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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 NTRS2000

Discriminability measures for predicting readability of text on textured backgrounds

Several discriminability measures were examined for their ability to predict reading search times for three levels of text contrast and a range of backgrounds (plain, a periodic texture, and four spatial-frequency-filtered textures created from the periodic texture). Search times indicate that these background variations only affect readability when the text contrast is low, and that spatial frequency content of the background affects readability. These results were not well predicted by the single variables of text contrast (Spearman rank correlation = -0.64) and background RMS contrast (0.08), but a global masking index and a spatial-frequency-selective masking index led to better predictions (-0.84 and -0.81, respectively). c2000 Optical Society of America.

NASA Discipline Space Human Factors↗
NASA NTRS2006

Multiphysics Thermal-Fluid Design Analysis of a Non-Nuclear Tester for Hot-Hydrogen Materials and Component Development

The objective of this effort is to perform design analyses for a non-nuclear hot-hydrogen materials tester, as a first step towards developing efficient and accurate multiphysics, thermo-fluid computational methodology to predict environments for hypothetical solid-core, nuclear thermal engine thrust chamber design and analysis. The computational methodology is based on a multidimensional, finite-volume, turbulent, chemically reacting, thermally radiating, unstructured-grid, and pressure-based formulation. The multiphysics invoked in this study include hydrogen dissociation kinetics and thermodynamics, turbulent flow, convective, and thermal radiative heat transfers. The goals of the design analyses are to maintain maximum hot-hydrogen jet impingement energy and to minimize chamber wall heating. The results of analyses on three test fixture configurations and the rationale for final selection are presented. The interrogation of physics revealed that reactions of hydrogen dissociation and recombination are highly correlated with local temperature and are necessary for accurate prediction of the hot-hydrogen jet temperature.

Wang, Ten-See↗
NASA NTRS2010

An Analysis of Rocket Propulsion Testing Costs

The primary mission at NASA Stennis Space Center (SSC) is rocket propulsion testing. Such testing is commonly characterized as one of two types: production testing for certification and acceptance of engine hardware, and developmental testing for prototype evaluation or research and development (R&D) purposes. For programmatic reasons there is a continuing need to assess and evaluate the test costs for the various types of test campaigns that involve liquid rocket propellant test articles. Presently, in fact, there is a critical need to provide guidance on what represents a best value for testing and provide some key economic insights for decision-makers within NASA and the test customers outside the Agency. Hence, selected rocket propulsion test databases and references have been evaluated and analyzed with the intent to discover correlations of technical information and test costs that could help produce more reliable and accurate cost projections in the future. The process of searching, collecting, and validating propulsion test cost information presented some unique obstacles which then led to a set of recommendations for improvement in order to facilitate future cost information gathering and analysis. In summary, this historical account and evaluation of rocket propulsion test cost information will enhance understanding of the various kinds of project cost information; identify certain trends of interest to the aerospace testing community.

Ramirez, Carmen↗
NASA NTRS2012

Comparative Study of Aerosol and Cloud Detected by CALIPSO and OMI

The Ozone Monitoring Instrument (OMI) on the Aura Satellite detects the presence of desert dust and smoke particles (also known as aerosols) in terms of a parameter known as the UV Aerosol Index (UV AI). The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission measures the vertical distribution of aerosols and clouds. Aerosols and clouds play important roles in the atmosphere and climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a very important task. This paper presents a comparative analysis of the CALIPSO Version 2 Vertical Feature Mask (VFM) product with the (OMI) UV Aerosol Index (UV AI) and reflectivity datasets for a full year of 2007. The comparison is done at regional and global scales. Based on CALIPSO arid OMI observations, the vertical and horizontal extent of clouds and aerosols are determined and the effects of aerosol type selection, load, cloud fraction on aerosol identification are discussed. It was found that the spatial-temporal correlation found between CALIPSO and OMI observations, is strongly dependent on aerosol types and cloud contamination. CALIPSO is more sensitivity to cloud and often misidentifies desert dust aerosols as cloud, while some small scale aerosol layers as well as some pollution aerosols are unidentified by OMI UV AI. Large differences in aerosol distribution patterns between CALIPSO and OMI are observed, especially for the smoke and pollution aerosol dominated areas. In addition, the results found a significant correlation between CALIPSO lidar 1064 nm backscatter and the OMI UV AI over the study regions.

