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

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At least 145 records · Page 8

Library based x-ray scatter correction for dedicated cone beam breast CT

Purpose: The image quality of dedicated cone beam breast CT (CBBCT) is limited by substantial scatter contamination, resulting in cupping artifacts and contrast-loss in reconstructed images. Such effects obscure the visibility of soft-tissue lesions and calcifications, which hinders breast cancer detection and diagnosis. In this work, we propose a library-based software approach to suppress scatter on CBBCT images with high efficiency, accuracy, and reliability. Methods: The authors precompute a scatter library on simplified breast models with different sizes using the GEANT4-based Monte Carlo (MC) toolkit. The breast is approximated as a semiellipsoid with homogeneous glandular/adipose tissue mixture. For scatter correction on real clinical data, the authors estimate the breast size from a first-pass breast CT reconstruction and then select the corresponding scatter distribution from the library. The selected scatter distribution from simplified breast models is spatially translated to match the projection data from the clinical scan and is subtracted from the measured projection for effective scatter correction. The method performance was evaluated using 15 sets of patient data, with a wide range of breast sizes representing about 95% of general population. Spatial nonuniformity (SNU) and contrast to signal deviation ratio (CDR) were used as metrics for evaluation. Results: Since the time-consuming MC simulation for library generation is precomputed, the authors’ method efficiently corrects for scatter with minimal processing time. Furthermore, the authors find that a scatter library on a simple breast model with only one input parameter, i.e., the breast diameter, sufficiently guarantees improvements in SNU and CDR. For the 15 clinical datasets, the authors’ method reduces the average SNU from 7.14% to 2.47% in coronal views and from 10.14% to 3.02% in sagittal views. On average, the CDR is improved by a factor of 1.49 in coronal views and 2.12 in sagittal views. Conclusions: The library-based scatter correction does not require increase in radiation dose or hardware modifications, and it improves over the existing methods on implementation simplicity and computational efficiency. As demonstrated through patient studies, the authors’ approach is effective and stable, and is therefore clinically attractive for CBBCT imaging.

60 APPLIED LIFE SCIENCES↗

DEPOSITION VELOCITY ESTIMATION WITH THE GENII V2 SOFTWARE

In 2010, the Department of Energy (DOE) Chief of Nuclear Safety and Office of Health, Safety and Security (HSS), with the support of industry experts in atmospheric sciences and accident dose consequences analysis, performed detailed analyses of the basis for the dry deposition velocity (DV) values used in the MACCS2 computer code. As a result of these analyses, DOE concluded that the historically used default DV values of 1 centimeter/second (cm/s) for unfiltered/unmitigated releases and 0.1 cm/s for filtered/mitigated releases may not be reasonably conservative for all DOE sites and accident scenarios. HSS recently issued Safety Bulletin 2011-02, Accident Analysis Parameter Update, recommending the use of the newly developed default DV, 0.1 cm/s for an unmitigated/unfiltered release. Alternatively site specific DV values can be developed using GENII version 2 (GENII v2) computer code. Key input parameters for calculating DV values include surface roughness, maximum wind speed for calm, particle size, particle density and meteorological data (wind speed and stability class). This paper will include reasonably conservative inputs, and a truncated parametric study. In lieu of the highly-conservative recommended DV value (0.1cm/s) for unmitigated/unfiltered release, GENII v2 has been used to justify estimated 95th percentile DV values. Also presented here are atmospheric dilution factors ({chi}/Q values) calculated with the MACCS2 code using the DV values form GENII v2, {chi}/Q values calculated directly with GENII v2, and a discussion of these results compare with one another. This paper will give an overview of the process of calculating DV with GENII v2 including a discussion of the sensitivity of input parameters.

99 GENERAL AND MISCELLANEOUS↗

A deep learning-based battery sizing optimization tool for hybridizing generation plants

Hybrid generation and energy storage systems offer the ability to increase flexibility of the combined asset. This flexibility can be used to increase provision of services already provided by the generation asset, such as timing sale of electricity to the energy market during high price periods, and also enable provision of additional services, such as ancillary services or contribute to resource adequacy. From a generation asset owner perspective, the decision to hybridize includes selecting an energy storage system that, among other factors, maximizes financial performance of the energy storage investment. Yet, existing tools to optimize energy storage sizing are either too rudimentary (i.e., based on “rules of thumb”) or too complex to implement (i.e., require specialized engineering and software knowledge and a high-performance computer to run). This work presents a novel deep learning-based battery sizing optimization tool that is designed to help generation asset owners easily assess preliminary sizing considerations for potential battery investments to hybridize their generation facility. The tool uses deep learning to predict revenue over a broad search space of potential battery sizes, estimates capital and operating costs (including accounting for battery degradation), and computes financial performance of each potential battery system investment, recommending a system with maximum financial performance. The tool is tested and validated for hydropower assets. Finally, this tool will help a greater cross-section of industry consider investments in battery systems, increasing their revenue and helping them compete in rapidly evolving electrify markets.

