SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
We describe how LDMS is being used to collect application data concurrent with system data and how the low-latency availability of this data for analysis can be used for real-time data analysis and feedback in order to support efficient, resilient, and reliable system operations. Finally, we will describe current related research areas.
The Deep Underground Neutrino Experiment (DUNE) will employ a uniquely large Liquid Argon Time Projection Chamber with four separate modules of 10kt fiducial mass each. Different modules will utilize single and dual-phase Liquid Argon technologies. An experimental program ("protoDUNE") has been initiated which includes a beam and cosmic ray test of large-scale DUNE prototypes at CERN in 2018. The volume of data to be collected by the protoDUNE single-phase detector will amount to a few petabytes and the sustained rate of data sent to mass storage will be in the range of a few hundred megabytes per second. The protoDUNE experiment requires substantial Data Quality Monitoring capabilities in order to ascertain the condition of the detector and its various subsystems. To this end, a Prompt Processing system has been developed which is complementary to Online Monitoring and is characterized by a lower bandwidth, scalable CPU resources and end-to-end latency on the scale of a few minutes. We present the design of the protoDUNE Prompt Processing system, the current status of its development and testing and issues related to its interfaces and deployment.
A model-dependent method is proposed to determine the location of the γ -ray-emitting region for a given flat spectrum radio quasar (FSRQ). In the model, the extra-relativistic electrons are injected at the base of the jet and non-thermal photons are produced by both synchrotron radiation and inverse-Compton (IC) scattering in the energy dissipation region. The target photons dominating IC scattering originate from both synchrotron photons and external ambient photon fields, and the energy density of external radiation field is a function of the distance between the position of the dissipation region and a central supermassive black hole, and their spectra are seen in the comoving frame. Moreover, the energy dissipation region could be determined by the model parameter through reproducing the γ -ray spectra. Such a model is applied to reproduce the quasi-simultaneous multi-wavelength observed data for 36 FSRQs. In order to define the width of the broad-line region (BLR) shell and dusty molecular torus (MT) shell, a simple numerical constraint is used to determine the outer boundary of the BLR and dusty MT. Our results show that (1) the γ -ray-emitting regions are located at the range from 0.1 to 10 pc; (2) the γ -ray-emitting regions are located outside the BLRs and within the dusty molecular tori; and (3) the γ -ray-emitting regions are located closer to the dusty MT ranges than the BLRs. Therefore, it may be concluded that direct evidence for the far site scenario could be obtained on the basis of the model results.
In order to complement the precipitation data collected as part of the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Measurements of Aerosols, Radiation, and Clouds over the Southern Ocean (MARCUS) campaign deployment aboard our Australian Antarctic Division (AAD) icebreaker Aurora Australis during summer 2017/18, we installed a Metek Micro Rain Radar (MRR-PRO model) and an Eigenbrodt OceanRAIN disdrometer on the monkey island. Biases in absorbed shortwave radiation over the Southern Ocean in numerical models compared to observations are most likely associated with biases in the representation of cloud microphysical properties such as liquid cloud droplet concentration and liquid water path that can be assessed by understanding precipitation together with cloud phase. The addition of these two AAD instruments will, together with MARCUS, enable studies relating precipitation and cloud properties (drop size distribution, number concentration, and modal diameter) to aerosol properties over the Southern Ocean. We deployed the disdrometer for all four voyages of Aurora Australis during summer 2017/18. The MRR was installed on Voyage 1 (Davis Base resupply) and again on Voyage 4 (Macquarie Island resupply), but was removed for the other two voyages due to commitments elsewhere. Instead of using up one ship’s expeditioner berth for our own technician to monitor these instruments, we asked the ARM technicians, through the ARM field campaign office, to monitor data collection of the MRR and disdrometer and notify me of any issues. The MRR performed well on the voyages and collected data nearly continuously. However, the disdrometer’s performance was very disappointing, with very little data collected at all. This seems due to instrumental faults; indeed we thank the ARM technicians who performed as much technical diagnostics as were possible while aboard.
In order for the analysis of data from the tracking detector to reduce the systematic uncertainty on the a_μ measurement and improve the sensitivity to a muon electric dipole moment, the internal position of the tracking modules must be known to a high level of precision. Track-based alignment was implemented with data from Run 1 using the Millepede II framework. An overview of the alignment methods, as well as the verification of alignment with simulation, will be given. A significant improvement in the mean p-value distribution and the fraction of reconstructed tracks after the alignment was achieved. A comparison of the accuracy in the determination of the beam's spatial distribution as a function of time will be presented before and after the alignment.
