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At least 325 records · Page 18

Wood Decomposition: Understanding Processes Regulating Carbon Transfer to Soil Carbon Pools Using FACE Wood at Multiple Scales

Dead wood comprises approximately 20% of forest biomass. While it is widely recognized for its role in ecosystem functions relative to habitat and nutrient cycling, there are considerable uncertainties associated with its role in the forest carbon (C) cycle. The principal uncertainty is whether dead wood contributes to the soil C pool. With little supporting evidence, the presumption is that C in wood is respired back to the atmosphere through decomposition processes. The inability to attribute forest soil C to its source components has been a barrier to addressing this important forest carbon cycle question. The U.S. Dept. of Energy’s Free Air CO 2 Enrichment (FACE) experiment produced wood that has a distinct δ 13 C signature that can be used to trace its fate through organic matter decomposition processes. Using two hardwood species (aspen, birch) from the Rhinelander FACE site and pine from the Duke FACE site, the FACE Wood Decomposition Experiment (FWDE) was established in 2011 to provide the foundation for addressing wood decomposition and its associated processes at the continental scale. Plots were installed on nine experimental forests representing a range in bioclimatic forest conditions within the continental U.S. Each identical plot has logs of the three species incubating on the soil surface and pine logs suspended in the air, representing standing dead wood. Abiotic conditions are monitored continuously, and soil and forest conditions characterized. Logs on the sites have been measured every two years to assess decay. This project was initiated in 2016 with specific objectives to: (a) determine whether dead wood C contributes to the soil C pool, (b) assess the fungal community composition mediating the decay, (c) assess the interactions of termites with microbial decay, and (d) develop a mechanistic model to simulate wood decomposition. The principal field sampling was conducted in 2017; correspondingly, the results reported here represent six years of decomposition. Wood decomposition varied from 13 to 75 % loss across the bioclimatic gradient. Sites in the southeastern U.S. coastal plain and piedmont had fastest decomposition rates for each of the species. In contrast sites in the Rocky Mountains had the slowest decay rates, which were associated with cold temperatures. Standing deadwood decomposes at a much slower rate than logs on the soil surface; a response due to differences in wood moisture content. Wood carbon was measured in the mineral soil across each of the sites; accordingly, this is the first study to affirm that a portion of the wood C does become part of the soil C pool. Averaged across the FWDE sites, approximately 1.4% of the soil C in the upper 10 cm of the mineral soil directly beneath the log was derived from the deadwood; within 50 cm of the log, wood C accounted for an average of 2.1%. These results demonstrate that the contribution of deadwood to the soil C pool is a soil volume surrounding the log; and it’s likely a larger volume than what we sampled. We also hypothesized that there would be more wood C in the mineral soil when termites were present. However, that hypothesis wasn’t supported by measurements on the Santee Experimental Forest termite exclusion (SEF-TX) plots under FACE logs that incubated for 6 years. Across all the sites, the majority of the wood C was transferred to the atmosphere. Approximately 7,000 fungal species were sequenced. The fungal communities were different among each of the sites suggesting local colonization; interestingly, within sites the three species also exhibited differences in fungal community composition. White rot was the dominant fungal form in pine and hardwood, which yields less lignin in the wood residue. Brown rot occurred in approximately 20% of the pine and aspen logs, and it did not occur in birch logs. The occurrence of brown rot was only weakly correlated to site factors. We conducted two additional experiments to assess the effects of termites on wood decomposition and the associated interactions with the fungal community. Pine and birch logs were incubated on the Santee Experimental Forest termite exclusion plots in upland and riparian settings. There was no difference in decay between areas where termites were able colonize and plots where they had been excluded. Highly variable foraging by termites was a primary contributor the result. Correspondingly, fungal communities did not vary on logs incubated among the two treatments, but they did reflect site and species differences. The second experiment was conducted on each of the nine FWDE sites where pine and birch wood blocks were incubated for two years with and without a wrapping designed to exclude termites and other arthropods. The effects of termites on wood decomposition could be confirmed on two of the four sites known to have subterranean termites. On the two southeastern sites, termites contributed approximately 8% to mass loss in pine blocks over two years. A major factor clouding the role of termites in wood decomposition is the inability to assess the time, duration, and intensity of the foraging with the logs. Another uncertainty is related to whether a piece of wood will be foraged. A process-based wood decomposition model was developed representing biological processes mediated by fungi, bacteria, termites, beetles, as well as physical and chemical processes. The Coarse Wood Decomposition Model (CWDM) was parameterized based on a thorough review of the literature and it was validated using data from the FWDE. In the initial setup, the model considers softwoods and hardwoods groups, as opposed to individual species. Sensitivity analyses incorporating climate data from 89 locations in North America demonstrated that CWDM was stable from the tropics to the boreal zone. Model calibration and validation showed it to perform very well. The CWDM is poised for additional testing with subsequent FWDE data as well as other data sets, and it is available for incorporation into forest biogeochemical models or DOEs Earth System Modeling framework.

