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DOE OSTI2018

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↗

DOE OSTI2016

Comparing Thick Target Neutron Yield Calculations for Alphas on F-19 using MCNP6 1.1 Beta with TENDL 2012 Libraries

Because of the heritage of MCNPX, the first production release of MCNP6{sup TM} used physics models, instead of ACE (A Compact Evaluated Nuclear Data File) formatted libraries, for simulating the transport of alpha particles at all energies, as MCNPX could not yet read ACE formatted light ion libraries. For non-Coulombic interactions, the physics models have suggested minimums of ∼ 20-200 MeV. The first production release of MCNP6, MCNP6{sup TM} 1.0, was still capable of transporting alphas to low energies; however, the physics models resulted in poor prediction of inelastic reactions at energies below the suggested minimums. This poorer prediction at low energies resulted in orders of magnitude lower neutron yields for events resulting from light ion interactions at low energies. For example, F-19(α,n)Na-22 from U-234 decay in UF{sub 6} produced poor neutron production results. Modeling these types of interactions correctly is vital for signal analysis for nonproliferation safeguards and nuclear security as well as for correctly characterizing source terms for radiation protection and shielding calculations. The TALYS computer code was developed to simulate nuclear reactions involving neutrons, photons, protons, deuterons, tritons, alphas and He-3 particles, in the 1 keV - 200 MeV energy range. TENDL is a nuclear data library, which provides the output of the TALYS nuclear model code system for direct use in applications (i.e. ACE formatted cross sections). Since 2008, TENDL had publicly provided ACE formatted libraries for alpha transport; however, not until the release of MCNP6{sup TM} 1.1 beta, had MCNP6 publicly possessed the capability to read such libraries. At the Radiation Protection and Shielding Division topical meeting in 2014, initial testing of MCNP6 1.1 beta showed that MCNP6 using TENDL 2012 resulted in poor prediction when compared to the compilation of experiment data provided in R. Heaton et al. Further comparisons for PuBe sources, using the MCNP6 1.1 beta spontaneous decay alpha feature coupled with alpha transport, were also given in the winter American Nuclear Society meeting in 2014, where the results showed large discrepancies with measured data. For F-19(α,n)Na-22 interactions, the R. Heaton et al. paper is a conglomeration of several important references; and the data provided by R. Heaton et al. used a numerical fit of the excitation function provided by Norman et al.. Norman et al. has recently published their (α,n) thick target yield data for PbF{sub 2} in tabular form, backing out the thick target yields of F-19(α,n)Na-22 and computing F{sub 2} and UF{sub 6} thick target neutron yields (as supplements to the PbF{sub 2} data). Here we compared measured thick target yields of E. B. Norman et al. to MCNP6 1.1 beta using TENDL 2012 libraries. Deterministically backing out the thick target yield from measured values involves using the stopping power. MCNP uses either the SPAR code or an interpolation of the Spar code and Bethe-Boch formula for computing stopping powers. As a result one may believe that these separate methods will arrive at separate thick target yields independent of the production cross section. In our MCNP calculations, we simulated the alpha until the alpha completely stopped in the medium. The energy loss in the condensed history algorithm is not continuous but discrete and related to the stopping powers. Because the neutron production yield is energy dependent, the energy loss dictates the emission of secondary neutrons; and therefore the difference in stopping powers used may have some slight effect on the yield difference. For this study, we chose to use the default condensed history algorithm setup, while future studies should address tightening steps in the condensed history algorithm to prove whether or not choice of stopping power actually matters. The fact that all 5 evaluated isotopic compositions resulted in different thick target yield percent differences does warrant this type of investigation. A typical user may not be only interested in integral emission, taking 10 s to 100 s of processor hours to simulate, but rather a timely generation of the spectra. Such an application would require biasing the production of secondaries from alpha sources such that millions of secondaries could be produced, emulating a converged energy dependent spectra. Neutron production biasing from alpha sources does not currently exist; however, developing a biasing algorithm for neutron production from alpha sources should be investigated in the future.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2015

The Center for Momentum Transport and Flow Organization in Plasmas - Final Scientific Report