A chloride-based molten-salt system that uses a ternary blend of MgCl2/KCl/NaCl is investigated to provide higher temperature thermal energy storage capability. Despite higher thermal stability, molten chlorides present several unique challenges, including the design of internal refractory-ceramic liners to prevent the corrosion and thermal stress of alloy tank shells. This work discusses issues and potential solutions related to containment of molten chloride salt, specifically the optimization of the refractory material at the molten salt interface (hot face). The down-selected hot face candidate limits permeation of salt through the material and forms a highly stable secondary surface phase in equilibrium with the molten salt. A mortar is created using the corrosion resistant hot face brick. Brick and mortar composite are subjected to mechanical stress/strain analysis, in order to calculate composite material properties and better inform thermomechanical models. The U.S. Department of Energy Generation 3 (DOE Gen3) program seeks to develop higher efficiency CSP plants that can provide cost-competitive, flexible power in the U.S. electric grid. The proposed Gen3 Liquid Pathway CSP plant closely resembles the configuration of current nitrate salt power towers with two-tank storage (Gen2). The differences between Gen2 and Gen3 include the types of compatible materials used in salt storage tank construction. Stainless steel loses strength at Gen3 temperatures, and although nickel superalloys would be capable of withstanding sustained high temperatures, these materials are prohibitively expensive at scale. Uninsulated tank shells also pose a significant risk as common steels are highly susceptible to chemical attack from molten chloride salt. To address these concerns, refractory-ceramic based containment materials are proposed to line the inside of the hot and cold storage tanks. In doing so, stainless or carbon steel shells may be used in construction depending on the level of insulation provided. The composition of the internal liner requires careful consideration to maximize the efficacy of multiple parameters including corrosion resistance, strength at operating temperature, durability, and cost. This is particularly true for the material at the interface with the salt, known as the "hot face", which is responsible for protecting the insulating layers between the tank shell and the hot face brick layer. The molten salt in this system is superheated over 300 °C above its freeze temperature. Therefore, unlike other industrial processes which use refractory-lined vessels, it is not expected that a freeze plane will develop in the hot face. Therefore, the hot face must be designed to withstand chemical corrosion and inhibit permeation of molten salt into the insulating layers. A down selection was performed to identify a hot face candidate best equipped to maintain thermal, mechanical, and chemical integrity when exposed to molten salt over extended periods of time. Long-duration chemical capability experiments were conducted with the down selected hot face refractory fully immersed in molten chloride salt for up to 3000 hours. The average salt penetration does not exceed 100 microns. When extrapolated to 20 and 30 years of continuous exposure, the expected salt penetration depth is approximately 2.0 mm and 2.9 mm, respectively. A magnesium-rich secondary phases develops at the salt/refractory interface. X-ray diffraction identifies the material as forsterite (Mg2SiO4), which is reported to form synthetically in molten chloride salt solutions. These results suggest the selected hot face will adequately inhibit salt permeation. While there is optimism that the hot face brick will inhibit salt permeation, mortar joints are typically the weakest point of a refractory brick liner. From a thermochemical perspective, differing thermal expansion coefficients may result in the mortar and brick to grow independent of each other, creating gaps through which molten salt can penetrate. To address this issue, NREL has developed an in-house mortar composed of the down selected hot face brick that has been shown to be compatible with the salt. Compressive stress/strain analyses have been performed on the brick/ mortar composites to generate stress/strain curves. Modulus of elasticity and Poisson's ratio of the composite may be calculated from the stress/strain curves, in order to provide more representative data to finite element mechanical models for accurate approximation of stress on the tank shell and the amount of thermal expansion expected within the tank liner.
The Working Party on the Scientific Issues of the Fuel Cycle (WPFC) has been established under the auspices of the Nuclear Energy Agency (NEA) Nuclear Science Committee (NSC), to co-ordinate scientific activities regarding various existing and advanced nuclear fuel cycles, including advanced reactor systems, associated chemistry and flowsheets, development and performance of fuels and materials, accelerators and spallation targets. Various expert groups were established to cover the above-mentioned topics. Within the WPFC, the Expert Group on Innovative Fuels (EGIF) was created with the objective of conducting joint and comparative studies to support the development of innovative fuels such as homogeneous and heterogeneous fuels, ADS fuels, and oxide, metal, nitride and carbide fuels, all of which can be implemented in advanced nuclear fuel cycles with fast reactors. The scope of the expert group covers innovative fuel fabrication techniques, irradiation performance of innovative fuels, characterisation and post-irradiation examination methods and predictive codes for innovative fuel fabrication and performance. This report presents the results of a benchmark study on innovative fuels for fast reactors using fuel performance codes. Irradiation results were shared among participants, and code calculations were performed to gain further insights on the fuel behaviour. Each participating institution used its own fuel performance code. Code to code and code to experiment comparisons are expected to provide data and improve understanding on the effects of minor actinides on fuel behaviour. In conclusion, the need for improvement of codes will be evaluated and the needs for new experimental data will be identified in order to finalise the code validation.
