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PyDSS is a high level Python interface for OpenDSS and provides the following functionalities: 1] Object oriented programming, 2] Dynamic visualization, 3] Custom controls, 4] Simulation parallelization, 5] Exporting results, 6] Improved error logging, and 7] Communication interface. Documentation on installation, setup and examples can be found here https://nrel.github.io/PyDSS/index.html
We present a 0.7–2.5 μm spectral library of 284 stars observed with the medium-resolution infrared spectrograph, SpeX, at the 3.0 m NASA Infrared Telescope Facility (IRTF) on Maunakea, Hawaii. This library extends the metallicity range of the IRTF Cool Star library beyond solar metallicity to −1.7 < [Fe/H] < 0.6. All of the observed stars are also in the MILES optical stellar library, providing continuous spectral coverage for each star from 0.35 to 2.5 μm. The spectra are absolute flux calibrated using Two Micron All Sky Survey photometry, and the continuum shape of the spectra is preserved during the data reduction process. Synthesized JHK {sub S} colors agree with observed colors at the 1%–2% level, on average. We also present a spectral interpolator that uses the library to create a data-driven model of spectra as a function of T{sub eff}, log g, and [Fe/H]. We use the library and interpolator to compare empirical trends with theoretical predictions of spectral feature behavior as a function of stellar parameters. These comparisons extend to the previously difficult to access low-metallicity and cool dwarf regimes, as well as the previously poorly sampled super-solar metallicity regime. The library and interpolator are publicly available.
This is the first paper in a projected program to produce quantitative information on the spectrum of the neutral oxygen atom under a variety of excitation conditions. Radiative rates and effective collision strengths are assembled from the recent literature where available, or are calculated for as yet untreated transitions using the University College superstructure/distorted-wave computer package, to produce a complete set of atomic data for a 13 hybrid level model of neutral oxygen. Level populations and relative intensities for 28 allowed, inter-combination, and forbidden oxygen lines are computed, under optically thin conditions, for the electron density range 4.0 less than log N(sub e) less than 12.0 and the electron temperature values T(sub e) = 5000, 10,000, 20,000, 50,000, and 100,000 K. Preliminary applications to observed intercombination/allowed and forbidden/allowed line ratios are discussed.
Several computer programs have been developed to enable efficient administration of a large, heterogeneous, UNIX-based computing and communication network that includes a variety of computers connected to a variety of subnetworks. One program provides secure software tools for administrators to create, modify, lock, and delete accounts of specific users. This program also provides tools for users to change their UNIX passwords and log-in shells. These tools check for errors. Another program comprises a client and a server component that, together, provide a secure mechanism to create, modify, and query quota levels on a network file system (NFS) mounted by use of the VERITAS File SystemJ software. The client software resides on an internal secure computer with a secure Web interface; one can gain access to the client software from any authorized computer capable of running web-browser software. The server software resides on a UNIX computer configured with the VERITAS software system. Directories where VERITAS quotas are applied are NFS-mounted. Another program is a Web-based, client/server Internet Protocol (IP) address tool that facilitates maintenance lookup of information about IP addresses for a network of computers.