54 ENVIRONMENTAL SCIENCES↗

Efficient Merge and Insert Operations for Binary Heaps and Trees

Binary heaps and binary search trees merge efficiently. We introduce a new amortized analysis that allows us to prove the cost of merging either binary heaps or balanced binary trees is O(l), in the amortized sense. The standard set of other operations (create, insert, delete, extract minimum, in the case of binary heaps, and balanced binary trees, as well as a search operation for balanced binary trees) remain with a cost of O(log n). For binary heaps implemented as arrays, we show a new merge algorithm that has a single operation cost for merging two heaps, a and b, of O(absolute value of a + min(log absolute value of b log log absolute value of b. log absolute value of a log absolute value of b). This is an improvement over O(absolute value of a + log absolute value of a log absolute value of b). The cost of the new merge is so low that it can be used in a new structure which we call shadow heaps. to implement the insert operation to a tunable efficiency. Shadow heaps support the insert operation for simple priority queues in an amortized time of O(f(n)) and other operations in time O((log n log log n)/f (n)), where 1 less than or equal to f (n) less than or equal to log log n. More generally, the results here show that any data structure with operations that change its size by at most one, with the exception of a merge (aka meld) operation, can efficiently amortize the cost of the merge under conditions that are true for most implementations of binary heaps and search trees.

Kuszmaul, Christopher Lee↗

Gravitational radiation from the Galaxy

The spectral flux of gravitational radiation incident on earth from the Galactic W UMa binaries, unevolved binaries, cataclysmic binaries, neutron star binaries, black hole-neutron star binaries, and close white dwarf binary (CWDB) systems is calculated. The peak values for the strain amplitude hv produced by the binaries are: log hv = -17.0/sq rt Hz at log v = -4.40 Hz for W UMa's; log hv = -16.5/sq rt Hz at log v = -5.50 Hz for unevolved binaries; log hv = -18.2/sq rt Hz at log v = -5.15 Hz for neutron star binaries; log hv = -17.0/sq rt Hz at log v = -4.7 Hz for black hole-neutron star binaries; log hv = -18.0 /sq rt Hz at log v = -4.10 Hz for cataclysmic binaries, and log hv = -27.0/sq rt Hz at log v = -4.0 Hz for CWDBs. The gravitational flux at ultralow frequencies is emitted mainly by unevolved binaries. The integrated flux incident on earth is about 2.4 x 10 to the -9th ergs/sq cm/s.

Hils, D.↗

Intrinsic and artificial bias in the KONUS cumulative number distribution

The known biases affecting the KONUS gamma burst cumulative number distribution are discussed and categorized as intrinsic (unavoidable) and artificial (avoidable). Artificial biases are removed to obtain a revised, more faithful representation of the true KONUS log N-log Pc, where Pc is in counts (1/0.25 s). A low Pc turnover is still apparent in the revised log N-log Pc. Conflicting claims that the KONUS log N-log Pc is compatible with a nearby disk or an isotropic, homogeneous distribution are tested using the revised log N-log Pc and a rigorous treatment of the KONUS intrinsic gamma background bias. The claims are shown to be improbable. Other possibilities and problms concerning log N-log Pc are discussed, but the need for a complete explanation of the low Pc turnover remains.