The extremely harsh conditions of advanced reactor designs pose serious challenges for nuclear fuels and materials. Traditional instrumentation (thermocouples, strain gauges, etc.) are not well suited for extended operation in such a harsh environment. This work discusses the potential for using fiber optic-based instrumentation in high temperature irradiation experiments. The primary limitation of fiber optic instrumentation in irradiation experiments is signal darkening due to attenuation in the fiber material. A computational model has been developed to predict broadband optical attenuation in fused silica fiber materials as a function of time, temperature, and dose. Preliminary results obtained using this model are shown for one cycle of irradiation in the high flux isotope reactor at various temperatures. An irradiation campaign has been initiated to provide temperature-dependent optical attenuation data at high dose in order to validate the predictive model. Demonstration of the safety and reliability of new and enhanced nuclear fuels and materials is essential for improving the safety and reliability of existing nuclear power plants and for the licensing and operation of advanced nuclear reactor technologies. Experimental validation of fuel performance codes requires high fidelity measurements during instrumented irradiation experiments. Therefore, a clear need exists for sensors of unprecedented accuracy, resolution, time/space/energy spectrum dependence, reduced size, and, perhaps most importantly, performance in harsh environments. The harsh environment during accelerated irradiation testing could include temperatures from 300 deg. C up to 2600 deg. C, and radiation damage levels ranging from 1 to greater than 100 dpa. Optical fiber-based sensors are a promising candidate for instrumentation in high temperature irradiation environments. Optical fibers are small, inexpensive, chemically inert, immune to electromagnetic interference, and made of high temperature radiation-hard materials. The ability to make distributed measurements of temperature or strain using a single inexpensive optical fiber currently exists for non-extreme environments as commercially available technology. Other advanced sensing technologies such as laser ultrasound, borescopes, and laser-induced breakdown spectroscopy use fiber optic light delivery as a critical component of the sensor design. Some potential applications for optical fiber-based sensors in instrumented irradiation experiments include in-situ measurements of thermal conductivity, ultrasonic measurement of elastic constants (with fiber optic delivery of signal for generation and detection of ultrasonic wave), and distributed measurements of temperature and/or strain (i.e., swelling). The primary limitation for the use of optical technologies for harsh environment (e.g., high neutron flux reactor environments) instrumentation is the attenuation of the light signal due to the effects of temperature and/or irradiation. This work summarizes initial efforts towards developing a predictive model of temperature-dependent radiation-induced attenuation in fused silica optical fibers at high dose. If there is adequate transmission in the fibers, fiber optic-based instrumentation could provide highly accurate distributed measurements during instrumented fuel/material irradiation experiments. Preliminary results show attenuation on the order of 5- 10 dB/m in the wavelength range of 750-900 nm at temperatures of 300 deg. C and below after one HFIR cycle (24 days). At higher temperatures (600 and 900 deg. C), the attenuation is reduced below 5 dB/m in the same wavelength range. This amount of attenuation is acceptable for most fiber optic based sensor systems with a dynamic range on the order of 20-50 dB for a reasonable length (1-2 meters) of fiber in the high flux region. Many optical components use a wavelength of 850 nm, which lies in the low attenuation window. In order to refine and ultimately validate the predictive model of optical fiber attenuation, a reactor irradiation campaign has been initiated. Rabbit irradiation capsules have been designed to irradiate optical fiber material (low and high OH fused silica, as well as single crystal sapphire) specimens in the HFIR at temperatures ranging from 100 to 1200 deg. C. (authors)
Miles of contaminated pipe must be characterized as part of the decommissioning effort at deactivated gaseous diffusion enrichment facilities. The current method requires cutting away asbestos- lined thermal enclosures and performing repeated, elevated operations to manually perform nondestructive assay (NDA) on pipe from the outside. The RadPiper robot, part of the Pipe Crawling Activity Measurement System (PCAMS) developed by Carnegie Mellon University and commissioned for use at the DOE Portsmouth Gaseous Diffusion Enrichment Facility, automatically measures U-235 in pipes from the inside. This improves certainty, increases safety, and greatly reduces measurement time. The heart of the RadPiper robot is a sodium iodide scintillation detector in an innovative disc-collimated assembly. By