employed to judge relative success or failure of the theoretical distributions to describe the experimental data. An extensive set of cloud droplet size distributions are measured under different aerosol injection rates. Five different aerosol injection rates are run both for size-selected aerosol particles, and six aerosol injection rates are run for broad-distribution, polydisperse aerosol particles. In relative comparison, the most favourable comparison to the measurements is the expression for stochastic condensation with size-dependent droplet removal rate. However, even this optimal distribution breaks down for broad aerosol size distributions, primarily due to deviations from the measured large-droplet tail. Lastly, a possible explanation for the deviation is the Ostwald ripening effect coupled with deactivation/activation in polluted cloud conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Bayesian Adaptive Polynomial Chaos Expansions

Polynomial chaos expansions (PCEs) are widely used for uncertainty quantification (UQ) tasks, particularly in the applied mathematics community. However, PCE has received comparatively less attention in the statistics literature, and fully Bayesian formulations remain rare—especially with implementations in R. Motivated by the success of adaptive Bayesian machine learning models such as BART, BASS and BPPR, we develop a new fully Bayesian adaptive PCE method with an efficient and accessible R implementation: khaos. Our approach includes a novel proposal distribution that enables data-driven interaction selection and supports a modified g-prior tailored to PCE structure. Through simulation studies and real-world UQ applications, we demonstrate that the Bayesian adaptive PCE provides competitive performance for surrogate modeling, global sensitivity analysis and ordinal regression tasks.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

CODEX clusters

Context: Large area catalogs of galaxy clusters constructed from ROSAT All-Sky Survey provide the basis for our knowledge of the population of clusters thanks to long-term multiwavelength efforts to follow up observations of these clusters. Aims: The advent of large area photometric surveys superseding previous, in-depth all-sky data allows us to revisit the construction of X-ray cluster catalogs, extending the study to lower cluster masses and higher redshifts and providing modeling of the selection function. Methods: We performed a wavelet detection of X-ray sources and made extensive simulations of the detection of clusters in the RASS data. We assigned an optical richness to each of the 24 788 detected X-ray sources in the 10 382 square degrees of the Baryon Oscillation Spectroscopic Survey area using red sequence cluster finder redMaPPer version 5.2 run on Sloan Digital Sky Survey photometry. We named this survey COnstrain Dark Energy with X-ray (CODEX) clusters. Results: We show that there is no obvious separation of sources on galaxy clusters and active galactic nuclei (AGN) based on the distribution of systems on their richness. This is a combination of an increasing number of galaxy groups and their selection via the identification of X-ray sources either by chance or by groups hosting an AGN. To clean the sample, we use a cut on the optical richness at the level corresponding to the 10% completeness of the survey and include it in the modeling of the cluster selection function. We present the X-ray catalog extending to a redshift of 0.6. Conclusions: The CODEX suvey is the first large area X-ray selected catalog of northern clusters reaching fluxes of 10 –13 ergs s –1 cm –2 . We provide modeling of the sample selection and discuss the redshift evolution of the high end of the X-ray luminosity function (XLF). Our results on z < 0.3 XLF agree with previous studies, while we provide new constraints on the 0.3 < z < 0.6 XLF. We find a lack of strong redshift evolution of the XLF, provide exact modeling of the effect of low number statistics and AGN contamination, and present the resulting constraints on the flat ΛCDM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Prompt fission neutron and gamma ray properties as a function of incident neutron energy

The CGMF code provides a complete description of the properties of the prompt neutrons and γ rays, emitted before beta decays. It is based on a Monte Carlo implementation of the Hauser-Feshbach statistical model, which provides an accurate phenomenological description of the de-excitation of the fission fragments toward stable configurations via neutron and γ-ray emissions. This approach allows a detailed description of a large number of observables, such as multiplicity probabilities and correlations between the emitted particles. In this contribution, we briefly review the approach and present selected examples of neutron and γ-ray observables for neutron incident energies from thermal to 20 MeV, and compare against available data for 235 U(n,f) reaction.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2017

Sharp predictions from eternal inflation patches in D-brane inflation

We numerically generate the six-dimensional landscape of D3-brane inflation and identify patches of eternal inflation near sufficiently flat inflection points of the potential. We show that reasonable measures that select patches of eternal inflation in the landscape yield sharp predictions for the spectral properties of primordial perturbations on observable scales. These include a scalar tilt of .936, a running of the scalar tilt −.00103, undetectably small tensors and non-Gaussianity, and no observable spatial curvature. Our results explicitly demonstrate that precision cosmology probes the combination of the statistical properties of the string landscape and the measure implied by the universe's quantum state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

UrbanScaping: Community Spatial Data Visualization & Analytics

Evaluating the electrification potential of buildings through retrofitting is crucial for reducing carbon emissions and the carbon footprint of built environments. This study leverages the Automatic Building Energy Modeling (AutoBEM) software, integrating the Model America database to create an urban context-based spatial analysis platform for community engagement and development. We selected Camp Hill Borough, PA, as a case study to analyze building-specific energy performance and evaluate the electrification potential of each building by switching to different Heating, Ventilation, and Air Conditioning (HVAC) systems and measurement components. The simulation results generated by the workflow provide retrofitting suggestions to help mitigate the carbon footprint as well as energy saving statistics of buildings. Additionally, the developed web-based interface serves as a community engagement platform, allowing residents to provide feedback and further develop interactive communication protocols. The outcomes of this project offer a baseline for community electrification planning and contribute to the design of low-carbon communities.

Chowdhury, Shovan [ORNL]↗
DOE OSTI2015

SU-E-T-77: A Statistical Approach to Manage Quality for Pre-Treatment Verification in IMRT/VMAT

Objective: The study presents the application of a simple concept of statistical process control (SPC) for pre-treatment quality assurance procedure analysis for planar dose measurements performed using 2D-array and a-Si electronic portal imaging device (a-Si EPID). Method: A total of 195 patients of four different anatomical sites: brain (n1=45), head & neck (n2=45), thorax (n3=50) and pelvis (n4=55) were selected for the study. Pre-treatment quality assurance for the clinically acceptable IMRT/VMAT plans was measured with 2D array and a-Si EPID of the accelerator. After the γ-analysis, control charts and the quality index Cpm was evaluated for each cohort. Results: Mean and σ of γ ( 3%/3 mm) were EPID γ %≤1= 99.9% ± 1.15% and array γ %<1 = 99.6% ± 1.06%. Among all plans γ max was consistently lower than for 2D array as compared to a-Si EPID. Fig.1 presents the X-bar control charts for every cohort. Cpm values for a-Si EPID were found to be higher than array, detailed results are presented in table 1. Conclusion: Present study demonstrates the significance of control charts used for quality management purposes in newer radiotherapy clinics. Also, provides a pictorial overview of the clinic performance for the advanced radiotherapy techniques.Higher Cpm values for EPID indicate its higher efficiency than array based measurements.

60 APPLIED LIFE SCIENCES↗