Jennings, Mark C.↗

Creative Analytics of Mission Ops Event Messages

Historically, tremendous effort has been put into processing and displaying mission health and safety telemetry data; and relatively little attention has been paid to extracting information from missions time-tagged event log messages. Todays missions may log tens of thousands of messages per day and the numbers are expected to dramatically increase as satellite fleets and constellations are launched, as security monitoring continues to evolve, and as the overall complexity of ground system operations increases. The logs may contain information about orbital events, scheduled and actual observations, device status and anomalies, when operators were logged on, when commands were resent, when there were data drop outs or system failures, and much much more. When dealing with distributed space missions or operational fleets, it becomes even more important to systematically analyze this data. Several advanced information systems technologies make it appropriate to now develop analytic capabilities which can increase mission situational awareness, reduce mission risk, enable better event-driven automation and cross-mission collaborations, and lead to improved operations strategies: Industry Standard for Log Messages. The Object Management Group (OMG) Space Domain Task Force (SDTF) standards organization is in the process of creating a formal standard for industry for event log messages. The format is based on work at NASA GSFC. Open System Architectures. The DoD, NASA, and others are moving towards common open system architectures for mission ground data systems based on work at NASA GSFC with the full support of the commercial product industry and major integration contractors. Text Analytics. A specific area of data analytics which applies statistical, linguistic, and structural techniques to extract and classify information from textual sources. This presentation describes work now underway at NASA to increase situational awareness through the collection of non-telemetry mission operations information into a common log format and then providing display and analytics tools to provide in-depth assessment of the log contents. The work includes: Common interface formats for acquiring time-tagged text messages Conversion of common files for schedules, orbital events, and stored commands to the common log format Innovative displays to depict thousands of messages on a single display Structured English text queries against the log message data store, extensible to a more mature natural language query capability Goal of speech-to-text and text-to-speech additions to create a personal mission operations assistant to aid on-console operations. A wide variety of planned uses identified by the mission operations teams will be discussed.

events↗

Two Ligands of Interest in Recovering Uranium from the Oceans: The Correct Formation Constants of the Uranyl(VI) Cation with 2,2'-Bipyridyl-6,6'-dicarboxylic Acid and 1,10-Phenanthroline-2,9-dicarboxylic Acid

The ligands BDA (2,2'-bipyridyl-6,6'-dicarboxylic acid) and PDA (1,10-phenanthroline-2,9-dicarboxylic acid) are of interest as functional group types for ion-exchange materials for extracting uranium from the oceans, reported in a previous paper for PDA Lashley, M. A. ( Inorg. Chem. 2016 55 10818 10829). Yang, Y. ( Inorg. Chem. 2019, 58, 6064 6074) have published what they claim to be a more accurate result for the formation of the UO 2 2+ /PDA complex of log K 1 = 22.84 compared with our reported value of log K 1 = 16.5, as well as log K 1 = 21.52 for the BDA complex. The determination of log K 1 for the PDA and BDA complexes with the UO 2 2+ cation was carried out by Yang et al. using a competition reaction between DTPA (diethylenetriamine pentaacetic acid) and BDA or PDA, monitoring the absorbance due to the BDA and PDA ligands. This competition method using absorbance versus pH titrations was developed for determining the formation constants of the complexes of several polypyridyl ligands plus PDA complexes of metal ions, which were too stable for log K determination by competition with protons. A key feature of such titrations is that in the competition reaction, the displacement of the pyridyl donor ligand (e.g., PDA) by the competing ligand (e.g., DTPA), the absorbance spectrum of the displaced pyridyl donor ligand should be observed. Competing ligands used to date have been EDTA (ethylenediamine tetraacetic acid), DTPA, or the hydroxide ion. In the study of Yang et al., no such displaced PDA or BDA was apparent in the absorbance spectra in their titrations so that their reported log K 1 values have no validity. Their log K 1 values are so much higher than log K 1 for the uranyl DTPA complex (~13.6) that DTPA could not possibly displace BDA or PDA from the uranyl cation, and a competition reaction could not possibly occur. Here, we report the correct value of log K 1 = 15.4 (ionic strength = zero) for the uranyl BDA complex, to illustrate the correct determination of such a constant by a competition reaction between BDA and hydroxide, showing how the characteristic absorbance spectrum for a BDA complex, here the UO 2 2+ complex, disappears, and the distinctive absorbance spectrum of the free nonprotonated BDA ligand appears as the pH is increased, and BDA is displaced by the hydroxide ion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Risk Assessment of Salmonellosis from Consumption of Alfalfa Sprouts and Evaluation of the Public Health Impact of Sprout Seed Treatment and Spent Irrigation Water Testing

