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The Role of Spin–Orbit Coupling in the Linear Absorption Spectrum and Intersystem Crossing Rate Coefficients of Ruthenium Polypyridyl Dyes

The successful use of molecular dyes for solar energy conversion requires efficient charge injection, which in turn requires the formation of states with sufficiently long lifetimes (e.g., triplets). The molecular structure elements that confer this property can be found empirically, however computational predictions using ab initio electronic structure methods are invaluable to identify structure-property relations for dye sensitizers. The primary challenge for simulations to elucidate the electronic and nuclear origins of these properties is a spin-orbit interaction which drives transitions between electronic states. Here, in this work, we present a computational analysis of the spin-orbit corrected linear absorption cross sections and intersystem crossing rate coefficients for a derivative set of phosphonated tris(2,2'-bipyridine)ruthenium(2+) dye molecules. After sampling the ground state vibrational distributions, the predicted linear absorption cross sections indicate that the mixture between singlet and triplet states plays a crucial role in defining the line shape of the metal-to-ligand charge transfer bands in these derivatives. Additionally, an analysis of the intersystem crossing rate coefficients suggests that transitions from the singlet into the triplet manifolds are ultrafast with rate coefficients on the order of 10 13 s -1 for each dye molecule.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

42 ENGINEERING↗

Tracer-field cross-correlations with k -nearest neighbour distributions

ABSTRACT In astronomy and cosmology significant effort is devoted to characterizing and understanding spatial cross-correlations between points – e.g galaxy positions, high energy neutrino arrival directions, X-ray and AGN sources, and continuous fields – e.g. weak lensing meiand Cosmic Microwave Background maps. Recently, we introduced the k-nearest neighbour (kNN) formalism to better characterize the clustering of discrete (point) data sets. Here, we extend it to the point – field cross-correlations analysis. It combines kNN measurements of the point data set with measurements of the field smoothed at many scales. The resulting statistics are sensitive to all orders in the joint clustering of the points and the field. We demonstrate that this approach, unlike the 2-pt cross-correlation, can measure the statistical dependence of two data sets even when there are no linear (Gaussian) correlations between them. We further demonstrate that this framework is far more effective than the two point function in detecting cross-correlations when the continuous field is contaminated by high levels of noise. For a particularly high level of noise, the cross-correlation between haloes and the underlying matter field in a cosmological simulation, between 10 h−1 Mpc and 30 h−1 Mpc, is detected at >5σ significance using the technique presented here, when the two-point cross-correlation significance is ∼1σ. Finally, we show that kNN cross-correlations of haloes and the matter field can be well modelled on quasi-linear scales using the Hybrid Effective Field Theory (HEFT) framework, with the same set of bias parameters as are used for 2-pt cross-correlations. The substantial improvement in the statistical power of detecting cross-correlations using this method makes it a promising tool for various cosmological applications.

79 ASTRONOMY AND ASTROPHYSICS↗

Insights from the APOKASC determination of the evolutionary state of red-giant stars by consolidation of different methods

ABSTRACT The internal working of low-mass stars is of great significance to both the study of stellar structure and the history of the Milky Way. Asteroseismology has the power to directly sense the internal structure of stars and allows for the determination of the evolutionary state – i.e. has helium burning commenced or is the energy generated only by the fusion in the hydrogen-burning shell? We use observational data from red-giant stars in a combination (known as APOKASC) of asteroseismology (from the Kepler mission) and spectroscopy (from SDSS/APOGEE). The new feature of the analysis is that the APOKASC evolutionary state determination is based on the comparison of diverse approaches to the investigation of the frequency-power spectrum. The high level of agreement between the methods is a strong validation of the approaches. Stars for which there is not a consensus view are readily identified. The comparison also facilitates the identification of unusual stars including those that show evidence for very strong coupling between p and g cavities. The comparison between the classification based on the spectroscopic data and asteroseismic data have led to a new value for the statistical uncertainty in APOGEE temperatures. These consensus evolutionary states will be used as an input for methods that derive masses and ages for these stars based on comparison of observables with stellar evolutionary models (‘grid-based modelling’) and as a training set for machine-learning and other data-driven methods of evolutionary state determination.

