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At least 1,153 records · Page 64

SU-E-I-04: Improving CT Quality for Radiation Therapy of Patients with High Body Mass Index Using Iterative Reconstruction Algorithms

Purpose: Iterative reconstruction (IR) algorithms are developed to improve CT image quality (IQ) by reducing noise without diminishing spatial resolution or contrast. The CT IQ for patients with a high Body Mass Index (BMI) can suffer from increased noise due to photon starvation. The purpose of this study is to investigate and to quantify the IQ enhancement for high BMI patients through the application of IR algorithms. Methods: CT raw data collected for 6 radiotherapy (RT) patients with BMI, greater than or equal to 30 were retrospectively analyzed. All CT data were acquired using a CT scanner (Somaton Definition AS Open, Siemens) installed in a linac room (CT-on-rails) using standard imaging protocols. The CT data were reconstructed using the Sinogram Affirmed Iterative Reconstruction (SAFIRE) and Filtered Back Projection (FBP) methods. IQ metrics of the obtained CTs were compared and correlated with patient depth and BMI. The patient depth was defined as the largest distance from anterior to posterior along the bilateral symmetry axis. Results: IR techniques are demonstrated to preserve contrast and reduce noise in comparison to traditional FBP. Driven by the reduction in noise, the contrast to noise ratio is roughly doubled by adopting the highest SAFIRE strength. A significant correlation was observed between patient depth and IR noise reduction through Pearson’s correlation test (R = 0.9429/P = 0.0167). The mean patient depth was 30.4 cm and the average relative noise reduction for the strongest iterative reconstruction was 55%. Conclusion: The IR techniques produce a measureable enhancement to CT IQ by reducing the noise. Dramatic noise reduction is evident for the high BMI patients. The improved CT IQ enables more accurate delineation of tumors and organs at risk and more accuarte dose calculations for RT planning and delivery guidance. Supported by Siemens.

60 APPLIED LIFE SCIENCES↗

Minimizing treatment planning errors in proton therapy using failure mode and effects analysis

Purpose: Failure mode and effects analysis (FMEA) is a widely used tool to evaluate safety or reliability in conventional photon radiation therapy. However, reports about FMEA application in proton therapy are scarce. The purpose of this study is to apply FMEA in safety improvement of proton treatment planning at their center. Methods: The authors performed an FMEA analysis of their proton therapy treatment planning process using uniform scanning proton beams. The authors identified possible failure modes in various planning processes, including image fusion, contouring, beam arrangement, dose calculation, plan export, documents, billing, and so on. For each error, the authors estimated the frequency of occurrence, the likelihood of being undetected, and the severity of the error if it went undetected and calculated the risk priority number (RPN). The FMEA results were used to design their quality management program. In addition, the authors created a database to track the identified dosimetric errors. Periodically, the authors reevaluated the risk of errors by reviewing the internal error database and improved their quality assurance program as needed. Results: In total, the authors identified over 36 possible treatment planning related failure modes and estimated the associated occurrence, detectability, and severity to calculate the overall risk priority number. Based on the FMEA, the authors implemented various safety improvement procedures into their practice, such as education, peer review, and automatic check tools. The ongoing error tracking database provided realistic data on the frequency of occurrence with which to reevaluate the RPNs for various failure modes. Conclusions: The FMEA technique provides a systematic method for identifying and evaluating potential errors in proton treatment planning before they result in an error in patient dose delivery. The application of FMEA framework and the implementation of an ongoing error tracking system at their clinic have proven to be useful in error reduction in proton treatment planning, thus improving the effectiveness and safety of proton therapy.

60 APPLIED LIFE SCIENCES↗

Reducing Southern Ocean Shortwave Radiation Errors in the ERA5 Reanalysis with Machine Learning and 25 Years of Surface Observations

Earth system models struggle to simulate clouds and their radiative effects over the Southern Ocean, partly due to a lack of measurements and targeted cloud microphysics knowledge. We have evaluated biases of downwelling shortwave radiation in the ERA5 climate reanalysis using 25 years (1995–2019) of summertime surface measurements, collected on the Research and Supply Vessel (RSV) Aurora Australis, the Research Vessel (R/V) Investigator, and at Macquarie Island. During October–March daylight hours, the ERA5 simulation of SW down exhibited large errors (mean bias = 54 W m -2 , mean absolute error = 82 W m -2 , root-mean-square error = 132 W m -2 , and R 2 = 0.71). To determine whether we could improve these statistics, we bypassed ERA5’s radiative transfer model for SW down with machine learning–based models using a number of ERA5’s gridscale meteorological variables as predictors. These models were trained and tested with the surface measurements of SW down using a 10-fold shuffle split. An extreme gradient boosting (XGBoost) and a random forest–based model setup had the best performance relative to ERA5, both with a near complete reduction of the mean bias error, a decrease in the mean absolute error and root-mean-square error by 25% ± 3%, and an increase in the R 2 value of 5% ± 1% over the 10 splits. Large improvements occurred at higher latitudes and cyclone cold sectors, where ERA5 performed most poorly. We further interpret our methods using Shapley additive explanations. Our results indicate that data-driven techniques could have an important role in simulating surface radiation fluxes and in improving reanalysis products.