Abstract We developed a risk assessment of human salmonellosis associated with consumption of alfalfa sprouts in the United States to evaluate the public health impact of applying treatments to seeds (0–5‐log 10 reduction in Salmonella ) and testing spent irrigation water (SIW) during production. The risk model considered variability and uncertainty in Salmonella contamination in seeds, Salmonella growth and spread during sprout production, sprout consumption, and Salmonella dose response. Based on an estimated prevalence of 2.35% for 6.8 kg seed batches and without interventions, the model predicted 76,600 (95% confidence interval (CI) 15,400 – 248,000) cases/year. Risk reduction (by 5 ‐ to 7‐fold) predicted from a 1‐log 10 seed treatment alone was comparable to SIW testing alone, and each additional 1‐log 10 seed treatment was predicted to provide a greater risk reduction than SIW testing. A 3‐log 10 or a 5‐log 10 seed treatment reduced the predicted cases/year to 139 (95% CI 33 – 448) or 1.4 (95% CI <1 – 4.5), respectively. Combined with SIW testing, a 3‐log 10 or 5‐log 10 seed treatment reduced the cases/year to 45 (95% CI 10–146) or <1 (95% CI <1 – 1.5), respectively. If the SIW coverage was less complete (i.e., less representative), a smaller risk reduction was predicted, e.g., a combined 3‐log 10 seed treatment and SIW testing with 20% coverage resulted in an estimated 92 (95% CI 22 – 298) cases/year. Analysis of alternative scenarios using different assumptions for key model inputs showed that the predicted relative risk reductions are robust. This risk assessment provides a comprehensive approach for evaluating the public health impact of various interventions in a sprout production system.

60 APPLIED LIFE SCIENCES↗

Geomechanical Framework for Secure CO 2 Storage in Fractured Reservoirs and Caprocks for Sedimentary Basins in theMidwest United States

This report presents final technical results for the project Geomechanical Framework for Secure CO 2 Storage in Fractured Reservoirs and Caprocks for Sedimentary Basins in the Midwest United States (DE-FE0023330). The project was a three-year effort consisting of seven technical tasks focused on defining geomechanical factors for CO 2 storage applications in deep saline rock formations in Ohio and the Midwest United States, because geomechancial issues have been identified as a significant risk factor for large-scale CO 2 storage applications. A basin-scale stress-strain analysis was completed to describe the geomechanical setting for rock formations of Ordovician-Cambrian age in Ohio and adjacent areas of the Midwest United States in relation to geologic CO 2 storage applications. The tectonic setting, stress orientation-magnitude, and geomechanical and petrophysical parameters for CO 2 storage zones and caprocks in the region were cataloged. Ten geophysical image logs were analyzed for natural fractures, borehole breakouts, and drilling-induced fractures. The logs indicated mostly less than 10 fractures per 100 vertical feet in the borehole, with mostly N65E principal stress orientation through the section. Geophysical image logs and other logs were obtained for three wells located near the sites where specific models were developed for geomechanical simulations: Arches site in Boone County, Kentucky; Northern Appalachian Basin site in Chautauqua County, New York; and E-Central Appalachian Basin site in Tuscarawas County, Ohio. For these three wells, 9,700 feet of image logs were processed and interpreted to provide a systematic review of the distribution within each well of natural fractures, wellbore breakouts, faults, and drilling induced fractures. There were many borehole breakouts and drilling-induced tensile fractures but few natural fractures. Concentrated fractures were present at the Rome-basal sandstone and basal sandstone-Precambrian contacts at the Arches and East-Central Appalachian Basin sites. Geophysical logs were utilized to develop local-scale geologic models by determining geomechanical and petrophysical parameters within the geologic formations. These data were ported to coupled fluid-flow and reservoir geomechanics multi-phase CO 2 injection simulations. The models were developed to emphasize the geomechanical layers within the CO 2 storage zones and caprocks. A series of simulations were completed for each site to evaluate whether commercial-scale CO 2 could be safely injected into each site, given site-specific geologic and geomechanical controls. This involved analyzing the simulation results for the integrity of the caprock, intermediate, and reservoir zones, as well quantifying the areal uplift at the surface. Simulation results were also examined to ensure that the stress-stress perturbations were isolated within the subsurface, and that there was only limited upward migration of the CO 2 . Simulations showed capacity to inject more than 10 million metric tons of CO 2 in a single well at the Arches and East Central Appalachian Basin sites without excessive geomechanical risks. Low-permeability rock layers at the Northern Appalachian Basin study area well resulted in very low CO 2 injection capacity. Fracture models developed for the sites suggests that the sites have sparse fracture network in the deeper Cambrian rocks. However, there were indicators in image logs of a moderate fracture matrix in the Rose Run Sandstone at the Northern Appalachian Basin site. Dual permeability fracture matrix simulations suggest the much higher injection rates may be feasible in the fractured interval. Guidance was developed for geomechanical site characterization in the areas of geophysical logging, rock core testing, well testing, and site monitoring. The guidance demonstrates that there is a suitable array of options for addressing geomechanical issues at CO 2 storage sites. Finally, a review of Marcellus and Utica-Point Pleasant shale gas wells and CO 2 storage intervals indicates that these items are vertically separated, except for the Oriskany sandstone and Marcellus wells in southwest Pennsylvania and northern West Virginia. Together, project results present a more realistic portrayal of geomechanical risk factors related to CO 2 storage for existing and future coal-fired power plants in Ohio.