13 HYDRO ENERGY↗

Cloud Thickness from Diffusion of Lidar Pulses in Clouds

Measurements of the distribution of reflected light from a laser beam incident on an aqueous suspension of particles or "cloud" with known thickness and particle size distribution are reported. The distribution is referred to as the "cloud radiative Green's function", G. In the diffusion domain, G is sensitive to cloud thickness, allowing that important quantity to be retrieved. The goal of the laboratory simulation is to provide preliminary estimates of sensitivity of G to cloud thickness,for use in the optimal design of an offbeam Lidar instrument for remote sensing of cloud thickness (THOR, Thickness from Offbeam Returns). These clouds of polystyrene microspheres suspended in water are analogous to real clouds of water droplets suspended in air. The microsphere size distribution is roughly lognormal, from 0.5 microns to 25 microns, similar to real clouds. Density of suspended spheres is adjusted so mean-free-path of visible photons is about 10 cm, approximately 1000 times smaller than in real clouds. The light source is a ND:YAG laser at 530 nm. Detectors are flux and photon-counting Photomultiplier Tube (PMTS), with a glass probe for precise positioning. A Labview 5 VI controls positioning, and data acquisition, via an NI Motion Control board connected to a stepper motor driving an Edmund linear slider, and a 16-channel 16-bit NI-DAQ board. The stepper motor is accurate to 10 microns, and step size is selectable from the VI software. Far from the incident beam, the rate of exponential increase as the direction of the incident beam is approached scales as expected from diffusion theory, linearly with the cloud thickness, and inversely as the square root of the reduced optical thickness, and is independent of particle size. Near the beam the signal begins to increase faster than exponential, due to single and low-order scattering near the backward direction, and here the distribution depends on particle size. Results are being used to verify 3D Monte Carlo radiative transfer simulations, used to estimate signal-to-noise ratios for remotely sensed off beam returns, for both homogeneous and inhomogeneous clouds. Signal-to-noise estimates show that unfiltered observations are straight forward at night, while narrow band pass filters are being studied for day.

Cahalan, Robert F.↗

Analyzing Responses of Chemical Sensor Arrays

NASA is developing a third-generation electronic nose (ENose) capable of continuous monitoring of the International Space Station s cabin atmosphere for specific, harmful airborne contaminants. Previous generations of the ENose have been described in prior NASA Tech Briefs issues. Sensor selection is critical in both (prefabrication) sensor material selection and (post-fabrication) data analysis of the ENose, which detects several analytes that are difficult to detect, or that are at very low concentration ranges. Existing sensor selection approaches usually include limited statistical measures, where selectivity is more important but reliability and sensitivity are not of concern. When reliability and sensitivity can be major limiting factors in detecting target compounds reliably, the existing approach is not able to provide meaningful selection that will actually improve data analysis results. The approach and software reported here consider more statistical measures (factors) than existing approaches for a similar purpose. The result is a more balanced and robust sensor selection from a less than ideal sensor array. The software offers quick, flexible, optimal sensor selection and weighting for a variety of purposes without a time-consuming, iterative search by performing sensor calibrations to a known linear or nonlinear model, evaluating the individual sensor s statistics, scoring the individual sensor s overall performance, finding the best sensor array size to maximize class separation, finding optimal weights for the remaining sensor array, estimating limits of detection for the target compounds, evaluating fingerprint distance between group pairs, and finding the best event-detecting sensors.