The development and operational sustainment of renewable (geothermal) and non-renewable (fossil fuel) energy resources will be accompanied by increasingly higher costs factors: exploration and site preparation, operational maintenance and repair. Increased government oversight in the wake of the Gulf oil spill will only add to the cost burden. It is important to understand that downhole conditions are not just about elevated temperatures. It is often construed that military electronics are exposed to the upper limit in terms of extreme service environments. Probably the harshest of all service conditions for electronics and electrical equipment are those in oil, gas, and geothermal wells. From the technology perspective, advanced materials, sensors, and microelectronics devices are benefificial to the exploration and sustainment of energy resources, especially in terms of lower costs. Besides the need for the science that creates these breakthroughs - there is also a need for sustained engineering development and testing. Downhole oil, gas, and geothermal well applications can have a wide range of environments and reliability requirements: Temperature, Pressure, Vibration, Corrosion, and Service duration. All too frequently, these conditions are not well-defifined because the application is labeled as 'high temperature'. This ambiguity is problematic when the investigation turns to new approaches for electronic packaging solutions. The objective is to develop harsh environment, electronic packaging that meets customer requirements of cost, performance, and reliability. There are a number of challenges: (1) Materials sets - solder alloys, substrate materials; (2) Manufacturing process - low to middle volumes, low defect counts, new equipment technologies; and (3) Reliability testing - requirements documents, test methods and modeling, relevant standards documents. The cost to develop and sustain renewable and non-renewable energy resources will continue to escalate within the industry. Downhole electronics can provide a very cost-effective approach for well exploration and sustainment (data logging). However, the harsh environments are a 'game-changer' in terms defining materials, assembly processes and the long-term reliability of downhole electronic systems. The system-level approach will enable the integration of each of these contributors - materials, processes, and reliability - in order to deliver cost-effective electronics that meet customer requirements.
The objectives of this project are to understand the processes that occur when a maximum of 70,000 metric tonnes of CO 2 are injected into two different formations to evaluate the response in different lithofacies and depositional environments. The evaluation will be accomplished through the use of both in situ and indirect MVA (monitoring, verification, and accounting) technologies. The project will optimize for carbon storage accounting for 99% of the CO 2 using lab and field testing and comprehensive characterization and modeling techniques. Site characterization and CO 2 injection should demonstrate state-of-the-art MVA tools and techniques to monitor and visualize the injected CO 2 plume and to refine geomodels developed using nearly continuous core, exhaustive wireline logs, and well tests and a multi-component 3-D seismic survey. Reservoir simulation studies will map the injected CO 2 plume and estimate tonnage of CO 2 stored in solution, as residual gas, and by mineralization and integrate MVA results and reservoir models shall be used to evaluate CO 2 leakage. A rapid-response mitigation plan was developed to minimize CO 2 leakage and provide a comprehensive risk management strategy. The CO 2 was intended to be supplied from a reliable facility and have an adequate delivery and quality of CO 2 . However, several unforeseen circumstances complicated this plan: (1) the initially negotiated CO 2 supply facility went offline and contracts associated with CO 2 supply had to be renegotiated, (2) a UIC Class VI permit proved to be difficult to obtain due to the experimental nature of the project. Both subjects are detailed in separate deliverables attached to this report. The CO 2 enhanced oil recovery (EOR) and geologic storage in Mississippian carbonate reservoir was sucessully deployed. Approximately 20,000 metric tons of CO 2 was injected in the upper part of the Mississippian reservoir to verify CO 2 EOR viability in carbonate reservoirs and evaluate a potential of transitioning to geologic CO 2 storage through EOR. A total of 1,101 truckloads, 19,803 metric tons—an average of 120 tonnes per day—were delivered over the course of injection that lasted from January 9 to June 21, 2016. After cessation of CO 2 injection, the KGS 2-32 well was converted to water injector and continues to operate. CO 2 EOR progression in the field was monitored weekly with fluid level, temperature, and production recording and formation fluid composition sampling. It is important to note that normally, CO 2 EOR pilots are less efficient than commercial operations due to lack of directional and precise well control, lack of surface facilities for CO 2 recycling, and other factors. As a result of this pilot CO 2 injection, the observed incremental average oil production increase was ~68% with only ~18% of injected CO 2 produced back. Decline curve analysis forecasts of additional cumulative oil produced were 32.44M STB to the end of 2027. Wellington Mississippian pilot efficiency by the end of forecast calculations is 11 MCF per barrel of produced oil. Using 32M STB oil production and $1,964,063 cost of CO 2 , CO 2 EOR cost per barrel of oil production is ~$60. Simple but robust monitoring