measuring from inside pipes, the robot significantly increases its count rate relative to external through-pipe measurements. The robot also provides imagery, models interior pipe geometry, and precisely measures distance in order to localize radiation measurements. Data collected by this system provides insight into pipe interiors that is simply not possible from exterior measurements, all while keeping operators safer. This paper describes the technical details of the PCAMS RadPiper robot. Key features for this robot include precision distance measurement, in-pipe obstacle detection, ability to transform for two pipe sizes, and robustness in autonomous operation. Test results demonstrating the robot's functionality are presented, including deployment tolerance tests, safeguarding tests, and localization tests. Integrated robot tests are also shown. (authors)
A modification program of the Static Experiment Critical Facility, STACY is now undergoing in Japan Atomic Energy Agency, JAEA, in order to accumulate fundamental critical data relating the critical control technology for fuel debris treatment in the Fukushima Daiichi Nuclear Power Station, 1FNPS. In accordance with the new regulatory requirement for research reactors established by Nuclear Regulation Authority of Japan, NRA in December 2013, fundamental design policies and basic nuclear properties of STACY have been confirmed for the critical experiments which are oriented to research on criticality control in the 1FNPS. Reactivity control in the STACY experiments is made by adjusting the water level in a core tank. The moderating ratio of the heterogeneous system which determines neutron spectrum can be adjusted by changing lattice plates. Safety review by NRA for revised basic design started in March, 2015. This paper described main specifications of experimental cores for license procedure, the availability of re activity control system, and the range of nuclear characteristics such as reactivity control, reactivity coefficients and kinetic parameters, which dominate static and transient characteristics of the STACY cores. (authors)
Single crystals of EuCu 2 As 2 and EuCu 2 Sb 2 were grown from CuAs and CuSb self-flux, respectively. The crystallographic, magnetic, thermal, and electronic transport properties of the single crystals were investigated by room-temperature x-ray diffraction (XRD), magnetic susceptibility χ versus temperature T, isothermal magnetization M versus magnetic field H, specific heat C p (T), and electrical resistivity ρ(T) measurements. EuCu 2 As 2 crystallizes in the body-centered tetragonal ThCr 2 Si 2 -type structure (space group I4/mmm), whereas EuCu 2 Sb 2 crystallizes in the related primitive tetragonal CaBe 2 Ge 2 -type structure (space group P4/nmm). The energy-dispersive x-ray spectroscopy and XRD data for the EuCu 2 Sb 2 crystals showed the presence of vacancies on the Cu sites, yielding the actual composition EuCu 1.82 Sb 2 . The ρ(T) and C p (T) data reveal metallic character for both EuCu 2 As 2 and EuCu 1.82 Sb 2 . Antiferromagnetic (AFM) ordering is indicated from the χ(T),C p (T), and ρ(T) data for both EuCu 2 As 2 (T N = 17.5 K) and EuCu 1.82 Sb 2 (T N = 5.1 K). In EuCu 1.82 Sb 2 , the ordered-state χ(T) and M(H) data suggest either a collinear A-type AFM ordering of Eu +2 spins S = 7/2 or a planar noncollinear AFM structure, with the ordered moments oriented in the tetragonal ab plane in either case. This ordered-moment orientation for the A-type AFM is consistent with calculations with magnetic dipole interactions. As a result, the anisotropic χ(T) and isothermal M(H) data for EuCu 2 As 2 , also containing Eu +2 spins S = 7/2, strongly deviate from the predictions of molecular field theory for collinear AFM ordering and the AFM structure appears to be both noncollinear and noncoplanar.
We have measured, analyzed and simulated the ground state valence photoelectron (PES), X-ray absorption (XAS), X-ray photoelectron (XPS) as well as normal and resonant Auger-Meitner electron (AES) spectra of oxazole at the carbon, oxygen and nitrogen K-edge in order to understand its electronic structure. Experimental data is compared to theoretical calculations performed at the coupled cluster, restricted active space perturbation theory to second order and time-dependent density functional levels of theory. We demonstrate that both N and O K-edge XAS are sensitive to the amount of dynamical electron correlation included in the theoretical description, and that for a complete description of XPS, additional orbital correlation and orbital relaxation effects need to be considered. The normal AES are dominated by a singlet excitation channel and well described by theory. Furthermore, the resonant AES, however, are more complicated. While the participator decay channels, dominating at higher kinetic energies, are well described by coupled cluster theory, spectator channels can only be described satisfactorily using a method that combines restricted active space perturbation theory to second order for the bound part and a one-center approximation for the continuum.