Overview of University of Colorado Efforts: The University of Colorado group has focused on two primary fronts during the grant period: development of a variety of multi-point diagnostic and/or imaging analysis techniques, and momentum-transport related experiments on a variety of devices (NSTX at PPPL, CSDX at UCSD, LAPD at UCLA, DIII-D at GA). Experimental work has taken advantage of several diagnostic instruments, including fast-framing cameras for imaging of electron density fluctuations (either directly or using injected gas puffs), ECEI for imaging of electron temperature fluctuations, and multi-tipped Langmuir and magnetic probes for corroborating measurements of Reynolds and Maxwell stresses. Mode Characterization in CSDX: We have performed a series of experiments at the CSDX linear device at UCSD, in collaboration with Center PI G. Tynan's group. The experiments included a detailed study of velocity estimation techniques, including direct comparisons between Langmuir probes and image-based velocimetry from fast-framing camera data. We used the camera data in a second set of studies to identify the spatial and spectral structure of coherent modes, which illuminates wave behavior to a level of detail previously unavailable, and enables direct comparison of dispersion curves to theoretical estimates. In another CSDX study, similar techniques were used to demonstrate a controlled transition from nonlinearly coupled discrete eigenmodes to fully developed broadband turbulence. The axial magnetic field was varied from 40-240 mT, which drove the transition. At low magnetic fields, the plasma is dominated by drift waves. As the magnetic field is increased, a strong potential gradient at the edge introduces an ExB shear-driven instability. At the transition, another mode with signatures of a rotation-induced Rayleigh–Taylor instability appears at the central plasma region. Concurrently, large axial velocities were found in the plasma core. For larger magnetic fields, all of the instabilities co-exist, leading to rich plasma dynamics and fully developed broadband turbulence. Edge-Turbulence and Flow Experiments in NSTX: A series of Gas Puff Imaging (GPI) observations on NSTX revealed a quasi-periodic oscillation in the plasma edge preceding the L-H transition in a limited set of neutral beam heated plasmas. These ~3 kHz flow oscillations exhibit both long wavelength and long correlation lengths, suggesting they are zonal-flow-like. The flow oscillations are strongly correlated with modulations of the level of edge turbulence, thus the system appears to undergo a predator--prey-type limit-cycle preceding the L-H transition. However, a clear trigger for the L-H transition was not observed. Reynolds stress profiles were obtained directly from image velocimetry for L-mode periods ELM-Precursor Studies in NSTX: A separate study based on NSTX-GPI data captured the two-dimensional evolution of edge-localized mode (ELM) precursors. Precursor events were observed preceding ELMs and ELM-induced H–L back-transitions in radio-frequency heated H-mode plasmas, and the growth of the precursor mode through the ELM filamentation was imaged in the plane perpendicular to the local B-field. Strong edge intensity modulations appeared to propagate in the electron diamagnetic direction while steadily drifting radially outwards. Intensity fluctuations were observed at frequencies around 20 kHz and wavenumbers of 0.05-0.2 cm -1 . Upon growing to a trigger point, precursor fluctuations were seen to form filamentary structures and move into the scrape-off layer (SOL) explosively with radial velocities peaking at 8 km/s. Once in the SOL, filaments reverse their propagation direction and travel in the ion diamagnetic direction. Edge intensity fluctuations were strongly correlated with magnetic signals from Mirnov coils, and toroidally distributed coils estimated toroidal mode numbers of n=5-10. Quantitatively similar precursors have been observed in ohmic H-mode plasmas as well, though significantly fewer events are seen in the ohmic cases and none were observed in the near-threshold NBI H-modes studied. Development of Velocimetry and Image Analysis Techniques: Along with the experiments listed above, the Colorado group has continued to explore various velocimetry techniques and their range of validity. We have developed a “linear optical flow” code, which calculates smooth velocity maps while accurately assessing local regions of high curl. This is critical for separating spatial scales of velocity behavior, and thus transport. This code has recently come on-line, and we are currently using it to revisit a number of older datasets. Additionally, we have worked on developing pattern-recognition techniques for imaging diagnostics, based on established digital image compression algorithms. This has the potential to open the analysis of turbulent plasma behavior beyond the well-trodden Fourier and wavelet approaches. Finally, we have extended several of these image-analysis routines to multiple other diagnostic sets, including GPI datasets in NSTX and ECEI imaging on DIII-D. In one study, correlation maps were used to measure the full 2-D mode structure of drift-wave level structures using ECEI for the first time. This enabled direct comparison to gyrokinetic simulations using the GEM code, from which is was determined that TEM modes were being measured in DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