Elsworth, Yvonne↗

Efficient Contingency Analysis in Power Systems via Network Trigger Nodes

Modeling failure dynamics within a power system is a complex and challenging process due to multiple inter-dependencies and convoluted inter-domain relationships. Subject matter experts (SMEs) are interested in understanding these failure dynamics for reducing the impact from future disasters (i.e., losses or failures of power system components, such as transmission lines). Contingency analysis (CA) tools enable such ’what-if’ scenario analyses to evaluate the impacts on the power system. Analyzing all possible contingencies among N system components can be computationally expensive. An important step for performing CA is identifying a set of k ‘trigger’ components, which when failed initially can significantly impact the overall system by causing multiple failures. Currently SMEs focus on identifying these trigger components by running expensive simulations on all possible subsets, which quickly becomes infeasible. Hence finding a relevant set of trigger components (contingencies) rapidly to enable efficient and useful CA is crucial.In a collaboration between computer scientists and power system experts, we propose an efficient method for performing CA by exploiting network inter-dependencies in power system components. First, we construct a network with multiple electric grid infrastructure components and dependencies as connections among them. We reformulate the problem of finding a set of trigger components as a problem of identifying critical nodes in the network, which can cascade power failures through connected nodes and cause significant damage to the network. To guide the practical CA tools, we develop a network-based model with a probabilistic edge-weights setup using intricate domain rules. Then we conduct an empirical study on real power system data in the US for both regional and national levels. Firstly, we use power system datasets for the US to create a national-scale domain-driven model. Secondly, we demonstrate that network-based model outperforms the outputs from a real CA tool and show on average 25 × improved selection of contingencies, thereby showcasing practical benefits to the power experts.

Tabassum, Anika↗

Irreversible Wash Aid Additive for Cesium Mitigation. Small-Scale Demonstration and Lessons Learned

The Irreversible Wash Aid Additive process has been under development by the U.S. Environmental Protection Agency (EPA) and Argonne National Laboratory (Argonne). This process for radioactive cesium mitigation consists of a solution to wash down contaminated structures, roadways, and vehicles and a sequestering agent to bind the radionuclides from the wash water and render them environmentally immobile. The purpose of this process is to restore functionality to basic services and immediately reduce the consequences of a radiologically-contaminated urban environment. Research and development have resulted in a down-selection of technologies for integration and demonstration at the pilot-scale level as part of the Wide Area Recovery and Resiliency Program (WARRP) under the Department of Homeland Security and the Denver Urban Area Security Initiative. As part of developing the methods for performing a pilot-scale demonstration at the WARRP conference in Denver in 2012, Argonne conducted small-scale field experiments at Separmatic Systems. The main purpose of these experiments was to refine the wash water collection and separations systems and demonstrate key unit operations to help in planning for the large scale demonstration in Denver. Since the purpose of these tests was to demonstrate the operations of the system, we used no radioactive materials. After a brief set of experiments with the LAKOS unit to familiarize ourselves with its operation, two experiments were completed on two separate dates with the Separmatic systems.