Zhou, Hanying↗

Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

stair-step artifact↗

Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

image registration↗

SU-C-12A-05: Radiation Dose in High-Pitch Pediatric Cardiac CTA: Correlation Between Lung Dose and CTDIvol, DLP, and Size Specific Dose Estimates (SSDE)

Purpose: To investigate the radiation dose for pediatric high pitch cardiac CTA Methods: A total of 14 cases were included in this study, with mean age of 6.2 years (ranges from 2 months to 15 years). Cardiac CTA was performed using a dual-source CT system (Definition Flash, Siemens). Tube voltage (70, 80 and 100kV) was chosen based on patient weight. All patients were scanned using a high-pitch spiral mode (pitch ranges from 2.5 to 3) with tube current modulation technique (CareDose4D, Siemens). For each case, the three dimensional dose distributions were calculated using a Monte Carlo software package (IMPACT-MC, CT Image GmbH). Scanning parameters of each exam, including tube voltage, tube current, beamshaping filters, beam collimation, were defined in the Monte Carlo calculation. Tube current profile along projection angles was obtained from projection data of each tube, which included data within the over-scanning range along z direction. The volume of lungs was segmented out with CT images (3DSlicer). Lung doses of all patients were calculated and compared with CTDIvol, DLP, and SSDE. Results: The average (range) of CTDIvol, DLP and SSDE of all patients was 1.19 mGy (0.58 to 3.12mGy), 31.54 mGy*cm (12.56 to 99 mGy*cm), 2.26 mGy (1.19 to 6.24 mGy), respectively. Radiation dose to the lungs ranged from 0.83 to 4.18 mGy. Lung doses correlated with CTDIvol, DLP and SSDE with correlation coefficients(k) at 0.98, 0.93, and 0.99. However, for the cases with CTDIvol less than 1mGy, only SSDE preserved a strong correlation with lung doses (k=0.83), while much weaker correlations were found for CTDIvol (k=0.29) and DLP (k=-0.47). Conclusion: Lung doses to pediatric patients during Cardiac CTA were estimated. SSDE showed the most robust correlation with lung doses in contrast to CTDIvol and DLP.

60 APPLIED LIFE SCIENCES↗

Study of software application of airborne laser doppler system for severe storms measurement

Significant considerations are described for performing a Severe Storms Measurement program in real time. Particular emphasis is placed on the sizing and timing requirements for a minicomputer-based system. Analyses of several factors which could impact the effectiveness of the system are presented. The analyses encompass the problems of data acquisition, data storage, data registration, correlation, and flow field computation, and error induced by aircraft motion, moment estimation, and pulse integration.

Alley, P. L.↗

Image Guider Subsystem Analysis for the GHAPS Project

The Gondola for High-Altitude Planetary Science (GHAPS) project is a balloon-borne astronomical observatory designed operate in the UV, Visible, and near-mid IR spectral region. The GHAPS Optical Telescope Assembly (OTA) is designed around a one meter aperture narrow field-of-view telescope with near diffraction limited performance. GHAPS will utilize Wallops Arc-Second Pointing System (WASP) for pointing the OTA with an accuracy of 1 arc second or better. WASP relies heavily on a self-contained star tracker assembly to determine the OTA line of sight. Preliminary structural analysis indicated that potential misalignments could be present between the OTA line of sight and the star tracker FOV center during the expected flight conditions that could compromise GHAPS pointing accuracy. An analysis is presented that estimates the worst case long-term (or bias) pointing misalignments for the GHAPS opto-mechanical configuration, examines the need for additional hardware to correct pointing errors, and determines the best hardware and software implementation to do so. The analysis includes the development of a photometric model to predict the limiting magnitude of a GHAPS Facility Guide System (FGS) for a variety of image sensor technologies from visible to mid IR. FGS system performance is estimated using star magnitude and spectral data from actual star catalogs for more realistic predictions. Based on expected performance and other factors, such as size, weight, power, and cost, a final recommendation is made for the GHAPS configuration.