An essential aspect of online monitoring, subtle anomaly detection increases the detection lead time for equipment failure and enables a nuclear power plant (NPP) to mitigate unexpected partial or full outages, resulting in significant cost saving to the plant. Once an anomaly is detected by plant staff, its cause and severity are investigated. Because the vast majority of anomalies require some level of investigation, including some that require time-consuming examination, before they are passed over to the engineering organization for further analysis, plants are often equipped with tools to assist the staff in performing anomaly detection. Those tools operate as a black box and are often based on statistical methods that establish sensor correlations using preconfigured mathematical models and flag correlation deviations as anomalies. Due to the number of anomalies detected at a given NPP on a daily basis, a significant number of flagged anomalies usually await examination for days or weeks. A primary cause of this backlog is that the methods used by the tools generate many false positives. Though this is usually attributed to oversensitive model settings due to very narrow normal operation bands, it can also be associated with the model development being inadequate for the process being monitored, or with missing model inputs that could have explained misclassified positives. The performance of anomaly detection tools impacts their plant acceptance and utilization, especially when the effort to address false positives generated by the tool depletes the value or cost saved by using that tool. Thus, means to advance anomaly detection performance have been investigated by the Department of Energy’s Light Water Reactor Sustainability program. Previous and ongoing efforts have targeted unsupervised machine-learning (ML) methods, which do not require the labeling of any data fed into the ML model. By contrast, in supervised anomaly detection methods, every data point is labeled as either a normal or abnormal process condition, and the model is trained to replicate the classification process. Supervised methods usually outperform unsupervised methods, due to the added value in differentiating normal from anomalous states of the monitored process. An NPP’s corrective action program requires it to track and document, via a dedicated report, the resolution of any issues that occur within the plant. Once created, each report is reviewed by a plant screening committee, and several classifications and decisions are made. Recently, a collaborating NPP developed an artificial intelligence and ML-based classifier to categorize a condition report (CR) into classes that can serve to label the data as normal or anomalous. Applying CRs as labels represents a semi-supervised use case. Semi-supervised ML assumes that labels exist for some data points (i.e., labeled anomalies, in this case) but not for the rest. In this effort, semi-supervised ML methods were used to fuse data from CRs with anomaly detection methods in order to test the hypothesis that partially labeled anomalies would improve the accuracy of the anomaly detection methods. Specifically, two methods were used. The first is the deep Semi-supervised Anomaly Detection (deep SAD) method, which can handle labels ranging from fully unsupervised to fully supervised cases. The second is a newly designed ML method developed specifically for this effort and referred to as the high-order feature (HOF)-based method. To evaluate these two methods in controlled environments, synthetic data generators were developed and used. The first datasets used a spring-mass-damper (SMD) system simulator commonly found in mechanical engineering references. This was used to create two use cases: a one- and a three-mass system. Anomalies were introduced by changing the spring and damper coefficients while the system was actuated by random forces. The second datasets used the commercial Dymola-Modelica software to build a simplified nuclear reactor model. Anomalies were added in the form of corrupted sensor readings and/or control commands. The deep SAD method was tested using the SMD system, while the HOF method was tested using both datasets. Application of the deep SAD semi-supervised ML method demonstrated that labels can generate increased confidence in detecting true anomalies. This helped increase the number of true positives and decrease the number of false negatives—something that would aid in addressing the backlog of possible anomalies. Application of the HOF method demonstrated that labels can aid in down selecting from a candidate set of features to a more optimal subset in order to better differentiate between normal and anomalous conditions.
Due to mandates from recent legislation, clinical decision support (CDS) software is being adopted by radiology practices across the country. This software provides imaging study decision support for referring providers at the point of order entry. CDS systems produce a large volume of data, providing opportunities for research and quality improvement. In order to better visualize and analyze trends in this data, an interactive data visualization dashboard was created using a commercially available data visualization platform. Following the integration of a commercially available clinical decision support product into the electronic health record, a dashboard was created using a commercially available data visualization platform (Tableau, Seattle, WA). Data generated by the CDS were exported from the data warehouse, where they were stored, into the platform. This allowed for real-time visualization of the data generated by the decision support software. The creation of the dashboard allowed the output from the CDS platform to be more easily analyzed and facilitated hypothesis generation. Integrating data visualization tools into clinical decision support tools allows for easier data analysis and can streamline research and quality improvement efforts.