61 RADIATION PROTECTION AND DOSIMETRY↗

An Overview of the Risk Assessment Information System

This technical memorandum (TM) presents an overview of the Risk Assessment Information System (RAIS), a collection of web-based tools designed to assist with the environmental risk assessment process. The objective of the RAIS is to be a single resource for the risk assessment process, providing guidance when planning and performing the steps: data assessment, exposure assessment, toxicity assessment, and risk characterization. The RAIS evolved as a result of the initial remediation efforts at various United States (U.S.) Department of Energy (DOE) facilities. The goal was to increase the efficiency and transparency of the human health and ecological assessments being performed by DOE’s Office of Environmental Management, Oak Ridge Operations (ORO) office by providing a repository for toxicity information, physicochemical data, risk assessment procedures, standardized risk calculation methods, and web-based tools. Since the initial launch in 1996, the RAIS has expanded its user base outside of the federal government and now has users from over 100 countries, universities, states, and local governments. What sets the RAIS apart from other risk assessment sites are the publicly available, searchable toxicity and physicochemical databases and the wide range of chemical and radionuclide risk calculation tools. The purpose of this TM is to present the RAIS tools in order of the website menus and explain how they fit in the risk assessment process. In addition, this TM describes differences between the chemical and radionuclide tools of the RAIS. Screening level equations, chronic daily intake equations, and default exposure factors used in the chemical and radionuclide calculators are included in the appendices of this TM. This TM is not intended to be a detailed guide to risk assessment or the RAIS tools. The tools on the RAIS can be used to comply with procedures from multiple agencies, including but not limited to DOE, U.S. Environmental Protection Agency (EPA), U.S. Department of Defense (DoD), and many state governments. Further information on the RAIS tools can be found in the user guides and tutorials available on the webpage.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Acoustic Mode Measurements in the Inlet of a Model Turbofan Using a Continuously Rotating Rake

Comprehensive measurements of the spinning acoustic mode structure in the inlet of the Advanced Ducted Propeller (ADP) have been completed. These measurements were taken using a unique and previously untried method which was first proposed by T.G. Sofrin. A continuously rotating microphone system was employed. The ADP model was designed and built by Pratt & Whitney and tested in the NASA Lewis 9- by 15-foot Anechoic Wind Tunnel. Three inlet configurations were tested with cut-on and cutoff stator vane sets. The cutoff stator was designed to suppress all modes at the blade passing frequency. Rotating rake measurements indicate that several extraneous circumferential modes were active. The mode orders suggest that their source was an interaction between the rotor and small interruptions in the casing tip treatment. The cut-on stator produced the expected circumferential modes plus higher levels of the unexpected modes seen with the cutoff stator.

Heidelberg, Laurence J.↗

Acoustic mode measurements in the inlet of a model turbofan using a continuously rotating rake

Comprehensive measurements of the spinning acoustic mode structure in the inlet of the Advanced Ducted Propeller (ADP) have been completed. These measurements were taken using a unique and previously untried method which was first proposed by T.G. Sofrin. A continuously rotating microphone system was employed. The ADP model was designed and built by Pratt & Whitney and tested in the NASA Lewis 9- by 15-foot Anechoic Wind Tunnel. Three inlet configurations were tested with cut-on and cutoff stator vane sets. The cutoff stator was designed to suppress all modes at the blade passing frequency. Rotating rake measurements indicate that several extraneous circumferential modes were active. The mode orders suggest that their source was an interaction between the rotor and small interruptions in the casing tip treatment. The cut-on stator produced the expected circumferential modes plus higher levels of the unexpected modes seen with the cutoff stator.

Heidelberg, Laurence J.↗

Requirements Development for the NASA Advanced Engineering Environment (AEE)

The requirements development process for the Advanced Engineering Environment (AEE) is presented. This environment has been developed to allow NASA to perform independent analysis and design of space transportation architectures and technologies. Given the highly collaborative and distributed nature of AEE, a variety of organizations are involved in the development, operations and management of the system. Furthermore, there are additional organizations involved representing external customers and stakeholders. Thorough coordination and effective communication is essential to translate desired expectations of the system into requirements. Functional, verifiable requirements for this (and indeed any) system are necessary to fulfill several roles. Requirements serve as a contractual tool, configuration management tool, and as an engineering tool, sometimes simultaneously. The role of requirements as an engineering tool is particularly important because a stable set of requirements for a system provides a common framework of system scope and characterization among team members. Furthermore, the requirements provide the basis for checking completion of system elements and form the basis for system verification. Requirements are at the core of systems engineering. The AEE Project has undertaken a thorough process to translate the desires and expectations of external customers and stakeholders into functional system-level requirements that are captured with sufficient rigor to allow development planning, resource allocation and system-level design, development, implementation and verification. These requirements are maintained in an integrated, relational database that provides traceability to governing Program requirements and also to verification methods and subsystem-level requirements.