54 ENVIRONMENTAL SCIENCES↗

A Data-Driven Framework for Direct Local Tensile Property Prediction of Laser Powder Bed Fusion Parts

This article proposes a generalizable, data-driven framework for qualifying laser powder bed fusion additively manufactured parts using part-specific in situ data, including powder bed imaging, machine health sensors, and laser scan paths. To achieve part qualification without relying solely on statistical processes or feedstock control, a sequence of machine learning models was trained on 6299 tensile specimens to locally predict the tensile properties of stainless-steel parts based on fused multi-modal in situ sensor data and a priori information. A cyberphysical infrastructure enabled the robust spatial tracking of individual specimens, and computer vision techniques registered the ground truth tensile measurements to the in situ data. The co-registered 230 GB dataset used in this work has been publicly released and is available as a set of HDF5 files. The extensive training data requirements and wide range of size scales were addressed by combining deep learning, machine learning, and feature engineering algorithms in a relay. The trained models demonstrated a 61% error reduction in ultimate tensile strength predictions relative to estimates made without any in situ information. Lessons learned and potential improvements to the sensors and mechanical testing procedure are discussed.

36 MATERIALS SCIENCE↗

A demonstration of dual spacecraft tracking conducted with the Viking spacecraft during the approach phase

The potential improvements in navigation capability of dual spacecraft tracking were demonstrated using Viking approach data. Under unfavorable conditions of large plasma noise, low spacecraft declination and large earth-spacecraft distance, the dual spacecraft tracking technique improved the Viking B approach accuracy based on short-arc radio metric data, by a factor of 7, to less than 200 km at Mars orbit insertion minus 3 days. From the results of an analytical expansion and the Viking demonstration with a large intentional error in Mars ephemeris, that dual spacecraft data types are shown to be insensitive to ephemeris error. Results also reveal the potential reduction of tracking time requirements during planet approach.

Chao, C. C.↗

Fourier domain target transformation analysis in the thermal infrared

Remote sensing uses of principal component analysis (PCA) of multispectral images include band selection and optimal color selection for display of information content. PCA has also been used for quantitative determination of mineral types and abundances given end member spectra. The preliminary results of the investigation of target transformation PCA (TTPCA) in the fourier domain to both identify end member spectra in an unknown spectrum, and to then calculate the relative concentrations of these selected end members are presented. Identification of endmember spectra in an unknown sample has previously been performed through bandmatching, expert systems, and binary classifiers. Both bandmatching and expert system techniques require the analyst to select bands or combinations of bands unique to each endmember. Thermal infrared mineral spectra have broad spectral features which vary subtly with composition. This makes identification of unique features difficult. Alternatively, whole spectra can be used in the classification process, in which case there is not need for an expert to identify unique spectra. Use of binary classifiers on whole spectra to identify endmember components has met with some success. These techniques can be used, along with a least squares fit approach on the endmembers identified, to derive compositional information. An alternative to the approach outlined above usese target transformation in conjunction with PCA to both identify and quantify the composition of unknown spectra. Preprocessing of the library and unknown spectra into the fourier domain, and using only a specific number of the components, allows for significant data volume reduction while maintaining a linear relationship in a Beer's Law sense. The approach taken here is to iteratively calculate concentrations, reducing the number of endmember components until only non-negative concentrations remain.

Anderson, D. L.↗

Bulk Current Injection Testing of Cable Noise Reduction Techniques, 50 kHz to 400 MHz

This paper presents empirical results of cable noise reduction techniques as demonstrated using bulk current injection (BCI) techniques with radiated fields from 50 kHz - 400 MHz. It is a follow up to the two-part paper series presented at the Asia Pacific EMC Conference that focused on TEM cell signal injection. This paper discusses the effects of cable types, shield connections, and chassis connections on cable noise. For each topic, well established theories are compared with data from a real-world physical system.