An understanding of the mechanical and optical properties of lithium fluoride (LiF) is essential to its use as a transparent tamper and window for dynamic materials experiments. In order to improve models for this material, we applied iterative Lagrangian analysis to ten independent sets of data from magnetically driven planar shockless compression experiments on single crystal [100] LiF to pressures as high as 350 GPa. We found that the compression response disagreed with a prevalent tabular equation of state for LiF that is commonly used to interpret shockless compression experiments. We also present complementary data from ab initio calculations performed using the diffusion quantum Monte Carlo method. The agreement between these two data sets lends confidence to our interpretation. In order to aid in future experimental analysis, we have modified the tabular equation of state to match the new data. We have also extended knowledge of the optical properties of LiF via shock-compression and shockless compression experiments, refining the transmissibility limit, measuring the refractive index to ~300 GPa, and confirming the nonlinear dependence of the refractive index on density. Lastly, we present a new model for the refractive index of LiF that includes temperature dependence and describe a procedure for correcting apparent velocity to true velocity for dynamic compression experiments.
Systematic measurements of temperature-dependent magnetization, resistivity, and angle-resolved photoemission spectroscopy (ARPES) at ambient pressure as well as resistivity under pressures up to 5.25 GPa were conducted on single crystals of CrAuTe 4 . Magnetization data suggest that magnetic moments are aligned antiferromagnetically along the crystallographic c axis below T N = 255 K. ARPES measurements show band reconstruction due to the magnetic ordering. Magnetoresistance data show clear anisotropy, and, at high fields, quantum oscillations. The Néel temperature decreases monotonically under pressure, decreasing to T N = 236 K at 5.22 GPa. The pressure dependencies of (i) T N , (ii) the residual resistivity ratio, and (iii) the size and power-law behavior of the low-temperature magnetoresistance all show anomalies near 2 GPa suggesting that there may be a phase transition (structural, magnetic, and/or electronic) induced by pressure. Lastly, for pressures higher than 2 GPa a significantly different quantum oscillation frequency emerges, consistent with a pressure induced change in the electronic states.
Neutrinos from very nearby supernovae, such as Betelgeuse, are expected to generate more than ten million events over 10 s in Super-Kamokande (SK). At such large event rates, the buffers of the SK analog-to-digital conversion board (QBEE) will overflow, causing random loss of data that are critical for understanding the dynamics of the supernova explosion mechanism. In order to solve this problem, two new data-acquisition (DAQ) modules were developed to aid in the observation of very nearby supernovae. The first of these, the SN module, is designed to save only the number of hit photomultiplier tubes during a supernova burst and the second, the Veto module, prescales the high-rate neutrino events to prevent the QBEE from overflowing based on information from the SN module. In the event of a very nearby supernova, these modules allow SK to reconstruct the time evolution of the neutrino event rate from beginning to end using both QBEE and SN module data. This paper presents the development and testing of these modules together with an analysis of supernova-like data generated with a flashing laser diode. We demonstrate that the Veto module successfully prevents DAQ overflows for Betelgeuse-like supernovae as well as the long-term stability of the new modules. During normal running the Veto module is found to issue DAQ vetos a few times per month resulting in a total dead-time less than 1 ms, and does not influence ordinary operations. Additionally, using simulation data we find that supernovae closer than 800 pc will trigger the Veto module, resulting in a prescaling of the observed neutrino data.
In this work, we present a parallel computing strategy for a hybridizable discontinuous Galerkin (HDG) nested geometric multigrid (GMG) solver. Parallel GMG solvers require a combination of coarse-grain and fine-grain parallelism to improve time-to-solution performance. In this work we focus on fine-grain parallelism. We use Intel's second generation Xeon Phi (Knights Landing) manycore processor. The GMG method achieves ideal convergence rates of 0.2 or less, for high polynomial orders. A matrix free (assembly free) technique is exploited to save considerable memory usage and increase arithmetic intensity. HDG enables static condensation, and due to the discontinuous nature of the discretization, we developed a matrix vector multiply routine that does not require any costly synchronizations or barriers. Our algorithm is able to attain 80% of peak bandwidth performance for higher order polynomials. This is possible due to the data locality inherent in the HDG method. Very high performance is realized for high order schemes, due to good arithmetic intensity, which declines as the order is reduced.