Telescope Guider↗

j5 v2.8.4

j5 automates and optimizes the design of the molecular biological process of cloning/constructing DNA. j5 enables users to benefit from (combinatorial) multi-part scar-less SLIC, Gibson, CPEC, Golden Gate assembly, or variants thereof, for which automation software does not currently exist, without the intense labor currently associated with the process. j5 inputs a list of the DNA sequences to be assembled, along with a Genbank, FASTA, jbei-seq, or SBOL v1.1 format sequence file for each DNA source. Given the list of DNA sequences to be assembled, j5 first determines the cost-minimizing assembly strategy for each part (direct synthesis, PCR/SOE, or oligo-embedding), designs DNA oligos with Primer3, adds flanking homology sequences (SLIC, Gibson, and CPEC; optimized with Primer3 for CPEC) or optimized overhang sequences (Golden Gate) to the oligos and direct synthesis pieces, and utilizes BLAST to check against oligo mis-priming and assembly piece incompatibility events. After identifying DNA oligos that are already contained within a local collection for reuse, the program estimates the total cost of direct synthesis and new oligos to be ordered. In the instance that j5 identifies putative assembly piece incompatibilities (multiple pieces with high flanking sequence homology), the program suggests hierarchical subassemblies where possible. The program outputs a comma-separated value (CSV) file, viewable via Excel or other spreadsheet software, that contains assembly design information (such as the PCR/SOE reactions to perform, their anticipated sizes and sequences, etc.) as well as a properly annotated genbank file containing the sequence resulting from the assembly, and appends the local oligo library with the oligos to be ordered j5 condenses multiple independent assembly projects into 96-well format for high-throughput liquid-handling robotics platforms, and generates configuration files for the PR-PR biology-friendly robot programming language. j5 thus provides a new way to design DNA assembly procedures much more productively and efficiently, not only in terms of time, but also in terms of cost. To a large extent, however, j5 does not allow people to do something that could not be done before by hand given enough time and effort. An exception to this is that, since the very act of using j5 to design the DNA assembly process standardizes the experimental details and workflow, j5 enables a single person to concurrently perform the independent DNA construction tasks of an entire group of researchers. Currently, this is not readily possible, since separate researchers employ disparate design strategies and workflows, and furthermore, their designs and workflows are very infrequently fully captured in an electronic format which is conducive to automation.

Hillson, Nathan↗

CMS Computing Resources: Meeting the demands of the high-luminosity LHC physics program

The high-luminosity program has seen numerous extrapolations of its needed computing resources that each indicate the need for substantial changes if the desired HL-LHC physics program is to be supported within the current level of computing resource budgets. Drivers include large increases in event complexity (leading to increased processing time and analysis data size) and trigger rates needed (5-10 fold increases) for the HL-LHC program. The CMS experiment has recently undertaken an effort to merge the ideas behind short-term and long-term resource models in order to make easier and more reliable extrapolations to future needs. Near term computing resource estimation requirements depend on numerous parameters: LHC uptime and beam intensities; detector and online trigger performance; software performance; analysis data requirements; data access, management, and retention policies; site characteristics; and network performance. Longer term modeling is affected by the same characteristics, but with much larger uncertainties that must be considered to understand the most interesting handles for increasing the "physics per computing dollar" of the HL-LHC. In this presentation, we discuss the current status of long term modeling of the CMS computing resource needs for HL-LHC with emphasis on techniques for extrapolations, uncertainty quantification, and model results. We illustrate potential ways that high-luminosity CMS could accomplish its desired physics program within today's computing budgets.

97 MATHEMATICS AND COMPUTING↗

Robust Distributed State Estimator for Interconnected Transmission and Distribution Networks (Final Report RPPR-1)

This project’s objective is to develop a combined transmission and distribution state estimator which accounts for very large system size and model complexity (by way of distributing the computations) and large number of solar PV units connected to the distribution system on multiple feeders. The project not only provides a robust formulation and solution to this problem but also tests the solution by implementing it on a well-established large utility system. It introduces several improvements with respect to the state of the art in existing state estimation software: (a) The developed state estimator (SE) allows robust and accurate monitoring of bidirectional flows in distribution systems which result due to the distributed energy sources which are not observable and thus not incorporated in generation dispatch; (b) Large utility systems with tens of thousands of transmission buses and hundreds of thousands of distribution nodes are difficult to model as a single integrated system. This shortcoming is addressed by developing a “scalable distributed computational framework” which allows splitting the ultra large system models into several small subsystems and coordinating their solution by a robust and practical state estimation formulation; (c) Measurement errors irrespective of their locations are detected and removed by the developed state estimator. Historically, transmission and distribution systems were analyzed and operated as two independent systems. Given the non-transposed short feeder sections, unevenly loaded phases, strictly radial configuration and unidirectional power flows in the absence of remote generation, distribution system analysis was customized to account for these characteristics. However, some of these assumptions are no longer valid (non-radial configuration, bidirectional power flows) and thus distribution system analysis should be revisited. Furthermore, in the past, the interaction between the transmission and distribution systems was quite passive, where distribution substations were modeled as lumped loads in the transmission system model. With substantial generation injected by renewable generation located in the distribution systems, such modeling will no longer be accurate. The developed state estimator facilitates proper monitoring of the interactions between the transmission and distribution systems and enables smart dispatch of these units which are made observable by the state estimator.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SU-F-T-367: Using PRIMO, a PENELOPE-Based Software, to Improve the Small Field Dosimetry of Linear Accelerators