58 GEOSCIENCES↗

Constraining the Stellar-to-Halo Mass Relation with Galaxy Clustering and Weak Lensing from DES Year 3 Data

We develop a framework to study the relation between the stellar mass of a galaxy and the total mass of its host dark matter halo using galaxy clustering and galaxy-galaxy lensing measurements. We model a wide range of scales, roughly from $\sim 100 \; {\rm kpc}$ to $\sim 100 \; {\rm Mpc}$, using a theoretical framework based on the Halo Occupation Distribution and data from Year 3 of the Dark Energy Survey (DES) dataset. The new advances of this work include: 1) the generation and validation of a new stellar mass-selected galaxy sample in the range of $\log M_\star/M_\odot \sim 9.6$ to $\sim 11.5$; 2) the joint-modeling framework of galaxy clustering and galaxy-galaxy lensing that is able to describe our stellar mass-selected sample deep into the 1-halo regime; and 3) stellar-to-halo mass relation (SHMR) constraints from this dataset. In general, our SHMR constraints agree well with existing literature with various weak lensing measurements. We constrain the free parameters in the SHMR functional form $\log M_\star (M_h) = \log(εM_1) + f\left[ \log\left( M_h / M_1 \right) \right] - f(0)$, with $f(x) \equiv -\log(10^{αx}+1) + δ[\log(1+\exp(x))]^γ/ [1+\exp(10^{-x})]$, to be $\log M_1 = 11.506^{+0.325}_{-0.404}$, $\log ε= -1.632^{+0.306}_{-0.181}$, $α= -1.638^{+0.108}_{-0.099}$, $γ= 0.596^{+0.251}_{-0.210}$ and $δ= 3.810^{+2.045}_{-1.811}$. The inferred average satellite fraction is within $\sim 5-35\%$ for our fiducial results and we do not see any clear trends with redshift or stellar mass. Furthermore, we find that the inferred average galaxy bias values follow the generally expected trends with stellar mass and redshift. Our study is the first SHMR in DES in this mass range, and we expect the stellar mass sample to be of general interest for other science cases.

Zacharegkas, G. [Argonne; Chicago U., KICP] (ORCID↗

Spectrum and chemical analysis of the double-ring planetary nebula IC 1297

The double-ring planetary nebula IC 1297 resembles NGC 7662 in appearance, although it is of much lower surface brightness. What is remarkable is the great strength of the dielectronic recombination O V line. Although this line is seen as a P Cygni feature in a number of planetary nebulae, it is in those instances accompanied by a strong continuum and other easily recognized features of stellar origin. No star is visible on CCD images of IC 1297. Optical region measurements are supplemented by IUE observations. The following logarithmic abundance values are found: log N(He) = 11.065; log N(forbidden C) = 8.6; log N(N) = 8.1; log N(O) = 8.74; log N(Ne) = 8.16; log N(S) = 7.0; log N(Cl) = 5.4; log N(Ar) = 6.2. The nebula shows no dramatic pattern of nucleogenesis events.

Aller, Lawrence H.↗

Energy deposition validation results for the evaluated electron data library in FRENSIE - 25357