Chen, Zhong↗
NASA NTRS2018

Digital Image Correlation Data Processing and Analysis Techniques to Enhance Test Data Assessment and Improve Structural Simulations

The NASA Shell Buckling Knockdown Factor Project (SBKF) was established in 2007 by the NASA Engineering and Safety Center (NESC) with the primary goal to develop new analysis-based buckling design factors (a.k.a. knockdown factors) and high-fidelity buckling simulations for selected launch-vehicle-like cylindrical shell structures. A series of tests are being conducted on large-scale metallic and composite cylindrical shells in order to provide validation data for these new factors and simulations. However, the validation of these new factors and simulations is quite demanding and requires test data that is commensurate with their fidelity. Traditional instrumentation, such as linear variable displacement transducers (LVDTs) and electrical-resistance strain gages serve a critical role in providing accurate displacement and strain measurements in these tests, but only allow for data to be recorded at a select number of point locations and are not sufficient to provide all the necessary validation data. Advanced measurement technologies can be used effectively to complement traditional instrumentation and gather additional data required to validate these structural simulations. In particular, three-dimensional digital image correlation (DIC) was implemented during SBKF cylinder testing to characterize the full-field displacement and strain behavior. Commercially available VIC-3DTM software and user-written data processing scripts were used to generate valuable data and insight into the complex buckling response of the cylinders that otherwise would be impossible to gather using traditional instrumentation. In addition, the measured data from DIC was used to verify measured test data obtained from other instrumentation, enhance test and analysis correlation, and help identify the root cause of anomalous test results that may have gone unexplained if only traditional instrumentation was used. Selected test results that demonstrate the use of DIC on the SBKF cylinders are presented and a portion of the data processing methods are described.

Gardner, Nathaniel W.↗
DOE OSTI2016

SDSS-IV eBOSS emission-line galaxy pilot survey

The Sloan Digital Sky Survey IV extended Baryonic Oscillation Spectroscopic Survey (SDSS-IV/eBOSS) will observe 195,000 emission-line galaxies (ELGs) to measure the Baryonic Acoustic Oscillation standard ruler (BAO) at redshift 0.9. To test different ELG selection algorithms, 9,000 spectra were observed with the SDSS spectrograph as a pilot survey based on data from several imaging surveys. First, using visual inspection and redshift quality flags, we show that the automated spectroscopic redshifts assigned by the pipeline meet the quality requirements for a reliable BAO measurement. We also show the correlations between sky emission, signal-to-noise ratio in the emission lines, and redshift error. Then we provide a detailed description of each target selection algorithm we tested and compare them with the requirements of the eBOSS experiment. As a result, we provide reliable redshift distributions for the different target selection schemes we tested. Lastly, we determine an target selection algorithms that is best suited to be applied on DECam photometry because they fulfill the eBOSS survey efficiency requirements.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1986

Intercomparison of preliminary Earth Radiation Budget Satellite (ERBS) flux estimates and geostationary satellite multi-spectral 'VAS' radiance measurements

Results are reported from a preliminary study to evaluate the level of correlation and, if possible, establish relationships between the spectral radiances sensed by the GOES 6 satellite VISSR Atmospheric Sounder (VAS) and the ERBS longwave sensor. A data set for February 7, 1985 was selected which was scanned with both sensors flying over the region of the Gulf of Mexico. Techniques applied to enhance the equivalence of the data are delineated. Regression equations were applied to assess the levels of correlations for each subsatellite point compared.