Bradley, Arthur T.↗

Fault-Tolerant, Radiation-Hard DSP

Commercial digital signal processors (DSPs) for use in high-speed satellite computers are challenged by the damaging effects of space radiation, mainly single event upsets (SEUs) and single event functional interrupts (SEFIs). Innovations have been developed for mitigating the effects of SEUs and SEFIs, enabling the use of very-highspeed commercial DSPs with improved SEU tolerances. Time-triple modular redundancy (TTMR) is a method of applying traditional triple modular redundancy on a single processor, exploiting the VLIW (very long instruction word) class of parallel processors. TTMR improves SEU rates substantially. SEFIs are solved by a SEFI-hardened core circuit, external to the microprocessor. It monitors the health of the processor, and if a SEFI occurs, forces the processor to return to performance through a series of escalating events. TTMR and hardened-core solutions were developed for both DSPs and reconfigurable field-programmable gate arrays (FPGAs). This includes advancement of TTMR algorithms for DSPs and reconfigurable FPGAs, plus a rad-hard, hardened-core integrated circuit that services both the DSP and FPGA. Additionally, a combined DSP and FPGA board architecture was fully developed into a rad-hard engineering product. This technology enables use of commercial off-the-shelf (COTS) DSPs in computers for satellite and other space applications, allowing rapid deployment at a much lower cost. Traditional rad-hard space computers are very expensive and typically have long lead times. These computers are either based on traditional rad-hard processors, which have extremely low computational performance, or triple modular redundant (TMR) FPGA arrays, which suffer from power and complexity issues. Even more frustrating is that the TMR arrays of FPGAs require a fixed, external rad-hard voting element, thereby causing them to lose much of their reconfiguration capability and in some cases significant speed reduction. The benefits of COTS high-performance signal processing include significant increase in onboard science data processing, enabling orders of magnitude reduction in required communication bandwidth for science data return, orders of magnitude improvement in onboard mission planning and critical decision making, and the ability to rapidly respond to changing mission environments, thus enabling opportunistic science and orders of magnitude reduction in the cost of mission operations through reduction of required staff. Additional benefits of COTS-based, high-performance signal processing include the ability to leverage considerable commercial and academic investments in advanced computing tools, techniques, and infra structure, and the familiarity of the science and IT community with these computing environments.

Czajkowski, David↗

Approach for Structurally Clearing an Adaptive Compliant Trailing Edge Flap for Flight

The Adaptive Compliant Trailing Edge (ACTE) flap was flown on the National Aeronautics and Space Administration (NASA) Gulfstream GIII testbed at the NASA Armstrong Flight Research Center. This smoothly curving flap replaced the existing Fowler flaps creating a seamless control surface. This compliant structure, developed by FlexSys Inc. in partnership with the Air Force Research Laboratory, supported NASA objectives for airframe structural noise reduction, aerodynamic efficiency, and wing weight reduction through gust load alleviation. A thorough structures airworthiness approach was developed to move this project safely to flight. A combination of industry and NASA standard practice require various structural analyses, ground testing, and health monitoring techniques for showing an airworthy structure. This paper provides an overview of compliant structures design, the structural ground testing leading up to flight, and the flight envelope expansion and monitoring strategy. Flight data will be presented, and lessons learned along the way will be highlighted.

flight test↗

A co-kurtosis PCA based dimensionality reduction with nonlinear reconstruction using neural networks

For turbulent reacting flow systems, identification of low-dimensional representations of the thermo-chemical state space is vitally important, primarily to significantly reduce the computational cost of device-scale simulations. Principal component analysis (PCA), and its variants, are a widely employed class of methods. Recently, an alternative technique that focuses on higher-order statistical interactions, co-kurtosis PCA (CoK-PCA), has been shown to effectively provide a low-dimensional representation by capturing the stiff chemical dynamics associated with spatiotemporally localized reaction zones. While its effectiveness has only been demonstrated based on a priori analyses with linear reconstruction, in this work, we employ nonlinear techniques to reconstruct the full thermo-chemical state and evaluate the efficacy of CoK-PCA compared to PCA. Specifically, we combine a CoK-PCA-/PCA-based dimensionality reduction (encoding) with an artificial neural network (ANN) based reconstruction (decoding) and examine, a priori, the reconstruction errors of the thermo-chemical state. In addition, we evaluate the errors in species production rates and heat release rates, which are nonlinear functions of the reconstructed state, as a measure of the overall accuracy of the dimensionality reduction technique. We employ four datasets to assess CoK-PCA/PCA coupled with ANN-based reconstruction: zero-dimensional (homogeneous) reactor for autoignition of an ethylene/air mixture that has conventional single-stage ignition kinetics, a dimethyl ether (DME)/air mixture which has two-stage (low and high temperature) ignition kinetics, a one-dimensional freely propagating premixed ethylene/air laminar flame, and a two-dimensional dataset representing turbulent autoignition of ethanol in a homogeneous charge compression ignition (HCCI) engine. Finally, results from the analyses demonstrate the robustness of the CoK-PCA based low-dimensional manifold with ANN reconstruction in accurately capturing the data, specifically from the reaction zones.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fourier method for 3-dimensional data fusion of X-ray Computed Tomography and ultrasound