The Framework for Research in Nuclear Science and Engineering (FRENSIE) is a collection of packages written in C++ that are designed primarily to aid in methods development. A recent development in FRENSIE is the modeling of single scattering electron interactions using the data in the Evaluated Electron Data Library (EEDL) from Lawrence Livermore National Laboratory (LLNL). Preliminary verification and validation (V and V) results using the well-known Lockwood energy deposition experiment and a comparison with MCNP6.2 were performed using several bivariate grid policies (Unit-base, Correlated, Unit-base Correlated), interpolation schemes (lin-lin, log-log, lin-log), and physics options (Coupled and Decoupled Elastic Scattering). The results show an agreement to within 0.5% between MCNP6.2 and FRENSIE when using the same bivariate grid policy (Correlated) and interpolation scheme (log-log). When compared to the experimental results of the Lockwood experiment, it was found that a Unit-base bivariate grid policy, lin-lin interpolation scheme, and lin-log interpolation scheme did not produce accurate results for the energy deposition in test problems. The log-log Correlated and Unit-base Correlated results showed the greatest agreement with the Lockwood experiment. The total energy deposition matched the experimental data to within 3%. Both the Correlated and Unit-base Correlated results had a tendency to estimate a higher energy deposition near the peaks and a lower energy deposition near the tails. The differences between coupled elastic scattering and decoupled scattering models were shown to be more prominent at higher energies with the results of the coupled elastic scattering being more accurate for the peak and less accurate for the tail of the energy deposition profiles. (authors)

61 RADIATION PROTECTION AND DOSIMETRY↗

April 2020 Darshan counters from the Summit supercomputer

This dataset is the Darshan counters collected from the Summit supercomputer in a month of April 2020. 1. Description of methods used for collection/generation of data: Job submitted on Summit HPC system when completed successfully and has made I/O calls (captured by Darshan tool) writes a Darshan log file on alpine filesystem. One job can have multiple `jsrun` commands and Darshan will generate separate logs each log corresponding to an `jsrun` command, so a job can have one or more Darshan logs associated with it. 2. Methods for processing the data: To process the data, we first use `darshan-util` tool to parse the Darshan logs. Then we restructure the logs and merge data from multiple Darshan logs if they belong to the same Summit job.

97 MATHEMATICS AND COMPUTING↗

Neural network modeling of in situ fluid-filled pore size distributions in subsurface shale reservoirs under data constraints

Subsurface nuclear magnetic resonance (NMR) logs acquired in the wellbore environment are sensitive to fluid-filled pore size distribution, fluid mobility, permeability, and porosity in the near-wellbore reservoir volume. NMR response of a formation layer is processed to extract the T2 distribution, which approximates the fluid-filled pore size distribution. NMR logs are acquired in limited number of wells due to financial and operational challenges, which adversely affects reservoir characterization. We developed here two neural-network-based machine learning techniques, long short-term memory (LSTM) network and variational autoencoder with a convolutional layer (VAEc) network, to process the ‘easy-to-acquire’ formation mineral and fluid saturation logs to generate synthetic NMR T2 distributions in the absence of ‘hard-to-acquire’ NMR T2 distribution log. Both the predictive models are trained and tested on limited wireline log measurements randomly selected from a 300-ft depth interval of the Bakken shale formation. Synthesis performances of LSTM and VAEc models in terms of R 2 are 0.78 and 0.75, respectively. Noise is inevitable in logging data due to the complex wellbore and formation conditions. Notably, both the predictive models robustly synthesize the fluid-filled pore size distributions in the presence of 50% noise in input logs and 30% noise in training T2 data. The performance of the proposed methodology improves with access to larger volume of training data from other formation types. The proposed method is critical to the synthesis of in situ fluid-filled pore size distributions in shale formations under data constraints due to financial and operational challenges.

58 GEOSCIENCES↗

Compact galaxies and the size–mass galaxy distribution from a colour-selected sample at 0.04 < z < 0.15 supplemented by ugrizYJHK photometric redshifts

ABSTRACT The size–mass galaxy distribution is a key diagnostic for galaxy evolution. Massive compact galaxies are potential surviving relics of a high-redshift phase of star formation. Some of these could be nearly unresolved in Sloan Digital Sky Survey (SDSS) imaging and thus not included in galaxy samples. To overcome this, a sample was selected from the combination of SDSS and UKIRT Infrared Deep Sky Survey (UKIDSS) photometry to r < 17.8. This was done using colour–colour selection, and then by obtaining accurate photometric redshifts (photo-z) using scaled flux matching (SFM). Compared to spectroscopic redshifts (spec-z), SFM obtained a 1σ scatter of 0.0125 with only 0.3 per cent outliers (|Δln (1 + z)| > 0.06). A sample of 163 186 galaxies was obtained with 0.04 < z < 0.15 over $2300\, {\rm deg}^2$ using a combination of spec-z and photo-z. Following Barro et al. log Σ1.5 = log M* − 1.5log r50, maj was used to define compactness. The spectroscopic completeness was 76 per cent for compact galaxies (log Σ1.5 > 10.5) compared to 92 per cent for normal-sized galaxies. This difference is primarily attributed to SDSS ‘fibre collisions’ and not the completeness of the main galaxy sample selection. Using environmental overdensities, this confirms that compact quiescent galaxies are significantly more likely to be found in high-density environments compared to normal-sized galaxies. By comparison with a high-redshift sample from 3D-HST, log Σ1.5 distribution functions show significant evolution, with this being a compelling way to compare with simulations such as EAGLE. The number density of compact quiescent galaxies drops by a factor of about 30 from z ∼ 2 to log (n/Mpc−3) = − 5.3 ± 0.4 in the SDSS–UKIDSS sample. The uncertainty is dominated by the steep cut off in log Σ1.5, which is demonstrated conclusively using this complete sample.