Purpose: To calculate output correction factors for Varian Clinac 2100iX beams for seven small field detectors and use the values to determine the small field output factors for the linacs at Karolinska university hospital. Methods: Phase space files (psf) for square fields between 0.25cm and 10cm were calculated using the PENELOPE-based PRIMO software. The linac MC-model was tuned by comparing PRIMO-estimated and experimentally determined depth doses and lateral dose-profiles for 40cmx40cm fields. The calculated psf were used as radiation sources to calculate the correction factors of IBA and PTW detectors with the code penEasy/PENELOPE. Results: The optimal tuning parameters of the MClinac model in PRIMO were 5.4 MeV incident electron energy and zero energy spread, focal spot size and beam divergence. Correction factors obtained for the liquid ion chamber (PTW-T31018) are within 1% down to 0.5 cm fields. For unshielded diodes (IBA-EFD, IBA-SFD, PTW-T60017 and PTW-T60018) the corrections are up to 2% at intermediate fields (>1cm side), becoming down to −11% for fields smaller than 1cm. The shielded diode (IBA-PFD and PTW-T60016) corrections vary with field size from 0 to −4%. Volume averaging effects are found for most detectors in the presence of 0.25cm fields. Conclusion: Good agreement was found between correction factors based on PRIMO-generated psf and those from other publications. The calculated factors will be implemented in output factor measurements (using several detectors) in the clinic. PRIMO is a userfriendly general code capable of generating small field psf and can be used without having to code own linac geometries. It can therefore be used to improve the clinical dosimetry, especially in the commissioning of linear accelerators. Important dosimetry data, such as dose-profiles and output factors can be determined more accurately for a specific machine, geometry and setup by using PRIMO and having a MC-model of the detector used.

43 PARTICLE ACCELERATORS↗

Multidisciplinary Optimization Branch Experience Using iSIGHT Software

The Multidisciplinary Optimization (MDO) Branch at NASA Langley Research Center is investigating frameworks for supporting multidisciplinary analysis and optimization research. An optimization framework call improve the design process while reducing time and costs. A framework provides software and system services to integrate computational tasks and allows the researcher to concentrate more on the application and less on the programming details. A framework also provides a common working environment and a full range of optimization tools, and so increases the productivity of multidisciplinary research teams. Finally, a framework enables staff members to develop applications for use by disciplinary experts in other organizations. Since the release of version 4.0, the MDO Branch has gained experience with the iSIGHT framework developed by Engineous Software, Inc. This paper describes experiences with four aerospace applications: (1) reusable launch vehicle sizing, (2) aerospike nozzle design, (3) low-noise rotorcraft trajectories, and (4) acoustic liner design. All applications have been successfully tested using the iSIGHT framework, except for the aerospike nozzle problem, which is in progress. Brief overviews of each problem are provided. The problem descriptions include the number and type of disciplinary codes, as well as all estimate of the multidisciplinary analysis execution time. In addition, the optimization methods, objective functions, design variables, and design constraints are described for each problem. Discussions on the experience gained and lessons learned are provided for each problem. These discussions include the advantages and disadvantages of using the iSIGHT framework for each case as well as the ease of use of various advanced features. Potential areas of improvement are identified.

Padula, S. L.↗

Monte Carlo simulation based study of a proposed multileaf collimator for a telecobalt machine

Purpose: The objective of the present work was to propose a design of a secondary multileaf collimator (MLC) for a telecobalt machine and optimize its design features through Monte Carlo simulation. Methods: The proposed MLC design consists of 72 leaves (36 leaf pairs) with additional jaws perpendicular to leaf motion having the capability of shaping a maximum square field size of 35 Multiplication-Sign 35 cm{sup 2}. The projected widths at isocenter of each of the central 34 leaf pairs and 2 peripheral leaf pairs are 10 and 5 mm, respectively. The ends of the leaves and the x-jaws were optimized to obtain acceptable values of dosimetric and leakage parameters. Monte Carlo N-Particle code was used for generating beam profiles and depth dose curves and estimating the leakage radiation through the MLC. A water phantom of dimension 50 Multiplication-Sign 50 Multiplication-Sign 40 cm{sup 3} with an array of voxels (4 Multiplication-Sign 0.3 Multiplication-Sign 0.6 cm{sup 3}= 0.72 cm{sup 3}) was used for the study of dosimetric and leakage characteristics of the MLC. Output files generated for beam profiles were exported to the PTW radiation field analyzer software through locally developed software for analysis of beam profiles in order to evaluate radiation field width, beam flatness, symmetry, and beam penumbra. Results: The optimized version of the MLC can define radiation fields of up to 35 Multiplication-Sign 35 cm{sup 2} within the prescribed tolerance values of 2 mm. The flatness and symmetry were found to be well within the acceptable tolerance value of 3%. The penumbra for a 10 Multiplication-Sign 10 cm{sup 2} field size is 10.7 mm which is less than the generally acceptable value of 12 mm for a telecobalt machine. The maximum and average radiation leakage through the MLC were found to be 0.74% and 0.41% which are well below the International Electrotechnical Commission recommended tolerance values of 2% and 0.75%, respectively. The maximum leakage through the leaf ends in closed condition was observed to be 8.6% which is less than the values reported for other MLCs designed for medical linear accelerators. Conclusions: It is concluded that dosimetric parameters and the leakage radiation of the optimized secondary MLC design are well below their recommended tolerance values. The optimized design of the proposed MLC can be integrated into a telecobalt machine by replacing the existing adjustable secondary collimator for conformal radiotherapy treatment of cancer patients.

