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At least 739 records · Page 41

Endomembrane Cation Transporters and Membrane Trafficking

Multicellular, as well as unicellular, organisms have evolved mechanisms to regulate ion and pH homeostasis in response to developmental cues and to a changing environment. The working hypothesis is that the balance of fluxes mediated by diverse transporters at the plasma membrane and in subcellular organelles determines ionic cellular distribution, which is critical for maintenance of membrane potential, pH control, osmolality, transport of nutrients, and protein activity. An emerging theme in plant cell biology is that cells respond and adapt to diverse cues through changes of the dynamic endomembrane system. Yet we know very little about the transporters that might influence the operation of the secretory system in plants. Here we focus on transporters that influence alkali cation and pH homeostasis, mainly in the endomembrane/ secretory system. The endomembrane system of eukaryote cells serves several major functions: i) sort cargo (e.g. enzymes, transporters or receptors) to specific destinations, ii) modulate the protein and lipid composition of membrane domains through remodeling, and iii) determine and alter the properties of the cell wall through synthesis and remodeling. We had uncovered a novel family of predicted cation/H + exchangers (CHX) and K + efflux antiporters (KEA) that are prevalent in higher plants, but rare in metazoans. We combined phylogenetic and transcriptomic analyses with molecular genetic, cell biological and biochemical studies, and have published the first reports on functions of plant CHXs and KEAs. CHX studied to date act at the endomembrane system where their actions are distinct from the better-studied NHX (Na/K-H + exchangers). Arabidopsis thaliana CHX20 in guard cells modulate stomatal opening, and thus is significant for vegetative survival. Other CHXs ensure reproductive success on dry land, as they participate in organizing pollen walls, targeting of pollen tubes to the ovule or promoting fertilization. Based on localization and mutant analyses, we conclude that CHXs modulate the ion balance, pH or both in micro-regions of endoplasmic reticulum, endosomes and prevacuolar compartment (PVC), and so influence membrane trafficking and signaling resulting in proper osmoregulation in guard cells and seed formation. We also demonstrated for the first time that AtKEA2 associates with chloroplasts, especially at the two poles of developing plastids. These results show that AtKEA1 and AtKEA2 transporters in specific microdomains of the inner envelope link local osmotic, ionic, and pH homeostasis to plastid division and thylakoid membrane formation. The first 3-D structure model of AtCHX was generated, and architecture-directed mutagenesis identified critical residues of the transport core giving insights to the transport mode of this family. Thus we have revealed for the first time crucial roles of an unknown K + /H + transport family on plant growth (KEA), gas exchange, pollen cell wall, and different phases of reproduction (CHXs). The dynamic endomembrane of plant cells is integral to cytokinesis, cell expansion, defense, and cell wall formation, thus these studies are directly relevant to the mission of the Department of Energy and to a better understanding of determinants for enhancing plant biomass and plant tolerance to abiotic stress.

54 ENVIRONMENTAL SCIENCES↗

Exploring the Clouds of Venus: Science Driven Aerobot Missions to Our Sister Planet

Venus is essential to our understanding of the evolution and habitability of Earth-size planets throughout the galaxy. The selection of the VERITAS, EnVision, and DAVINCI missions by NASA and ESA in June 2021 is an important step in advancing the science. However, addressing many of the most challenging questions will require in situ platforms that can operate in the Venus environment for extended periods in order to capture the full complexity of our sister planet. Aerobots are aerial vehicles that exploit buoyancy to achieve long-duration operation in the Venus cloud layer where environmental conditions are comparatively benign. Buoyancy control, explained in more detail in a companion paper at this conference, allows aerobots to change altitude with little energy expenditure enabling new scientific measurement opportunities. These include atmospheric chemistry, dynamics, geophysical measurements of the crust and interior and geological investigations enabled by high resolution surface imaging. One aspect to our approach to defining missions that fit within the resource constraints of competitive missions is keeping the scale small. Today’s science-driven appetite for sophisticated measurements and large volumes of data is driving size upwards but advances in technology can enable aerobots that can be delivered to Venus at manageable costs. The other aspect is supporting the aerobot at Venus with orbiters providing data relay, localization and synergistic science. The recently selected orbiters, equipped with low-cost proximity relay systems routinely used at Mars may obviate the need for dedicated orbiters thereby enabling Discovery mission candidates. Four aerobot mission concepts have been defined which fit comfortably within the current New Frontiers (NF) cost cap ($900M in $FY22). One of these concepts would also be a candidate for a Discovery mission if that cost cap ($500M in $FY19) were raised. Raising the NF cost cap would enable more capable aerobot missions combining both altitude control with synergistic orbital observations. Investigations of surface geology at high resolution with subcloud NIR nightside imaging and dropsondes on the dayside of Venus could also benefit from collaborations with foreign contributions.