Herman, L. D.↗
NASA NTRSDate not supplied

Performance Assessment of LunaNet’s Augmented Forward Signal

LunaNet provides a common set of interoperable specifications for communication and position, navigation and time (PNT) services and interfaces soon to be implemented in lunar vicinity. The LunaNet Interoperability Specification (LNIS) provides the design for the GNSS-like Augmented Forward Signal (AFS), which enables orbiting and surface users in lunar space, such as Artemis, to estimate their position, velocity, and time. The specification of AFS defines two orthogonal signal components on a single carrier: the in-phase component (AFS-I), a lower-chip-rate data channel tailored for applications where low SWaP (Size, Weight, and Power) is critical (e.g., IoT devices or search and rescue), and the quadrature component (AFS-Q), a high-chip-rate data-less pilot signal for high-precision, robust lunar navigation and positioning applications. An initial description of AFS was provided in [1], with initial analysis results shown in [2] and [3] and the current signal in space description provided in [4]. As part of NASA's Lunar Communication Relay and Navigation Systems (LCRNS) project, this work expands upon the initial analysis results and proposes a new expanded set of AFS-Q spreading codes that exceed the cross-correlation and autocorrelation sidelobe performance of L1C and other GNSS signals, while providing additional expansion capabilities for future provider satellites. A set of 420 codes was selected from a Weil-based code derived from the prime number 10247, which is larger than the 10243 prime number used to derive Beidou’s B1C Weil sequences. Both the initial set of 210 codes and the expanded set of 420 codes are shown to provide the best cross-correlation of any 10230-chip satellite navigation codes. The performance is demonstrated for hierarchical sets of spreading codes optimized and organized in sets of 30 codes. The new codes were developed using an optimization approach and correlation methodology described in [5]. The work also compares LunaNet’s AFS to terrestrial GNSS signals in terms of acquisition, tracking, and data demodulation performance. Performance is evaluated for receivers that only track the 1.023 MCPS data channel spreading code for low SWaP IoT use cases, as well as for receivers that track both the 1.023 MCPS data channel and the 5.115 MCPS pilot channel spreading code for high-performance use cases. Performance is assessed in the presence of interference and thermal noise. The analysis is performed in terms of expected operating conditions on the lunar surface. Several unique flexibility aspects of the augmented forward signal are described, including the use of the Q channel’s secondary and tertiary codes to enable variable coherent integrations during acquisition. This is compared to GNSS signals such as L5/E5 and MBOC in terms of achievable processing gain for interference mitigation versus acquisition complexity. The work details acquisition and tracking techniques used to optimally acquire and track the primary, secondary, and tertiary codes on the Q channel, as well as acquisition of the I channel spreading code. Acquisition of the 8 ms Q channel spreading code is also compared to joint acquisition of the I and Q channel primary codes in noise and interference environments.