Rogers, Eric↗

Hybrid data-driven and model-informed online tool wear detection in milling machines

Precision machining tool wear is responsible for low product throughput and quality. Monitoring the tool wear online is vital to prevent degradation in machining quality. However, direct real-time tool wear measurement is not practical. This paper presents residual-based anomaly detection models, combining a hybrid model comprised of a physics-based model and a data-driven model (a decision tree or a neural network) to predict signals of interest (e.g., power or forces) under nominal conditions, followed by Page’s cumulative sum test for detecting tool wear on-line using the computer numerical control machine measurements. The most informative features are ranked using dynamic programming and its approximation variants from real-time measurements and machine settings, such as the width of cut, depth of cut, feed rate and spindle speed, that serve as inputs to the predictive models. The baseline nominal model is incrementally updated with experimental data via a gradient boosted adaptation model to generate the residuals that account for discrepancies between the actual machine data under normal conditions and the baseline nominal model predictions. The hybrid model is validated against 20 Mazak milling machine experimental tests and one Haas run-to-failure experiment. The proposed anomaly detector is applied to synthetic data from simulations of the physics-based model at different operating conditions, measurement noise levels, and tool wear levels, and the methods were able to achieve an overall 92% accuracy in data with 1% noise. The anomaly detection methods based on hybrid model reduced the false alarms of either the data-driven or physical-based models alone, and are found to be capable of good online detection of tool wear.

Online anomaly detection↗

Longitudinal analysis of risk factors for dementia based on Mild Cognitive Impairment Screen results and questionnaire responses from healthy Japanese individuals registered in an online database

Abstract Introduction Despite an urgent need for developing remedial measures against dementia, no disease‐modifying drugs have been developed. Efficient protocols for participant recruitment need to be established for conducting clinical trials. To meet this need, a large‐scale online registry system, the Integrated Registry of Orange Plan (IROOP ® ), was created for healthy individuals. Although the risk factors for dementia have been discussed in our previous studies for a short interval of 6 months, some factors remain controversial. The present study aimed to explore factors affecting longitudinal changes in cognitive function for a longer interval of 18 months using the IROOP ® data. Methods This study assessed the longitudinal changes in the collated data for predicting the risk of dementia and included 473 individuals (175 men and 298 women; mean age 59.6 ± 10.1 years) registered in the IROOP ® between July 5, 2016 and January 15, 2018 who completed the initial questionnaire and brief assessment of cognitive function (Mild Cognitive Impairment Screen) at baseline and the regular questionnaire and the Mild Cognitive Impairment Screen at least once after baseline. Statistical analyses were performed using IBM SPSS, version 23.0, for Windows for demographic data and the MIXED procedure in SAS, version 9.4, for the linear mixed‐effect model. In each analysis, the statistical significance level was set at P < .05. Results Mood, sleep, quality of life, and medical histories including cognition were found to influence longitudinal changes in cognitive function. Discussion Given the multifactorial etiology of dementia, preventive measures targeting multiple domains are required for maintaining cognitive function, instead of focusing on one lifestyle factor.