"O'Rourke, Joseph"↗

CICE, The Los Alamos Sea Ice Model

The Los Alamos sea ice model (CICE) is the result of an effort to develop a computationally efficient sea ice component for a fully coupled atmosphere–land–ocean–ice global climate model. It was originally designed to be compatible with the Parallel Ocean Program (POP), an ocean circulation model developed at Los Alamos National Laboratory for use on massively parallel computers. CICE has several interacting components: a vertical thermodynamic model that computes local growth rates of snow and ice due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of ice dynamics, which predicts the velocity field of the ice pack based on a model of the material strength of the ice; an incremental remapping transport model that describes horizontal advection of the areal concentration, ice and snow volume and other state variables; and a ridging parameterization that transfers ice among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the ice ecosystem. The CICE sea ice model is used for climate research as one component of complex global earth system models that include atmosphere, land, ocean and biogeochemistry components. It is also used for operational sea ice forecasting in the polar regions and in numerical weather prediction models.

Hunke, Elizabeth↗

Multi-Element Unstructured Analyses of Complex Valve Systems

The safe and reliable operation of high pressure test stands for rocket engine and component testing places an increased emphasis on the performance of control valves and flow metering devices. In this paper, we will present a series of high fidelity computational analyses of systems ranging from cryogenic control valves and pressure regulator systems to cavitating venturis that are used to support rocket engine and component testing at NASA Stennis Space Center. A generalized multi-element framework with sub-models for grid adaption, grid movement and multi-phase flow dynamics has been used to carry out the simulations. Such a framework provides the flexibility of resolving the structural and functional complexities that are typically associated with valve-based high pressure feed systems and have been difficult to deal with traditional CFD methods. Our simulations revealed a rich variety of flow phenomena such as secondary flow patterns, hydrodynamic instabilities, fluctuating vapor pockets etc. In the paper, we will discuss performance losses related to cryogenic control valves, and provide insight into the physics of the dominant multi-phase fluid transport phenomena that are responsible for the choking like behavior in cryogenic control elements. Additionally, we will provide detailed analyses of the modal instability that is observed in the operation of the dome pressure regulator valve. Such instabilities are usually not localized and manifest themselves as a system wide phenomena leading to an undesirable chatter at high flow conditions.

Sulyma, Peter↗

Lightweight, Miniature Inertial Measurement System

A miniature, lighter-weight, and highly accurate inertial navigation system (INS) is coupled with GPS receivers to provide stable and highly accurate positioning, attitude, and inertial measurements while being subjected to highly dynamic maneuvers. In contrast to conventional methods that use extensive, groundbased, real-time tracking and control units that are expensive, large, and require excessive amounts of power to operate, this method focuses on the development of an estimator that makes use of a low-cost, miniature accelerometer array fused with traditional measurement systems and GPS. Through the use of a position tracking estimation algorithm, onboard accelerometers are numerically integrated and transformed using attitude information to obtain an estimate of position in the inertial frame. Position and velocity estimates are subject to drift due to accelerometer sensor bias and high vibration over time, and so require the integration with GPS information using a Kalman filter to provide highly accurate and reliable inertial tracking estimations. The method implemented here uses the local gravitational field vector. Upon determining the location of the local gravitational field vector relative to two consecutive sensors, the orientation of the device may then be estimated, and the attitude determined. Improved attitude estimates further enhance the inertial position estimates. The device can be powered either by batteries, or by the power source onboard its target platforms. A DB9 port provides the I/O to external systems, and the device is designed to be mounted in a waterproof case for all-weather conditions.