X-ray Computed Tomography (CT) is essential for nondestructive inspection of many manufactured components but is susceptible to various forms of artifacts and noise. In particular, multi-detector row cone-beam CT systems can suffer from so called “cone-beam” artifacts and partial volume effects, particularly on planar edges at the periphery of the field of view in the cone angle dimension. Uni-directional ultrasonic testing methods generally have extremely accurate in-plane depth resolution but poorer lateral resolution due to physical and geometric constraints. This paper presents a novel technique called Computed Tomographic Fusion (CT-F) which uses three-dimensional Fourier filtering to combine x-ray cone-beam CT reconstructions and ultrasound data in the frequency space. The result is a single image with improved accuracy and quality. CT-F mitigates artifacts while allowing for rapid, accurate characterization of large three-dimensional CT volumes. Finally, using simulations and experiments, we demonstrate artifact reduction and edge contrast improvement in volumetric reconstructions.

42 ENGINEERING↗

In-pixel AI for lossy data compression at source for X-ray detectors

Integrating neural networks for data compression directly in the Read-Out Integrated Circuits (ROICs), i.e. the pixelated front-end, would result in a significant reduction in off-chip data transfer, overcoming the I/O bottleneck. Our ROIC test chip (AI-In-Pixel-65) is designed in a 65 nm Low Power CMOS process for the readout of pixelated X-ray detectors. Each pixel consists of an analog front-end for signal processing and a 10b analog-to-digital converter operating at 100KSPS. Here, we compare two non-reconfigurable techniques, Principal Component Analysis (PCA) and an AutoEncoder (AE) as lossy data compression engines implemented within the pixelated area. The PCA algorithm achieves 50$×$ compression, adds one clock cycle latency, and results in a 21% increase in the pixel area. The AE achieves 70$×$ compression, adds 30 clock cycle latency, and results in a similar area increase.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Delamination growth in composite materials

The Double Cantilever Beam (DCB) and the End Notched Flexure (ENF) specimens are employed to characterize MODE I and MODE II interlaminar fracture resistance of graphite/epoxy (CYCOM 982) and graphite/PEEK (APC2) composites. Sizing of test specimen geometries to achieve crack growth in the linear elastic regime is presented. Data reduction schemes based upon beam theory are derived for the ENF specimen and include the effects of shear deformation and friction between crack surfaces on compliance, C, and strain energy release rate, G sub II. Finite element (FE) analyses of the ENF geometry including the contact problem with friction are presented to assess the accuracy of beam theory expressions for C and G sub II. Virtual crack closure techniques verify that the ENF specimen is a pure Mode II test. Beam theory expressions are shown to be conservative by 20 to 40 percent for typical unidirectional test specimen geometries. A FE parametric study investigating the influence of delamination length and depth, span, thickness and material properties on G sub II is presented. Mode I and II interlaminar fracture test results are presented. Important experimental parameters are isolated, such as precracking techniques, rate effects, and nonlinear load-deflection response. It is found that subcritical crack growth and inelastic materials behavior, responsible for the observed nonlinearities, are highly rate-dependent phenomena with high rates generally leading to linear elastic response.

Gillespie, J. W., Jr.↗

Results of wind simulations in the mesosphere using precision C-band radars and the inflatable falling sphere technique

The inflatable sphere technique represents a relatively inexpensive approach for obtaining density and wind data between 30 and 90 km. The procedure in its current form is adequate for operational rocket network type application. However, detailed information is lost because of oversmoothing. The present study had the objective to determine whether more detailed wind profiles could be obtained using the inflatable falling sphere and Hirobin. Hirobin is the name for the sphere reduction program used at NASA Wallops Island, VA. In connection with the aim of the study, information had to be obtained regarding the precision of the radar used to track the sphere. For this purpose, data from three C-band radars, each with a different tracking precision, were simulated. On the basis of the results of the investigation, it is concluded that, given a radar with a known precision and a perfectly performing sphere, the Hirobin filters can be adjusted to provide small-scale wind information to about 70 km.