Baldry, Ivan K.↗

Constraining quenching time-scales in galaxy clusters by forward-modelling stellar ages and quiescent fractions in projected phase space

We forward-model mass-weighted stellar ages (MWAs) and quiescent fractions (f Q ) in projected phase space (PPS), using data from the Sloan Digital Sky Survey, to jointly constrain an infall quenching model for galaxies in log (M vir /M ⊙ ) > 14 galaxy clusters at z ∼ 0. We find the average deviation in MWA from the MWA–M⋆ relation depends on position in PPS, with a maximum difference between the inner cluster and infalling interloper galaxies of ∼1 Gyr. Our model employs infall information from N-body simulations and stochastic star-formation histories from the universemachine model. We find total quenching times of t Q = 3.7 ± 0.4 Gyr and t Q = 4.0 ± 0.2 Gyr after first pericentre, for 9 < log (M ⋆ /M ⊙ ) < 10 and 10 < log (M ⋆ /M ⊙ ) < 10.5 galaxies, respectively. By using MWAs, we break the degeneracy in time of quenching onset and time-scale of star formation rate (SFR) decline. We find that time of quenching onset relative to pericentre is $t_{\mathrm{delay}}=3.5^{+0.6}_{-0.9}$ Gyr and $t_{\mathrm{delay}}=-0.3^{+0.8}_{-1.0}$ Gyr for 9 < log (M ⋆ /M ⊙ ) < 10 and 10 < log (M ⋆ /M ⊙ ) < 10.5 galaxies, respectively, and exponential SFR suppression time-scales are τenv ≤ 1.0 Gyr for 9 < log (M ⋆ /M ⊙ ) < 10 galaxies and τenv ∼ 2.3 Gyr for 10 < log (M ⋆ /M ⊙ ) < 10.5 galaxies. Stochastic star formation histories remove the need for rapid infall quenching to maintain the bimodality in the SFR of cluster galaxies; the depth of the green valley prefers quenching onsets close to first pericentre and a longer quenching envelope, in slight tension with the MWA-driven results. Taken together these results suggest that quenching begins close to, or just after pericentre, but the time-scale for quenching to be fully complete is much longer and therefore ram-pressure stripping is not complete on first pericentric passage.

79 ASTRONOMY AND ASTROPHYSICS↗

Characterization and identification of HPC applications at leadership computing facility

High Performance Computing (HPC) is an important method for scientific discovery via large-scale simulation, data analysis, or artificial intelligence. Leadership-class supercomputers are expensive, but essential to run large HPC applications. The Petascale era of supercomputers began in 2008, with the first machines achieving performance in excess of one petaflops, and with the advent of new supercomputers in 2021 (e.g., Aurora, Frontier), the Exascale era will soon begin. However, the high theoretical computing capability (i.e., peak FLOPS) of a machine is not the only meaningful target when designing a supercomputer, as the resources demand of applications varies. A deep understanding of the characterization of applications that run on a leadership supercomputer is one of the most important ways for planning its design, development and operation. In order to improve our understanding of HPC applications, user demands and resource usage characteristics, we perform correlative analysis of various logs for different subsystems of a leadership supercomputer. This analysis reveals surprising, sometimes counter-intuitive patterns, which, in some cases, conflicts with existing assumptions, and have important implications for future system designs as well as supercomputer operations. For example, our analysis shows that while the applications spend significant time on MPI, most applications spend very little time on file I/O. Combined analysis of hardware event logs and task failure logs show that the probability of a hardware FATAL event causing task failure is low. Combined analysis of control system logs and file I/O logs reveals that pure POSIX I/O is used more widely than higher level parallel I/O. Based on holistic insights of the application gained through combined and co-analysis of multiple logs from different perspectives and general intuition, we engineer features to "fingerprint" HPC applications. We use t-SNE (a machine learning technique for dimensionality reduction) to validate the explainability of our features and finally train machine learning models to identify HPC applications or group those with similar characteristic. To the best of our knowledge, this is the first work that combines logs on file I/O, computing, and inter-node communication for insightful analysis of HPC applications in production.