Tang, Liang↗

CICE, The Los Alamos Sea Ice Model

The Los Alamos sea ice model (CICE) is the result of an effort to develop a computationally efficient sea ice component for a fully coupled atmosphere–land–ocean–ice global climate model. It was originally designed to be compatible with the Parallel Ocean Program (POP), an ocean circulation model developed at Los Alamos National Laboratory for use on massively parallel computers. CICE has several interacting components: a vertical thermodynamic model that computes local growth rates of snow and ice due to vertical conductive, radiative and turbulent fluxes, along with snowfall; an elastic-viscous-plastic model of ice dynamics, which predicts the velocity field of the ice pack based on a model of the material strength of the ice; an incremental remapping transport model that describes horizontal advection of the areal concentration, ice and snow volume and other state variables; and a ridging parameterization that transfers ice among thickness categories based on energetic balances and rates of strain. It also includes a biogeochemical model that describes evolution of the ice ecosystem. The CICE sea ice model is used for climate research as one component of complex global earth system models that include atmosphere, land, ocean and biogeochemistry components. It is also used for operational sea ice forecasting in the polar regions and in numerical weather prediction models.

Hunke, Elizabeth↗

Space-time generalization of mutual information

The mutual information characterizes correlations between spatially separated regions of a system. Yet, in experiments we often measure dynamical correlations, which involve probing operators that are also separated in time. Here, we introduce a space-time generalization of mutual information which, by construction, satisfies several natural properties of the mutual information and at the same time characterizes correlations across subsystems that are separated in time. In particular, this quantity, that we call the space-time mutual information, bounds all dynamical correlations. We construct this quantity based on the idea of the quantum hypothesis testing. As a by-product, our definition provides a transparent interpretation in terms of an experimentally accessible setup. We draw connections with other notions in quantum information theory, such as quantum channel discrimination. Finally, we study the behavior of the space-time mutual information in several settings and contrast its long-time behavior in many-body localizing and thermalizing systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Exe-Guard Project