Schmidlin, F. J.↗

Translating Phased Array Measurements of a Low-Noise Top-Mounted Propulsion Installation for a Supersonic Airliner

A novel translating-phased-array technique was applied during a model-scale validation test of low-noise propulsion concepts for supersonic transport aircraft. The test involved particle image velocimetry, far field and translating phased array acoustic measurements. This paper covers the translating phased array portion. Data were acquired for a series of nozzles with different chevron designs, both uninstalled and installed on a representative aircraft planform. The far field data confirmed the noise reduction potential of top-mounted installation, while the phased array results gave insights into how the reduction occurred and highlighted areas for improvement. This was the inaugural test for the new translating phased array, which measures source maps as seen by observers at different polar angles. Propagation effects through the free jet were documented for the different viewing angles. The source maps obtained were used to understand important aspects of the far field noise measurements.

Beamforming↗

Thermodynamics of Minerals Stable near Earth's Surface

Project “Thermodynamics of Minerals Stable Near the Earth’s Surface” uses specialized calorimetric techniques to obtain new thermochemical data for solid phases of interest in the Earth’s “critical zone”, the near surface regions of the planet most directly affecting and affected by human activity. Major activity was in three areas: manganese oxide materials, aluminum clusters which are precursors to aluminum oxyhydroxide precipitates, and zeolites. All these classes of minerals are potential carriers of heavy metals and radionuclides in the environment, both within their crystal structures and as adsorbed layers or colloids. Their thermodynamic stability, as well as the sequence of stability of competing phases, governs the aqueous solubility of contaminants (and nutrients) in soil, groundwater, and sediments. The thermodynamics of these phases is strongly affected by particle size and crystallinity, since they often occur as very fine particles which do not coarsen in the near-surface environment. Many of these materials exhibit extensive polymorphism, multicomponent solid solution, and variable hydration states. Thus, one must define and systematize important thermodynamic variables, since one cannot make measurements on each and every possible phase, particle size, and composition. A major finding of the work on manganese oxides was labile water-induced oxidation-reduction reactions. These will be studied further by a combination of thermodynamic and synchrotron-based spectroscopic methods, the latter in collaboration with Peggy O’Day at UC Merced. The adsorption of other species, including simple organics, on such redox-active surfaces will also be investigated by a combination of thermochemical and spectroscopic studies. Studies of the energetics of water adsorption on mineral surfaces will be expanded to emphasize the adsorption of CO2 and small organic molecules, relevant to soil, groundwater, and the subsurface environment. Gas adsorption calorimetry, immersion calorimetry, and solution calorimetry will be combined with appropriate analytical and spectroscopic techniques to obtain a comprehensive picture of the interactions and their energetics. The evolution of aqueous aluminum clusters to form aluminum oxyhydroxide precipitates will be studied in detail by a combination of calorimetric and structural methods applied to aqueous samples aged at room temperature. The energetics of new classes of clusters will be explored. The project addresses several common themes relevant to the broad mission of the Department of Energy. Thermochemical data for minerals stable near the Earth’s surface, though still incomplete, are essential for understanding both natural and anthropogenic processes that affect our very existence on this planet. Such data contribute to the fundamental underpinning for mitigation and management strategies for the extraction and use of energy. Fundamental thermodynamic and mechanistic understanding is required to model processes ranging from heavy metal pollution to nuclear waste disposal to climate change.

58 GEOSCIENCES↗

Efficient boundary-guided scanning for high-resolution X-ray ptychography

In the realm of X-ray ptychography experiments, a considerable amount of ptychography scans are typically performed within a field of view encompassing the target sample. While it is crucial to obtain overlapping scans in small increments over the region of interest for achieving high-resolution sample reconstruction, a significant number of these scans often redundantly measure the empty background within the wide field of view. To address this inefficiency, an innovative algorithm is proposed that introduces automatic guidance for data acquisition. The algorithm first directs the scan point to actively search for the object of interest within the field of view. Subsequently, it intelligently scans along the perimeter of the sample, strategically acquiring measurements exclusively within the boundary of the region of interest. By employing this approach, a reduction in the number of measurements required to obtain high-resolution reconstruction images is demonstrated, as compared with conventional raster scanning methods. Furthermore, the automatic guidance provided by the algorithm offers the added advantage of saving valuable time during the reconstruction process. Through practical implementation on real experiments, these findings showcase the efficacy of the proposed algorithm in enhancing the efficiency and accuracy of X-ray ptychography experiments. This novel approach holds immense potential for advancing sample analysis and imaging techniques in various scientific disciplines.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