Liu, Zhengchun↗

An Overview of Surface Heat Microbial Reduction as a Viable Microbial Reduction Modality for Spacecraft Surfaces

In accordance with NASA Planetary Protection (PP) policy requirements, flight project hardware may be required to undergo microbial reduction processes to prevent the forward contamination of target planetary bodies with Earth organisms. Heat microbial reduction (HMR) is the most commonly employed modality used at JPL for reducing the microbial bioburden on flight hardware. In 2013, longstanding HMR specifications were abandoned, and revised specifications were developed which integrated the latest findings on bacterial spore heat resistivity. Revised decimal reduction values (D-values) for time-temperature lethality curves (110 °C to 200 °C) were developed to account for “hardy” bacterial spores that exhibit greater heat resistance than previously understood. Presented here is a comparative analysis of the revised NASA HMR specifications against empirical data compiled from recent JPL studies, and peer-reviewed, published literature. Bacillus sp. strain ATCC 29669 displayed high heat resistance, and this strain’s 4-log heat lethality curve was comparable to the revised 4-log specification. Spores of Bacillus atrophaeus ATCC 9372 displayed less heat resistance, and exhibited D-values which were less than the revised 3-log microbial reduction specifications. Extrapolations indicate that the current 6-log reduction credit applied to 350 °C for 1 hr. and 500 °C for 0.5 sec. is highly conservative. Projections indicate that a 10- to 18-log reduction of both hardy and non-hardy spores may be achievable at bakeouts of 350 °C for 1 hr. The findings reported here indicate the revised NASA HMR specifications from 110 °C to 200 °C are appropriate for achieving 4-log and 6-log reductions with hardy spore populations; however, for non-hardy spore populations, or for temperatures above 200 °C, the specifications are exceedingly conservative.

Shirey, Brian T.↗

Distributions of the Mean for Lognormally Distributed Data - 19427

In environmental sciences, a distribution of the mean is often needed for right-skewed data. For example, risk assessments are often based on distributions of the mean to obtain upper confidence limits (UCLs) for analyte concentrations, and, in probabilistic performance assessment (PPA) models, parameters are given distributions rather than deterministic values, and they are usually given distributions of their mean rather than the population distributions to account for the large spatial and temporal domains to which they are applied. How this distribution of the mean is developed depends on the characteristics of the parameter's full distribution and how the parameter relates to its use. In this presentation, I will discuss the implications of a right skew in distribution development. Parameters may vary over orders of magnitude and/or may be right-skewed. The material property of saturated hydraulic conductivity, Ks, is a prime example of such a parameter. Right-skewed parameters are often assumed to follow lognormal distributions. If X follows a lognormal distribution, then log(X) follows a normal distribution. For some right-skewed parameters, practitioners go back and forth between the two forms of the data depending on their needs. For example, it may be preferred to use the untransformed version of X in a model or equation, but it is easier to visualize the parameter values on a logarithmic scale. However, distribution development for the average value of the parameter will differ depending on whether X or log(X) is modeled. This difference is due to Jensen's Inequality, a theorem which states that the expected value of a concave function of a variable is less than or equal to the same function of the expected value of the variable; a logarithm is a concave function. In other words, the mean of log(X) is always less than or equal to the log of the mean of X and therefore the mean estimated from a distribution based on log(X) is less than or equal to the mean estimated from a distribution based on X. If a parameter is naturally considered on a log scale by subject matter experts, then distributions developed for the mean of log(X) may be more consistent with the use of the parameters in the literature than distributions developed for X. The statistical decisions of distribution development will be discussed within the context of right-skewed, lognormal data. These issues include method-of-moments versus maximum likelihood estimation of the distribution parameters and the use of bootstrapping to aid in the visualization of a distribution of the mean. The details surrounding Jensen's Inequality will be explained and visualized within the context of distribution development of a right-skewed parameter such as saturated hydraulic conductivity. (authors)

54 ENVIRONMENTAL SCIENCES↗