The exe-Guard Project is an alliance between Dominion Virginia Power (DVP), Sandia National Laboratories (SNL), Dartmouth University, and Schweitzer Engineering Laboratories (SEL). SEL is primary recipient on this project. The exe-Guard project was selected for award under DE-FOA-0000359 with CFDA number 81.122 to address Topic Area of Interest 4: Hardened platforms and Systems. The exe-Guard project developed an antivirus solution for control system embedded devices to prevent the execution of unauthorized code and maintain settings and configuration integrity. This project created a white list antivirus solution for control systems capable of running on embedded Linux® operating systems. White list antivirus methods allow only credible programs to run through the use of digital signatures and hash functions. Once a system’s secure state is baselined, white list antivirus software denies deviations from that state because of the installation of malicious code as this changes hash results. Black list antivirus software has been effective in traditional IT environments but has negative implications for control systems. Black list antivirus uses pattern matching and behavioral analysis to identify system threats while relying on regular updates to the signature file and recurrent system scanning. Black list antivirus is vulnerable to zero day exploits which have not yet been incorporated into a signature file update. System scans hamper the performance of high availability applications, as revealed in NIST special publication 1058 which summarizes the impact of blacklist antivirus on control systems: Manual or “on-demand” scanning has a major effect on control processes in that they take CPU time needed by the control process (Sometimes close to 100% of CPU time). Minimizing the antivirus software throttle setting will reduce but not eliminate this effect. Signature updates can also take up to 100% of CPU time, but for a much shorter period than a typical manual scanning process. Control systems are vulnerable to performance losses if off-the-shelf blacklist antivirus solutions aren’t implemented with care. This investment in configuration in addition to constant decommissioning to perform manual signature file updates is unprecedented and impractical. Additionally, control systems are often disconnected or islanded from the network making the delivery of signature updates difficult. Exe-Guard project developed a white list antivirus solution that mitigated the above drawbacks and allows control systems to cost-effectively apply malware protection while maintaining high reliability. The application of security patches can also be minimized since white listing maintains constant defense against unauthorized code execution. Security patches can instead be applied in less frequent intervals where system decommissioning can be scheduled and planned for. Since control systems are less dynamic than IT environments, the feasibility of maintaining a secure baselined state is more practical. Because upgrades are performed in infrequent, calculated intervals, it allows a new security baseline to be established before the system is returned to service. Exe-Guard built on the efforts of SNL under the Code Seal project. SNL demonstrated prototype Trust Anchors on the project which are independent monitoring and control devices that can be integrated into untrustworthy components. The exe-Guard team started with the lessons learned under this project then designed commercial solution for white list malware protection. Malware is a real threat, even on islanded or un-networked installations, since operators can unintentionally install infected files, plug in infected mass storage devices, or infect a piece of equipment on the islanded local area network that can then spread to other connected equipment. Protection at the device level is one of the last layers of defense in a security-in-depth defense model before an asset becomes compromised. This project provided non-destructive intrusion, isolation and automated response solution, achieving a goal of the Department of Energy (DOE) Roadmap to Secure Control Systems. It also addressed CIP-007-R4 which requires asset owners to employ malicious software prevention tools on assets within the electronic security perimeter. In addition, the CIP-007-R3 requirement for security patch management is minimized because white listing narrows the impact of vulnerabilities and patch releases. The exe-Guard Project completed all tasks identified in the statement of project objective and identified additional tasks within scope that were performed and completed within the original budget. The cost share was met and all deliverables were successfully completed and submitted on time. Most importantly the technology developed and commercialized under this project has been adopted by the Energy sector and thousands of devices with exe-Guard technology integrated in them have now been deployed and are protecting our power systems today

24 POWER TRANSMISSION AND DISTRIBUTION↗

Land-Atmosphere Feedback Experiment (LAFE) Science Plan

The Land-Atmosphere Feedback Experiment (LAFE; pronounced “la-fey”) deploys several state-of-the-art scanning lidar and remote sensing systems to the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Southern Great Plains (SGP) site. These instruments will augment the ARM instrument suite in order to collect a data set for studying feedback processes between the land surface and the atmosphere. The novel synergy of remote-sensing systems will be applied for simultaneous measurements of land-surface fluxes and horizontal and vertical transport processes in the atmospheric convective boundary layer (CBL). The impact of spatial inhomogeneities of the soil-vegetation continuum on land-surface-atmosphere (LSA) feedback will be studied using the scanning capability of the instrumentation. The time period of the observations is August 2017, because large differences in surface fluxes between different fields and bare soil can be observed, e.g., pastures versus fields where the wheat has already been harvested. The remote sensing system synergy will consist of three components: 1) The SGP water vapor and temperature Raman lidar (SRL), the SGP Doppler lidar (SDL), and the National Center for Atmospheric Research (NCAR) water vapor differential absorption lidar (DIAL) (NDIAL) mainly in vertical staring modes to measure mean profiles and gradients of moisture, temperature, and horizontal wind. They will also measure profiles of higher-order turbulent moments in the water vapor and wind fields and profiles of the latent heat flux. 2) A novel scanning lidar system synergy consisting of the National Oceanic and Atmospheric Administration (NOAA) High-Resolution Doppler lidar (HRDL), the University of Hohenheim (UHOH) water-vapor differential absorption lidar (UDIAL), and the UHOH temperature Raman lidar (URL). These systems will perform coordinated range-height indicator (RHI) scans from just above the canopy level to the lower troposphere, including the interfacial layer of the CBL. The optimal azimuth is to the ENE of the SGP central facility, which takes advantage of both changes in the surface elevation and different crop types planted along that path. 3) The University of Wisconsin Space Science and Engineering Center Portable Atmospheric Research Center (SPARC) and the University of Oklahoma Collaborative Lower Atmospheric Mobile Profiling System (CLAMPS) operating two vertically pointing atmospheric emitted radiance interferometers (AERIs) and two Doppler lidar (DL) systems scanning cross track to the central RHI for determining the surface friction velocity and the horizontal variability of temperature, moisture, and wind. Thus, both the variability of surface fluxes and CBL dynamics and thermodynamics over the SGP site will be studied for the first time. The combination of these three components will enable us to estimate both the divergence of the latent heat profile and the advection of moisture. Thus, the moisture budget in the SGP domain can be studied. Furthermore, the simultaneous measurements of surface and entrainment fluxes as well as the daily cycle of the CBL thermodynamic state will provide a unique data set for characterizing LSA interaction in dependence of large-scale and local conditions such as soil moisture and the state of the vegetation. The measurements will also be applied for the development of improved parameterizations of surface fluxes and turbulence in the CBL. The latter is possible because mean profiles, gradients, higher-order moments, and fluxes are measured simultaneously. The results will be used for the verification of simulations of LSA feedback in large-eddy simulation (LES) and mesoscale models, which are planned for the SGP site. Due to the strong connection between the pre-convective state of the CBL and the formation of clouds and precipitation, this new generation of experiments will strongly contribute to the improvement of their representation in weather, climate, and earth system models.