technologies proved to be very efficient in detecting and locating CO 2 . High CO 2 reservoir retentions with low yields within an actively producing field could help to estimate real-world risks of CO 2 geological storage for future projects. The Wellington Field CO 2 EOR was executed in a controlled environment with high efficiency. This case study proves that CO 2 EOR could be successfully applied in Kansas carbonate reservoirs if CO 2 sources and associated infrastructure are available. Recent developments in unconventional resources development in Mid-Continent USA and associated large volume disposal of backflow water and the resulting seismic activity have brought more focus and attention to the Arbuckle Group in southern Kansas. Despite the commercial interest, limited essential information about reservoir properties and structural elements has impeded the management and regulation of disposal, an issue brought to the forefront by recent seismicity in and near areas of large volumes and rates of brine disposal. The Kansas Geological Survey (KGS) collected, compiled, and analyzed available data, including well logs, core data, step rate tests, drill stem tests, 2-D and 3-D seismic data, water level measurements, and others types of data. Several exploratory wells were drilled and core was collected and modern suites of logs were analyzed. Reservoir properties were populated into several site-specific geological models. The geological models illustrate the highly heterogeneous nature of the Arbuckle Group. Vertical and horizontal variability results in several distinct hydro-stratigraphic units that are the result of both depositional and diagenetic processes. During the course of this project, it has been demonstrated that advanced seismic interpretation methods can be used successfully for characterization of the Mississippian reservoir and Arbuckle saline aquifer. Analysis of post-stack 3-D seismic data at the Mississippian reservoir showed the response of a gradational velocity transition. Pre-stack gather analysis showed that porosity zones of the Mississippian and Arbuckle reservoirs exhibit characteristic amplitude versus offset (AVO) response. Simultaneous AVO inversion estimated P- and S-impedances. The 3-D survey gather azimuthal anisotropy analysis (AVAZ) provided information about the fault and fracture network and showed good agreement to the regional stress field and well data. Mississippian reservoir porosity and fracture predictions agreed well with the observed mobility of injected CO 2 in KGS well 2-32. Fluid substitution modeling predicted acoustic impedance reduction in the Mississippian carbonate reservoir introduced by the presence of CO 2 . Seismicity in the United States midcontinent has increased by orders of magnitude over the past decade. Spatiotemporal correlations of seismicity to wastewater injection operations have suggested that injection-related pore fluid pressure increases are inducing the earthquakes. In this investigation, we examine earthquake occurrence in southern Kansas and northern Oklahoma and its relation to the change in pore pressure. The main source of data comes from the Wellington Array in the Wellington oil field, in Sumner County, Kansas, which has monitored for earthquakes in central Sumner County, Kansas, since early 2015. The seismometer array was established to monitor CO 2 injection operations at Wellington Field. Although no seismicity was detected in association with the spring 2016 Mississippian CO 2 injection, the array has recorded more than 2,500 earthquakes in the region and is providing valuable understanding to induced seismicity. A catalog of earthquakes was built from this data and was analyzed for spatial and temporal changes, stress information, and anisotropy information. The region of seismic concern has been shown to be expanding through use of the Wellington earthquake catalog, which has revealed a northward progression of earthquake activity reaching the metropolitan area of Wichita. The stress orientation was also calculated from this earthquake catalog through focal mechanism inversion. The calculated stress orientation was confirmed through comparison to other stress measurements from well data and previous earthquake studies in the region. With this knowledge of the stress orientation, the anisotropy in the basement could be understood. This allowed for the anisotropy measurements to be correlated to pore pressure increases. The increase in pore pressure was monitored through time-lapse shear-wave anisotropy analysis. Since the onset of the observation period in 2010, the orientation of the fast shear wave has rotated 90°, indicating a change associated with critical pore pressure build up. The time delay between fast and slow shear wave arrivals has increased, indicating a corresponding increase in anisotropy induced by pore pressure rise. In-situ near-basement fluid pressure measurements corroborate the continuous pore pressure increase revealed by the shear-wave anisotropy analysis over the earthquake monitoring period. This research is the first to identify a change in pore fluid pressure in the basement using seismological data and it was recently published in the AAAS journal Science Advances (Nolte et al., 2017). The shear-wave splitting analysis is a novel application of the technique, which can be used in other regions to identify an increase in pore pressure. This increasing pore fluid pressure has become more regionally extensive as earthquakes are occurring in southern Kansas, where they previously were absent. These monitoring techniques and analyses provide new insight into mitigating induced seismicity’s impact on society.