LCRNS↗
NASA NTRSDate not supplied

Performance Assessment of LunaNet’s Augmented Forward Signal

LunaNet provides a common set of interoperable specifications for communication and position, navigation and time (PNT) services and interfaces soon to be implemented in lunar vicinity. The LunaNet Interoperability Specification (LNIS) provides the design for the GNSS-like Augmented Forward Signal (AFS), which enables orbiting and surface users in lunar space, such as Artemis, to estimate their position, velocity, and time. The specification of AFS defines two orthogonal signal components on a single carrier: the in-phase component (AFS-I), a lower-chip-rate data channel tailored for applications where low SWaP (Size, Weight, and Power) is critical (e.g., IoT devices or search and rescue), and the quadrature component (AFS-Q), a high-chip-rate data-less pilot signal for high-precision, robust lunar navigation and positioning applications. An initial description of AFS was provided in LNIS 2023, with initial analysis results shown in Dafesh 2024 and Dafesh 2025, and the current signal in space description provided in LNIS 2025. As part of NASA's Lunar Communication Relay and Navigation Systems (LCRNS) project, this work expands upon the initial analysis results and proposes a new expanded set of AFS-Q spreading codes that exceed the cross-correlation and autocorrelation sidelobe performance of L1C and other GNSS signals, while providing additional expansion capabilities for future service satellites. A set of 420 codes was selected from a Weil-based code derived from the prime number 10247, which is larger than the 10243 prime number used to derive BeiDou’s B1C Weil sequences. Both the initial set of 210 codes and the expanded set of 420 codes are shown to provide the best cross-correlation of any 10230-chip satellite navigation codes. The performance is demonstrated for hierarchical sets of spreading codes optimized and organized in sets of 30 codes. The work also compares LunaNet’s AFS to terrestrial GNSS signals in terms of acquisition, tracking, and data demodulation performance. Performance is evaluated for receivers that only track the 1.023 MCPS data channel spreading code for low SWaP IoT use cases, as well as for receivers that track both the 1.023 MCPS data channel and the 5.115 MCPS pilot channel spreading code for high-performance use cases. Performance is assessed in the presence of interference and thermal noise. The analysis is performed in terms of expected operating conditions on the lunar surface. Several unique flexibility aspects of the augmented forward signal are described, including the use of the Q channel’s secondary and tertiary codes to enable variable coherent integrations during acquisition. This is compared to GNSS signals such as L5/E5 and MBOC in terms of achievable processing gain for interference mitigation versus acquisition complexity. The work details acquisition and tracking techniques used to optimally acquire and track the primary, secondary, and tertiary codes on the Q channel, as well as acquisition of the I channel spreading code. Acquisition of the 8 ms, Q channel spreading code is also compared to joint acquisition of the I and Q channel primary codes in noise and interference environments

LCRNS↗
DOE OSTI2023

Mass Dependence of Galaxy–Halo Alignment in LOWZ and CMASS

We measure the galaxy-ellipticity (GI) correlations for the Sloan Digital Sky Survey Data Release 12 LOWZ and CMASS samples with the shape measurements from the DESI Legacy Imaging Surveys. We model the GI correlations in an N-body simulation with our recent accurate stellar–halo mass relation from the Photometric object Around Cosmic webs (PAC) method. The large data set and our accurate modeling turns out an accurate measurement of the alignment angle between central galaxies and their host halos. We find that the alignment of central elliptical galaxies with their host halos increases monotonically with galaxy stellar mass or host halo mass, which can be well described by a power law for the massive galaxies. We also find that central elliptical galaxies are more aligned with their host halos in LOWZ than in CMASS, which might indicate an evolution of galaxy–halo alignment, though future studies are needed to verify this is not induced by the sample selections. In contrast, central disk galaxies are aligned with their host halos about 10 times more weakly in the GI correlation. These results have important implications for intrinsic alignment (IA) correction in weak lensing studies, IA cosmology, and theory of massive galaxy formation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Nanocatalysis: Size- and Shape-dependent Chemisorption and Catalytic Reactivity