Southern Great Plains, atmospheric boundary layer,↗

Measurement and Computation of Supersonic Flow in a Lobed Diffuser-Mixer for Trapped Vortex Combustors

The trapped vortex combustor (TVC) pioneered by Air Force Research Laboratories (AFRL) is under consideration as an alternative to conventional gas turbine combustors. The TVC has demonstrated excellent operational characteristics such as high combustion efficiency, low NO(x) emissions, effective flame stabilization, excellent high-altitude relight capability, and operation in the lean-burn or rich burn-quick quench-lean burn (RQL) modes of combustion. It also has excellent potential for lowering the engine combustor weight. This performance at low to moderate combustor mach numbers has stimulated interest in its ability to operate at higher combustion mach number, and for aerospace, this implies potentially higher flight mach numbers. To this end, a lobed diffuser-mixer that enhances the fuel-air mixing in the TVC combustor core was designed and evaluated, with special attention paid to the potential shock system entering the combustor core. For the present investigation, the lobed diffuser-mixer combustor rig is in a full annular configuration featuring sixfold symmetry among the lobes, symmetry within each lobe, and plain parallel, symmetric incident flow. During hardware cold-flow testing, significant discrepancies were found between computed and measured values for the pitot-probe-averaged static pressure profiles at the lobe exit plane. Computational fluid dynamics (CFD) simulations were initiated to determine whether the static pressure probe was causing high local flow-field disturbances in the supersonic flow exiting the diffuser-mixer and whether shock wave impingement on the pitot probe tip, pressure ports, or surface was the cause of the discrepancies. Simulations were performed with and without the pitot probe present in the modeling. A comparison of static pressure profiles without the probe showed that static pressure was off by nearly a factor of 2 over much of the radial profile, even when taking into account potential axial displacement of the probe by up to 0.25 in. (0.64 cm). Including the pitot probe in the CFD modeling and data interpretation lead to good agreement between measurement and prediction. Graphical inspection of the results showed that the shock waves impinging on the probe surface were highly nonuniform, with static pressure varying circumferentially among the pressure ports by over 10 percent in some cases. As part of the measurement methodology, such measurements should be routinely supplemented with CFD analyses that include the pitot probe as part of the flow-path geometry.