We report that maps of cosmic microwave background (CMB) temperature and polarization from the 2015 release of Planck data provide the highestquality full-sky view of the surface of last scattering available to date. This enables us to detect possible departures from a globally isotropic cosmology. We present the first searches using CMB polarization for correlations induced by a possible non-trivial topology with a fundamental domain that intersects, or nearly intersects, the last-scattering surface (at comoving distance χ rec ), both via a direct scan for matched circular patterns at the intersections and by an optimal likelihood calculation for specific topologies. We specialize to flat spaces with cubic toroidal (T3) and slab (T1) topologies, finding that explicit searches for the latter are sensitive to other topologies with antipodal symmetry. These searches yield no detection of a compact topology with a scale below the diameter of the last-scattering surface. The limits on the radius R i of the largest sphere inscribed in the fundamental domain (at log-likelihood ratio ΔlnL > -5 relative to a simply-connected flat Planck best-fit model) are: R i > 0.97 χ rec for the T3 cubic torus; and R i > 0.56 χ rec for the T1 slab. The limit for the T3 cubic torus from the matched-circles search is numerically equivalent, R i > 0.97 χ rec at 99% confidence level from polarization data alone. We also perform a Bayesian search for an anisotropic global Bianchi VII h geometry. In the non-physical setting, where the Bianchi cosmology is decoupled from the standard cosmology, Planck temperature data favour the inclusion of a Bianchi component with a Bayes factor of at least 2.3 units of log-evidence. However, the cosmological parameters that generate this pattern are in strong disagreement with those found from CMB anisotropy data alone. Fitting the induced polarization pattern for this model to the Planck data requires an amplitude of -0.10 ± 0.04 compared to the value of + 1 if the model were to be correct. In the physically motivated setting, where the Bianchi parameters are coupled and fitted simultaneously with the standard cosmological parameters, we find no evidence for a Bianchi VII h cosmology and constrain the vorticity of such models to (ω/H) 0 < 7.6 × 10 -10 (95% CL).
We have obtained low-resolution optical (0.7–0.98 μ m) and near-infrared (1.11–1.34 μ m and 0.8–2.5 μ m) spectra of 12 isolated planetary-mass candidates ( J = 18.2–19.9 mag) of the 3 Myr σ Orionis star cluster with the aim of determining the spectroscopic properties of very young, substellar dwarfs and assembling a complete cluster mass function. We have classified our targets by visual comparison with high- and low-gravity standards and by measuring newly defined spectroscopic indices. We derived L0–L4.5 and M9–L2.5 using high- and low-gravity standards, respectively. Our targets reveal clear signposts of youth, thus corroborating their cluster membership and planetary masses (6–13 M {sub Jup}). These observations complete the σ Orionis mass function by spectroscopically confirming the planetary-mass domain to a confidence level of ∼75%. The comparison of our spectra with BT-Settl solar metallicity model atmospheres yields a temperature scale of 2350–1800 K and a low surface gravity of log g ≈ 4.0 [cm s{sup −2}], as would be expected for young planetary-mass objects. We discuss the properties of the cluster’s least-massive population as a function of spectral type. We have also obtained the first optical spectrum of S Ori 70, a T dwarf in the direction of σ Orionis. Our data provide reference optical and near-infrared spectra of very young L dwarfs and a mass function that may be used as templates for future studies of low-mass substellar objects and exoplanets. The extrapolation of the σ Orionis mass function to the solar neighborhood may indicate that isolated planetary-mass objects with temperatures of ∼200–300 K and masses in the interval 6–13 M {sub Jup} may be as numerous as very low-mass stars.