This review article focuses on correlating the catalytic reactivity of NPs and their geometry. It illustrated that chemisorption and catalytic properties such as the onset reaction temperature, the activity, and selectivity of a nanocatalyst may be tuned through controlled synthesis of NPs with well-defined sizes and shapes. It has become clear that detailed information on the physical/chemical properties of supported NP systems must be available for the rational design of the next generation of nanosized catalysts. Such NP systems must be representative of active catalysts, and must be sufficiently well-defined ( e.g., with respect to size and shape) to serve as a basis for theoretical modeling. In addition, a synergistic combination of in situ and in operando characterization techniques working under realistic reaction conditions ( e.g. elevated temperatures and high pressure) must be available, since the working state of a NP catalyst might not be the state in which the catalyst was prepared, but a structural and/or chemical isomer that adapted to the particular reaction conditions. In order to address the complexity of real-world catalysts, a synergistic approach taking advantage of a variety of state-of-the-art experimental and theoretical methods must be undertaken. In this review, we have described some of the impressive developments that have been made in these areas. Many serious challenges still remain in the areas of catalyst characterization and design. One such challenge is to design highly active metal NP catalysts using abundant, inexpensive metals which can replace precious metal catalysts. Additionally, there is an increasingly pressing need for catalyst development for energy production applications, such as in fuel cells or for the synthesis of chemicals and fuels. Further work is needed to design more active and selective catalysts for these reactions that are viable at an industrial scale. In the coming years, nanocatalysis research must meet these challenges by building on the work described in this report. Further advancements in developing new synthetic methods will allow increased control over NP structure and stability, allowing for new insights into NP structure-reactivity correlations. In addition, the development of higher resolution in situ and in operando measurement techniques capable of probing catalytic reactions at NP surfaces over an extended range of temperatures and pressures and harsh environmental conditions will give unprecedented insight into NP catalysts in their working state. Single-nanoparticle spectroscopic and catalytic characterization must also be further developed. Advancements in computational modeling of more realistic catalysts will also bring us closer to gaining a molecularlevel view of a reaction at a NP surface when used to complement experimental studies. Such progress will bring us closer to realizing the goal of synthesizing highly effective, tailor-made, tunable nanoparticle catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

The Uniform Methods Project: Smart Thermostat Evaluation Protocol

A smart thermostat is an internet-connected device that controls home heating, ventilation, and air-conditioning (HVAC) equipment and can automatically adjust temperature set points to optimize performance and achieve energy savings. Smart thermostat features often include two way communication, occupancy detection (such as geofencing and occupancy sensors), schedule learning, and seasonal optimization algorithms. Smart thermostats can control most conventional HVAC systems, including central air conditioners, heat pumps, and forced air furnaces. Several types of residential utility programs offer smart thermostats as replacements measures. Working with smart thermostat vendors, utilities can offer separate optimization programs to produce energy savings beyond those achieved by installing a smart thermostat. From an evaluation perspective, smart thermostat programs have several noteworthy features. First, the energy savings from a smart thermostat may change over the life of the device. As a smart thermostat is connected to the internet, original equipment manufacturers can update the thermostat software to improve the thermostat's energy efficiency. Likewise, users can adjust the thermostat settings and schedules over time in response to changes in weather, thermal comfort, energy prices, or preferences for energy efficiency. Additionally, many thermostat manufacturers offer seasonal optimization programs that recommend changes or make minor, automated adjustments to the thermostat settings to improve energy efficiency. These opt-in programs are now standard offerings for many smart thermostat manufacturers and provided at no additional cost to users. The potential for software updates and continuous optimization and the evolving nature of user interactions mean future energy savings may differ from first-year savings and the energy savings of smart thermostats may need to be evaluated more than once. Second, smart thermostats often have small unit energy savings relative to a home's total energy consumption, especially in comparison to whole- home retrofit programs. This can make it difficult to detect the smart thermostat savings in billing or advanced metering infrastructure (AMI) meter consumption data. For example, as cooling loads in many regions average about 20% of annual electricity consumption, smart thermostat savings of 10% of cooling energy use would equate to a 2% reduction in home electricity consumption. Evaluators should use regression analysis of whole-home billing consumption or advanced metering infrastructure (AMI) meter consumption data to evaluate smart thermostat savings because, as explained at greater length below , these data are usually available to evaluators and regression can control for the impacts of weather and other potentially confounding factors on a home's energy consumption. Finally, as with other energy efficiency programs, participation in smart thermostat programs is self-selective. As discussed at greater length below , smart thermostat participants tend to be, among other things, younger, higher-income, and more likely to adopt electric vehicles (EVs) and internet connected devices than nonparticipants. These differences are often unobservable to the evaluator and correlated with a home's energy consumption, creating the potential for bias in estimating savings. Due to the small unit savings of thermostats, errors and biases from self-selection that may not be very consequential when evaluating a whole- home retrofits (e.g., ±2% of home electricity consumption) can have a major impact when evaluating the savings and cost-effectiveness of smart thermostat programs. A percentage point change in the estimated savings could affect the cost-effectiveness of a program. This means it is important for evaluators to assess and to minimize the potential for error from selection bias in estimating smart thermostat program savings. The Uniform Methods Project provides model protocols for determining energy savings and demand reductions that result from specific energy efficiency measures implemented through state and utility programs. In most cases, the measure protocols are based on a particular option identified by the International Performance Verification and Measurement Protocol ; however, this work provides a more detailed approach to implementing that option. Each chapter is written by technical experts in collaboration with their peers, reviewed by industry experts, and subject to public review and comment. The UMP protocols can be used by utilities, program administrators, public utility commissions, evaluators, and other stakeholders for both program planning and evaluation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRSDate not supplied

Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning

Multi-model Monte Carlo methods have been demonstrated to be an efficient and accurate alternative to standard Monte Carlo (MC) in the model-based propagation of uncertainty in entry, descent, and landing (EDL) applications. These multi-model MC methods fuse predictions from low-fidelity models with the high-fidelity EDL model of interest to produce unbiased statistics with a fraction of the computational cost. The accuracy and efficiency of the multi-model MC methods are dependent upon the magnitude of correlations of the low-fidelity models with the high-fidelity model, but also upon the correlation amongst the low-fidelity models, and their relative computational cost. Because of this layer of complexity, the question of how to optimally select the set of low-fidelity models has remained open. In this work, methods for optimal model construction and tuning are investigated as a means to increase the speed and precision of trajectory simulation for EDL. Specifically, the focus is on the inclusion of low-fidelity model tuning within the sample allocation optimization that accompanies multi-model MC methods. Preliminary results indicate that low-fidelity model tuning can significantly improve efficiency and precision of trajectory simulations and provide an increased edge to multi-model MC methods when compared to standard MC. The challenges and potential benefits to exploring a fully iterative and comprehensive optimization strategy in future work are highlighted.

uncertainty quantification↗
NASA NTRSDate not supplied

Improving Multi-Model Trajectory Simulation Estimators using Model Selection and Tuning

Multi-model Monte Carlo methods have been demonstrated to be an efficient and accurate alternative to standard Monte Carlo (MC) in the model-based propagation of uncertainty in entry, descent, and landing (EDL) applications. These multi-model MC methods fuse predictions from low-fidelity models with the high-fidelity EDL model of interest to produce unbiased statistics with a fraction of the computational cost. The accuracy and efficiency of the multi-model MC methods are dependent upon the magnitude of correlations of the low-fidelity models with the high-fidelity model, but also upon the correlation among the low-fidelity models, and their relative computational cost. Because of this layer of complexity, the question of how to optimally select the set of low-fidelity models has remained open. In this work, methods for optimal model construction and tuning are investigated as a means to increase the speed and precision of trajectory simulation for EDL. Specifically, the focus is on the inclusion of low-fidelity model tuning within the sample allocation optimization that accompanies multi-model MC methods. Preliminary results indicate that low-fidelity model tuning can significantly improve efficiency and precision of trajectory simulations and provide an increased edge to multi-model MC methods when compared to standard MC. The challenges and potential benefits to exploring a fully iterative and comprehensive optimization strategy in future work are highlighted.

uncertainty quantification↗
DOE OSTI2016

Assessment of Lung Tumour Motion and Volume Size Dependencies Using Various Evaluation Measures