Brankovic, Andreja↗

Threats to a Colorado river provisioning basin under coupled future climate and societal scenarios

Clean, reliable supplies of water are critical to the sustainability and resilience of communities, including water needed for energy and food production, industry, drinking water, and other human and ecological needs. However, water infrastructure and management in the United States are largely optimized for historic conditions—designed and operated to respond to social needs, and past mean and extreme streamflow, which may no longer apply in the future. Temperature, precipitation, ecosystem dynamics, energy and food production, and social systems are all experiencing changes, which cumulatively affect the security of water supply. Here, we examine the impact of these changes in a provisioning basin in the arid Southwest, the San Juan River, which supplies water, food, and energy to the Colorado River and the Rio Grande. Our analysis applies a multi-model framework to examine future climate and water use scenarios. Results demonstrate that the San Juan River basin could experience significant disruptions to water deliveries (-12% to -48% for the drier models) and shortages that exceed manageable thresholds (53% to 73% of water in shorted years), potentially affecting both the local basin as well as other regions that receive water and energy from the San Juan. While water stress metrics vary across the scenarios, results indicate the need for government, industry, and communities to consider options for adapting to water supply shifts. These results raise important questions regarding the resilience of water resources in basins across the West under future scenarios and implications for energy, food, and other water supply needs.

54 ENVIRONMENTAL SCIENCES↗

Light-induced lattice expansion leads to high-efficiency perovskite solar cells

Light-induced structural dynamics plays a vital role in the physical properties, device performance, and stability of hybrid perovskite–based optoelectronic devices. We report that continuous light illumination leads to a uniform lattice expansion in hybrid perovskite thin films, which is critical for obtaining high-efficiency photovoltaic devices. Correlated, in situ structural and device characterizations reveal that light-induced lattice expansion benefits the performances of a mixed-cation pure-halide planar device, boosting the power conversion efficiency from 18.5 to 20.5%. The lattice expansion leads to the relaxation of local lattice strain, which lowers the energetic barriers at the perovskite-contact interfaces, thus improving the open circuit voltage and fill factor. The light-induced lattice expansion did not compromise the stability of these high-efficiency photovoltaic devices under continuous operation at full-spectrum 1-sun (100 milliwatts per square centimeter) illumination for more than 1500 hours.

14 SOLAR ENERGY↗

Cooperative Systems in Presence of Cyber-Attacks: A Unified Framework for Resilient Control and Attack Identification

Here, this paper considers a cooperative control problem in presence of unknown attacks. The attacker aims at destabilizing the consensus dynamics by intercepting the system’s communication network and corrupting its local state feedback. We first revisit the virtual network based resilient control proposed in our previous work and provide a new interpretation and insights into its implementation. Based on these insights, a novel distributed algorithm is presented to detect and identify the compromised communication links. It is shown that it is not possible for the adversary to launch a harmful and stealthy attack by only manipulating the physical states being exchanged via the network. In addition, a new virtual network is proposed which makes it more difficult for the adversary to launch a stealthy attack even though it is also able to manipulate information being exchanged via the virtual network. A numerical example demonstrates that the proposed control framework achieves simultaneously resilient operation and real-time attack identification.

97 MATHEMATICS AND COMPUTING↗

Fluid absorption solar energy receiver

A conventional solar dynamic system transmits solar energy to the flowing fluid of a thermodynamic cycle through structures which contain the gas and thermal energy storage material. Such a heat transfer mechanism dictates that the structure operate at a higher temperature than the fluid. This investigation reports on a fluid absorption receiver where only a part of the solar energy is transmitted to the structure. The other part is absorbed directly by the fluid. By proportioning these two heat transfer paths the energy to the structure can preheat the fluid, while the energy absorbed directly by the fluid raises the fluid to its final working temperature. The surface temperatures need not exceed the output temperature of the fluid. This makes the output temperature of the gas the maximum temperature in the system. The gas can have local maximum temperatures higher than the output working temperature. However local high temperatures are quickly equilibrated, and since the gas does not emit radiation, local high temperatures do not result in a radiative heat loss. Thermal radiation, thermal conductivity, and heat exchange with the gas all help equilibrate the surface temperature.