This data- and event-driven persistent storage system leverages the use of commercial software provided by Oracle for portability, ease of maintenance, scalability, and ease of integration with embedded, client-server, and multi-tiered applications. In this role, the Service Management Database (SMDB) is a key component of the overall end-to-end process involved in the scheduling, preparation, and configuration of the Deep Space Network (DSN) equipment needed to perform the various telecommunication services the DSN provides to its customers worldwide. SMDB makes efficient use of triggers, stored procedures, queuing functions, e-mail capabilities, data management, and Java integration features provided by the Oracle relational database management system. SMDB uses a third normal form schema design that allows for simple data maintenance procedures and thin layers of integration with client applications. The software provides an integrated event logging system with ability to publish events to a JMS messaging system for synchronous and asynchronous delivery to subscribed applications. It provides a structured classification of events and application-level messages stored in database tables that are accessible by monitoring applications for real-time monitoring or for troubleshooting and analysis over historical archives.
The dataset repository is organized into three main folders, each containing one group of life cycled battery packs. Within each folder individual battery packs own their dedicated csv file for continuous data logging, which are named with their respective battery pack number. The folders are named: - regular_alt_batteries: Containing one csv file for each battery pack cycled at the same load level or load range throughout lifetime - recommissioned_batteries: Containing one csv file for each battery pack cycled at different load levels at varying life stages - second_life_batteries: Containing one csv file for each second life battery pack cycled at constant current througout the second life
NASA is currently evaluating different methods to predict how much time crewmembers will spend conducting repair and maintenance activities on future space missions. As mission scope and spacecraft architectures change, it will be necessary to understand how crew repair and maintenance timelines are impacted by mission operations and technology changes. Past work has been done using historical ISS data to accurately predict crew habitation and operation timelines, resulting in the development of NASA’s Exploration Crew Time Model (ECTM). However, understanding crew maintenance and repair requirements has posed a unique challenge due to the complexity of available datasets, the probabilistic nature of sub-system failures, and the impacts of reliability growth on failure rates. This paper presents a methodology to collect and condition empirical repair and maintenance time data from available data sets, to extrapolate from that data to estimate projected maintenance and repair times for a lunar Surface Habitat, and to assess how uncertainty in repair time could impact utilization time on the lunar surface. NASA International Space Station (ISS) maintenance and crew time data are logged into two central databases, the Maintenance Data Collection (MDC) and the Operations Planning Timeline Integration System (OPTimIS) respectively. Separately, each of these two datasets capture only portions of the complete set of data required to generate an accurate assessment of crew time spent on maintenance activities at a sub-system level. MDC provides a detailed catalog of failure events and an overview of the failure’s required maintenance and OPTimIS provides a description of crew activities and crew time durations dedicated to maintenance. To create a more useful crew time estimate for maintenance timelines, the authors developed a methodology to capture relevant data from each set and combine and utilize that data by linking crew time requirements to specific components. The authors compare the failure logs in the MDC to crew activity logs pulled from OPTimIS and then process the data to estimate required repair times for each failure event. Data is also classified by the outcome of each repair event, whether the failed component was replaced or whether it was repaired in place. The entire maintenance activity dataset is then categorized based on the class of failed component to allow for a statistically significant sample size for each class and to provide accurate crew time estimates for any components lacking relevant data. This resultant component repair time data can be used in the future to generate Mean Time To Repair (MTTR) estimates and confidence intervals for each class of component based on a probabilistic distribution of documented maintenance events. These improved MTTR values can then be applied to candidate element sub-system architectures, along with component Mean Time Between Failure (MTBF) data to generate distributions for potential required system crew repair time estimates for a given mission. Repair time distributions can then be used to develop more accurate crew schedules and to assess potential available utilization time.