Ogawa, Masayo↗

A study of the degree of fluorination in regioregular poly(3-hexylthiophene)

Here, we systematically varied the degree of fluorination along the backbone of a series of highly regioregular 3-hexylthiophene-based polymers, P3HT-50F, P3HT-33F and P3HT-25F, in which 50%, 33% and 25% of the thiophene units within the polymer chain contain fluorine atoms in the available 4-position. These materials were homopolymerized using the Kumada catalyst transfer polycondensation method from a set of mono-fluorinated bi-, ter- and quarterthiophenes, to ensure high polymer regioregularity and evenly-spaced fluorine atoms along the conjugated thiophene backbone. The monomers were obtained from a synthetic route consisting of iterative Migita-Stille couplings of fluorinated and non-fluorinated 3- hexylthiophenes. The effect of the fluorine atoms on both polymer structure and properties is presented, with supporting quantum mechanical calculations that rationalize the intrinsic conformation preferences of the three P3HT derivatives. P3HT-50F (M¯ n = 34 kg/mol, 98.5% rr), P3HT-33F (M¯ n = 46 kg/mol, 98% rr) and P3HT-25F (M¯ n = 53 kg/mol, 95% rr) displayed HOMO levels of -5.34, -5.26 and -5.24 eV, bandgaps of 1.98, 1.98 and 1.97 eV, and average field-effect transistor hole mobilities of 4.5 × 10 -3 , 2.7 × 10 -2 , and 1.2 × 10 -2 cm 2 V -1 s -1 , respectively.

36 MATERIALS SCIENCE↗

Monitoring Change Through Hierarchical Segmentation of Remotely Sensed Image Data

NASA's Goddard Space Flight Center has developed a fast and effective method for generating image segmentation hierarchies. These segmentation hierarchies organize image data in a manner that makes their information content more accessible for analysis. Image segmentation enables analysis through the examination of image regions rather than individual image pixels. In addition, the segmentation hierarchy provides additional analysis clues through the tracing of the behavior of image region characteristics at several levels of segmentation detail. The potential for extracting the information content from imagery data based on segmentation hierarchies has not been fully explored for the benefit of the Earth and space science communities. This paper explores the potential of exploiting these segmentation hierarchies for the analysis of multi-date data sets, and for the particular application of change monitoring.

Tilton, James C.↗

Automated Generation and Assessment of Autonomous Systems Test Cases

This slide presentation reviews some of the issues concerning verification and validation testing of autonomous spacecraft routinely culminates in the exploration of anomalous or faulted mission-like scenarios using the work involved during the Dawn mission's tests as examples. Prioritizing which scenarios to develop usually comes down to focusing on the most vulnerable areas and ensuring the best return on investment of test time. Rules-of-thumb strategies often come into play, such as injecting applicable anomalies prior to, during, and after system state changes; or, creating cases that ensure good safety-net algorithm coverage. Although experience and judgment in test selection can lead to high levels of confidence about the majority of a system's autonomy, it's likely that important test cases are overlooked. One method to fill in potential test coverage gaps is to automatically generate and execute test cases using algorithms that ensure desirable properties about the coverage. For example, generate cases for all possible fault monitors, and across all state change boundaries. Of course, the scope of coverage is determined by the test environment capabilities, where a faster-than-real-time, high-fidelity, software-only simulation would allow the broadest coverage. Even real-time systems that can be replicated and run in parallel, and that have reliable set-up and operations features provide an excellent resource for automated testing. Making detailed predictions for the outcome of such tests can be difficult, and when algorithmic means are employed to produce hundreds or even thousands of cases, generating predicts individually is impractical, and generating predicts with tools requires executable models of the design and environment that themselves require a complete test program. Therefore, evaluating the results of large number of mission scenario tests poses special challenges. A good approach to address this problem is to automatically score the results based on a range of metrics. Although the specific means of scoring depends highly on the application, the use of formal scoring - metrics has high value in identifying and prioritizing anomalies, and in presenting an overall picture of the state of the test program. In this paper we present a case study based on automatic generation and assessment of faulted test runs for the Dawn mission, and discuss its role in optimizing the allocation of resources for completing the test program.