Bair, Edward J.↗

ENERGY RELEASE AND INITIATION OF A SUNQUAKE IN A C-CLASS FLARE

We present an analysis of the C7.0 solar flare from 2013 February 17, revealing a strong helioseismic response (sunquake) caused by a compact impact observed with the Helioseismic and Magnetic Imager on board the Solar Dynamics Observatory (SDO) in the low atmosphere. This is the weakest known C-class flare generating a sunquake event. To investigate the possible mechanisms of this event and understand the role of accelerated charged particles and photospheric electric currents, we use data from three space observatories: RHESSI, SDO, and Geostationary Operational Environmental Satellite. We find that the photospheric flare impact does not spatially correspond to the strongest hard X-ray emission source, but both of these events are parts of the same energy release. Our analysis reveals a close association of the flare energy release with a rapid increase in the electric currents and suggests that the sunquake initiation is unlikely to be caused by the impact of high-energy electrons, but may be associated with rapid current dissipation or a localized impulsive Lorentz force in the lower layers of the solar atmosphere.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluating the Effect of Vane Trailing Edge Flow on Turbine Rim Sealing

Abstract Modern gas turbine development continues to move toward increased overall efficiency, driven in part by higher firing temperatures that point to a need for more cooling air to prevent catastrophic component failure. However, using additional cooling flow bled from the upstream compressor causes a corresponding detriment to overall efficiency. A primary candidate for cooling flow optimization is purge flow, which contributes to sealing the stator–rotor cavity and prevents ingestion of hot main gas path (MGP) flow into the wheelspace. Previous research has identified that the external main gas path flow physics play a significant role in driving rim seal ingestion. However, the potential impact of other cooling flow features on ingestion behavior, such as vane trailing edge (VTE) flow, is absent in the open literature. This paper presents experimental measurements of rim cavity cooling effectiveness collected from a one-stage turbine operating at engine-representative Reynolds and Mach numbers. Carbon dioxide (CO2) was used as a tracer gas in both the purge flow and vane trailing edge flow to investigate flow migration into and out of the wheelspace. Results show that the vane trailing edge flow does in fact migrate into the rim seal and that there is a superposition relationship between individual cooling flow contributions. Computational fluid dynamics (CFD) simulations using unsteady Reynolds-averaged Navier–Stokes (URANS) were used to confirm VTE flow ingestion into the rim seal cavity. Radial and circumferential traverse surveys were performed to quantify cooling flow radial migration through the main gas path with and without vane trailing edge flow. The surveys confirmed that vane trailing edge flow is entrained into the wheelspace as purge flow is reduced. Local CO2 measurements also confirmed the presence of VTE flow deep in the wheelspace cavity.

Engineering↗

Self-Navigating Robotic Assistant for Long-term Wide Area Floor Contamination Monitoring - 18213