The purpose of the study was to assess internal target volume changes through the breathing cycle and associated tumour motion for lung patients and to establish possible correlations between different parameters. Respiration-induced volume changes with breathing cycle and the associated tumour motion were analyzed for 11 patients. Selected phases were the maximum and average intensity projections and the 10 phases of equal duration and separation obtained through the respiratory cycle. Tumour centre of mass (COM) motion planes were generated using least square fitting, and their angles and orientations were then compared between the cases studied. Trajectories that are composed by the points of COM location in different phases were identified, and their interrelation was assessed through different similarity measures. The results were used to determine if there is any correlation between parameters chosen and if the margins conventionally used for the planning target volume creation successfully encompassed lung tumour motion and volume change. The results show that the extent of tumour motion was related to its volume and location. The tumour displacement was predominantly left and inferior. Planar fitting to COM motion data through respiratory phases demonstrated some correlation in best fit motion plane positions between different data sets. In the plane fit comparison, for each patient, the lower root mean square error values showed that a good planar fit can be achieved for the COM motion path. The evaluation of the inhale and exhale trajectories may allow, for certain tumour locations and size, contouring on only inhalation or exhalation phases, knowing that tumour motion will be adequately covered on the other phases. Taking all the data into account and knowing the tumour size and location, a good estimate can be made of the motion plane position in the three-dimensional space and the required dosimetric margins.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2015

TU-CD-BRB-04: Automated Radiomic Features Complement the Prognostic Value of VASARI in the TCGA-GBM Dataset

Purpose: To compare the complementary prognostic value of automated Radiomic features to that of radiologist-annotated VASARI features in TCGA-GBM MRI dataset. Methods: For 96 GBM patients, pre-operative MRI images were obtained from The Cancer Imaging Archive. The abnormal tumor bulks were manually defined on post-contrast T1w images. The contrast-enhancing and necrotic regions were segmented using FAST. From these sub-volumes and the total abnormal tumor bulk, a set of Radiomic features quantifying phenotypic differences based on the tumor intensity, shape and texture, were extracted from the post-contrast T1w images. Minimum-redundancy-maximum-relevance (MRMR) was used to identify the most informative Radiomic, VASARI and combined Radiomic-VASARI features in 70% of the dataset (training-set). Multivariate Cox-proportional hazards models were evaluated in 30% of the dataset (validation-set) using the C-index for OS. A bootstrap procedure was used to assess significance while comparing the C-Indices of the different models. Results: Overall, the Radiomic features showed a moderate correlation with the radiologist-annotated VASARI features (r = −0.37 – 0.49); however that correlation was stronger for the Tumor Diameter and Proportion of Necrosis VASARI features (r = −0.71 – 0.69). After MRMR feature selection, the best-performing Radiomic, VASARI, and Radiomic-VASARI Cox-PH models showed a validation C-index of 0.56 (p = NS), 0.58 (p = NS) and 0.65 (p = 0.01), respectively. The combined Radiomic-VASARI model C-index was significantly higher than that obtained from either the Radiomic or VASARI model alone (p = <0.001). Conclusion: Quantitative volumetric and textural Radiomic features complement the qualitative and semi-quantitative annotated VASARI feature set. The prognostic value of informative qualitative VASARI features such as Eloquent Brain and Multifocality is increased with the addition of quantitative volumetric and textural features from the contrast-enhancing and necrotic tumor regions. These results should be further evaluated in larger validation cohorts.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Bichromatic Wave Selection for Validation of the Difference-Frequency Transfer Function for the OC6 Validation Campaign: Preprint

The focus of the Offshore Code Comparison Collaboration, Continuation, with Correlation and unCertainity (OC6) project, which operates under the International Energy Agency (IEA) Wind Task 30, is to refine the accuracy of engineering tools used to design offshore wind turbines. In support of this work, a new validation campaign is being developed that seeks to better understand the nonlinear wave loading that excites floating wind systems at their low-frequency, rigid-body modes in surge and pitch. The validation data will be used in a three-way validation between simplified engineering tools and higher-fidelity tools, such as computational fluid dynamics (CFD). Irregular wave spectrums, which are traditionally used to examine the nonlinear wave interaction with offshore structures, are too computationally expensive to be simulated in CFD tools, and so bichromatic wave cases will be used instead. This paper reviews the process used to choose the bichromatic wave pairs to be used in the campaign to validate the second-order difference-frequency quadratic and potential loads at the surge and pitch natural frequencies of a floating semisubmersible.

17 WIND ENERGY↗