60 APPLIED LIFE SCIENCES↗

Structural Weight Estimation for Launch Vehicles

This paper describes some of the work in progress to develop automated structural weight estimation procedures within the Vehicle Analysis Branch (VAB) of the NASA Langley Research Center. One task of the VAB is to perform system studies at the conceptual and early preliminary design stages on launch vehicles and in-space transportation systems. Some examples of these studies for Earth to Orbit (ETO) systems are the Future Space Transportation System [1], Orbit On Demand Vehicle [2], Venture Star [3], and the Personnel Rescue Vehicle[4]. Structural weight calculation for launch vehicle studies can exist on several levels of fidelity. Typically historically based weight equations are used in a vehicle sizing program. Many of the studies in the vehicle analysis branch have been enhanced in terms of structural weight fraction prediction by utilizing some level of off-line structural analysis to incorporate material property, load intensity, and configuration effects which may not be captured by the historical weight equations. Modification of Mass Estimating Relationships (MER's) to assess design and technology impacts on vehicle performance are necessary to prioritize design and technology development decisions. Modern CAD/CAE software, ever increasing computational power and platform independent computer programming languages such as JAVA provide new means to create greater depth of analysis tools which can be included into the conceptual design phase of launch vehicle development. Commercial framework computing environments provide easy to program techniques which coordinate and implement the flow of data in a distributed heterogeneous computing environment. It is the intent of this paper to present a process in development at NASA LaRC for enhanced structural weight estimation using this state of the art computational power.

Cerro, Jeff↗

Flight and Direct to Earth/Space Relay Communication System Architecture for GSFC CubeSat Missions

The CubeSat platform is finding increasing use in space science applications due to its low cost and comparative ease of launch. It is becoming a key scientific discovery tool in low Earth orbit (LEO) and beyond, including geosynchronous equatorial orbit (GEO), the Lagrange Points, Lunar missions, and more. The increasing complexity of these missions and their scientific goals must be supported by equal advancements in communications technology. Higher data rates and greater reliability are required every year. However, the reduced Size, Weight, and Power (SWaP) constraints of CubeSat platforms introduce unique challenges in the area of satellite communications. There is currently a lack of communication equipment tailored specifically to the CubeSat platform. This lack of standardized, tested equipment extends development time and reduces mission confidence. Furthermore, missions utilizing the CubeSat platform are often subject to more difficult design constraints. Antenna placement, size, and pointing are often subordinate to the requirements of the payload instruments and mission goals. Traditional link margin estimation techniques are insufficient in these cases, as they emphasize worst case scenarios. In reality the actual link parameters may vary widely even during a single pass. This presents new challenges in predicting communications performance and scheduling ground station contacts, but also new opportunities for improving efficiency. This paper presents the integration, testing, and validation process for a new software defined radio (SDR) designed for the CubeSat platform in conjunction with Vulcan Wireless, Inc. The SDR is planned for use on 5 upcoming CubeSat missions at NASAs Goddard Space Flight Center (GSFC) including a Geosynchronous Transfer Orbit (GTO) mission and it may also serve as a standard and well-tested option for future missions by enabling a standardized, rapid and low cost CubeSat communication system network integration process. Detailed simulations have been developed to estimate the communication performance of these missions, taking the unique antenna placements and attitude behavior of each satellite into account. These simulations allow a much more accurate analysis of the expected link margin, which varies considerably during each pass for the NASA Space Relay (SR) and Direct to Earth (DTE) network. The modelling procedures are outlined, and the results are used to predict communications performance of the missions.

Space Networks↗