For Routine Contamination Testing (RCT) of an operational nuclear facility or one undergoing Decontamination and Decommissioning (D and D), workers utilize specified travel corridors (enclosed hallways or areas designated with tape or rope in open spaces) to minimize the risk of spreading contamination. Radiation health technicians must continually monitor these areas for contamination to minimize worker dose and prevent its spread to uncontrolled areas. For many sites, it is impractical for the technician to adequately survey such areas. The Nuclear Robotics Group (NRG) at UT Austin has developed a self-navigating robotic platform equipped with radiation detectors to augment the technician to improve both survey coverage and frequency. While maintaining a controlled velocity and floor-to-sensor distance, the system takes radiation measurements to identify and/or localize contamination sources. Readings above background levels are reported to a remote workstation to allow technicians to then respond accordingly. The completion of these mundane tasks by a robot allows the trained technicians to focus instead on operational tasks, D and D, or responding to alarms. The robot generates a map using a Lidar range sensor with established Simultaneous Localization and Mapping (SLAM) techniques. Range data is then compared to previously generated maps for robot localization and autonomous navigation. To maximize coverage, the robot executes a Complete Coverage Path Planning (CCPP) algorithm using a static map that is discretized into cells to assure comprehensive yet efficient coverage. As the system executes the generated plan, it builds a radiation map of the area for the technician to validate and verify the results. If contamination is detected, the robot will minimize the spread of contamination by stopping, sounding an alarm, and alerting the remote technician. The proposed system allows for long-term deployment with minimal human intervention. It is robust to both highly dynamic obstacles (i.e. personnel) and low dynamic changes (i.e. temporally stored cart) in the environment. This is accomplished through continuous spatiotemporal updating of the static map, and the utilization of a supervisory controller that allows the system to reliably respond to unexpected events or states (i.e. low battery, closed door, etc.). While the supervisory controller can respond to temporary complications, the system also recognizes the environment can change slowly over time necessitating that the CCPP automatically be updated to account for observed 'permanent' changes to the environment. To do this, the robot uses intermediate probabilistic data to make intelligent planning decisions offline while still maintaining local reactive obstacle avoidance and safety features. The self-updating of the map allows the robot to run longer without the need to remake the map, leading to more consistent monitoring data and less maintenance from the human technician. This paper will review the current system hardware, the CCPP algorithm, the supervisory controller, the probabilistic algorithm for identifying permanent changes, and recent experiments at UT Austin to experimentally validate the reported sensor coverage. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

TU-CD-BRB-09: Prediction of Chemo-Radiation Outcome for Rectal Cancer Based On Radiomics of Tumor Clinical Characteristics and Multi-Parametric MRI

Purpose: To evaluate the tumor clinical characteristics and quantitative multi-parametric MR imaging features for prediction of response to chemo-radiation treatment (CRT) in locally advanced rectal cancer (LARC). Methods: Forty-three consecutive patients (59.7±6.9 years, from 09/2013 – 06/2014) receiving neoadjuvant CRT followed by surgery were enrolled. All underwent MRI including anatomical T1/T2, Dynamic Contrast Enhanced (DCE)-MRI and Diffusion-Weighted MRI (DWI) prior to the treatment. A total of 151 quantitative features, including morphology/Gray Level Co-occurrence Matrix (GLCM) texture from T1/T2, enhancement kinetics and the voxelized distribution from DCE-MRI, apparent diffusion coefficient (ADC) from DWI, along with clinical information (carcinoembryonic antigen CEA level, TNM staging etc.), were extracted for each patient. Response groups were separated based on down-staging, good response and pathological complete response (pCR) status. Logistic regression analysis (LRA) was used to select the best predictors to classify different groups and the predictive performance were calculated using receiver operating characteristic (ROC) analysis. Results: Individual imaging category or clinical charateristics might yield certain level of power in assessing the response. However, the combined model outperformed than any category alone in prediction. With selected features as Volume, GLCM AutoCorrelation (T2), MaxEnhancementProbability (DCE-MRI), and MeanADC (DWI), the down-staging prediciton accuracy (area under the ROC curve, AUC) could be 0.95, better than individual tumor metrics with AUC from 0.53–0.85. While for the pCR prediction, the best set included CEA (clinical charateristics), Homogeneity (DCE-MRI) and MeanADC (DWI) with an AUC of 0.89, more favorable compared to conventional tumor metrics with an AUC ranging from 0.511–0.79. Conclusion: Through a systematic analysis of multi-parametric MR imaging features, we are able to build models with improved predictive value over conventional imaging or clinical metrics. This is encouraging, suggesting the wealth of imaging radiomics should be further explored to help tailor the treatment into the era of personalized medicine. This work is supported by the National Science Foundation of China (NSFC Grant No. 81201091), National High Technology Research and Development Program of China (863 program, Grant No. 2015AA020917), and Fund Project for Excellent Abroad Scholar Personnel in Science and Technology.

60 APPLIED LIFE SCIENCES↗