Testing challenges↗

Reconstituted Three-Dimensional Interactive Imaging

A method combines two-dimensional images, enhancing the images as well as rendering a 3D, enhanced, interactive computer image or visual model. Any advanced compiler can be used in conjunction with any graphics library package for this method, which is intended to take digitized images and virtually stack them so that they can be interactively viewed as a set of slices. This innovation can take multiple image sources (film or digital) and create a "transparent" image with higher densities in the image being less transparent. The images are then stacked such that an apparent 3D object is created in virtual space for interactive review of the set of images. This innovation can be used with any application where 3D images are taken as slices of a larger object. These could include machines, materials for inspection, geological objects, or human scanning. Illuminous values were stacked into planes with different transparency levels of tissues. These transparency levels can use multiple energy levels, such as density of CT scans or radioactive density. A desktop computer with enough video memory to produce the image is capable of this work. The memory changes with the size and resolution of the desired images to be stacked and viewed.

Hamilton, Joseph↗

Far Term Noise Reduction Roadmap for the Mid-Fuselage Nacelle Subsonic Transport

A noise reduction technology roadmap study is presented to determine the feasibility for the Mid-Fuselage Nacelle (MFN) aircraft concept to achieve the noise goal set by NASA for the Far Term time frame, beyond 2035. The study starts with updating the noise prediction of the existing MFN configuration that had been modeled for the time frame between 2025 and 2035. The updated prediction for the Mid Term time frame is 34.3 dB cumulative effective perceived noise level (EPNL) below the Stage 4 regulation. A suite of technologies that are deemed feasible to mature for practical implementation in the Far Term and whose potentials for noise reduction have been illustrated is selected for analysis. For each technology, component noise reduction is modeled either by available experimental data or by physics-based modeling with aircraft system level methods. The noise reduction is then applied to the corresponding noise component predicted by advanced aircraft system noise prediction tools, and the total aircraft noise is predicted as the incoherent summation of the components. It is shown that the Far Term MFN aircraft has the potential to achieve a cumulative noise level of 40.2 EPNL dB below Stage 4. The key technologies to achieve this low aircraft noise level are assessed by the impact of each technology on the aircraft system noise. This roadmap shows the potential of this revolutionary, yet still tube-and-wing, MFN concept to reach the NASA Far Term noise goal.

Guo, Yueping↗

Magnetic Field Intermittency in the Solar Wind: Parker Solar Probe and SolO Observations Ranging from the Alfvén Region up to 1AU

Parker Solar Probe (PSP) and SolO data are utilized to investigate magnetic field intermittency in the solar wind (SW). Small-scale intermittency (20−100 di) is observed to radially strengthen when methods relying on higher-order moments are considered (SFq; SDK), but no clear trend is observed at larger scales. However, lower-order moment-based methods (e.g., partial variance of increments; PVI) are deemed more appropriate for examining the evolution of the bulk of coherent structures (CSs), PVI ≥ 3. Using PVI, we observe a scale-dependent evolution in the fraction of the data set occupied by CSs, fPVI≥3. Specifically, regardless of the SW speed, a subtle increase is found in fPVI≥3 for ℓ = 20 di, in contrast to a more pronounced radial increase in CSs observed at larger scales. Intermittency is investigated in relation to plasma parameters. Though, slower SW speed intervals exhibit higher fPVI≥6 and higher kurtosis maxima, no statistical differences are observed for fPVI≥3. Highly Alfvénic intervals display lower levels of intermittency. The anisotropy with respect to the angle between the magnetic field and SW flow, ΘVB is investigated. Intermittency is weaker at ΘVB ≈ 0° and is strengthened at larger angles. Considering the evolution at a constant alignment angle, a weakening of intermittency is observed with increasing advection time of the SW. Our results indicate that the strengthening of intermittency in the inner heliosphere is driven by the increase in comparatively highly intermittent perpendicular intervals sampled by the probes with increasing distance, an effect related directly to the evolution of the Parker spiral.

Nikos Sioulas↗

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