To understand soil microbial community stability and temporal turnover in response to climate change, a long-term soil transplant experiment was conducted in three agricultural experiment stations over large transects from a warm temperate zone (Fengqiu station in central China) to a subtropical zone (Yingtan station in southern China) and a cold temperate zone (Hailun station in northern China). Annual soil samples were collected from these three stations from 2005 to 2011, and microbial communities were analyzed by sequencing microbial 16S ribosomal RNA gene amplicons using Illumina MiSeq technology. Our results revealed a distinctly differential pattern of microbial communities in both northward and southward transplantations, along with an increase in microbial richness with climate cooling and a corresponding decrease with climate warming. The microbial succession rate was estimated by the slope (w value) of linear regression of a log-transformed microbial community similarity with time (time–decay relationship). Compared with the low turnover rate of microbial communities in situ (w=0.046, P<0.001), the succession rate at the community level was significantly higher in the northward transplant (w=0.058, P<0.001) and highest in the southward transplant (w=0.094, P<0.001). Climate warming lead to a faster succession rate of microbial communities as well as lower species richness and compositional changes compared with in situ and climate cooling, which may be related to the high metabolic rates and intense competition under higher temperature. This study provides new insights into the impacts of climate change on the fundamental temporal scaling of soil microbial communities and microbial phylogenetic biodiversity.
ABSTRACT We present the first comprehensive halo occupation distribution (HOD) analysis of the Dark Energy Spectroscopic Instrument (DESI) One-Percent Survey luminous red galaxy (LRG) and Quasi Stellar Object (QSO) samples. We constrain the HOD of each sample and test possible HOD extensions by fitting the redshift-space galaxy 2-point correlation functions in 0.15 < r < 32 h−1 Mpc in a set of fiducial redshift bins. We use AbacusSummit cubic boxes at Planck 2018 cosmology as model templates and forward model galaxy clustering with the AbacusHOD package. We achieve good fits with a standard HOD model with velocity bias, and we find no evidence for galaxy assembly bias or satellite profile modulation at the current level of statistical uncertainty. For LRGs in 0.4 < z < 0.6, we infer a satellite fraction of $f_\mathrm{sat} = 11\pm 1~{y{\ \mathrm{per\,cent}}}$, a mean halo mass of $\log _{10}\overline{M}_h/M_\odot =13.40^{+0.02}_{-0.02}$, and a linear bias of $b_\mathrm{lin} = 1.93_{-0.04}^{+0.06}$. For LRGs in 0.6 < z < 0.8, we find $f_\mathrm{sat}=14\pm 1~{{\ \mathrm{per\,cent}}}$, $\log _{10}\overline{M}_h/M_\odot =13.24^{+0.02}_{-0.02}$, and $b_\mathrm{lin}=2.08_{-0.03}^{+0.03}$. For QSOs, we infer $f_\mathrm{sat}=3^{+8}_{-2}\mathrm{per\,cent}$, $\log _{10}\overline{M}_h/M_\odot = 12.65^{+0.09}_{-0.04}$, and $b_\mathrm{lin} = 2.63_{-0.26}^{+0.37}$ in redshift range 0.8 < z < 2.1. Using these fits, we generate a large suite of high fidelity galaxy mocks, forming the basis of systematic tests for DESI Y1 cosmological analyses. We also study the redshift-evolution of the DESI LRG sample from z = 0.4 up to z = 1.1, revealling significant and interesting trends in mean halo mass, linear bias, and satellite fraction.
We observed the effect on gene transcription of laser-mediated, long-wavelength UV-irradiation of Saccharomyces cerevisiae by RNAseq analysis at times T15, T30, and T60 minutes after recovery in growth medium. Laser-irradiated cells were viable, and the transcriptional response was transient, with over 400 genes differentially expressed at T15 or T30, returning to basal level transcription by T60. Identification of transcripts exhibiting enhanced differential expression that were unique to UV laser-irradiation were identified by imposing a stringent significance cut-off (p <0.05, log 2 difference >2) then filtering out genes known as environmental stress response (ESR) genes. Using these rigorous criteria, 56 genes were differentially expressed at T15; at T30 differential expression was observed for 57 genes, some of which persisted from T15. Among the highly up-regulated genes were those supporting amino acid metabolic processes sulfur amino acids, methionine, aspartate, cysteine, serine), sulfur regulation (hydrogen sulfite metabolic processes, sulfate assimilation, sulfate reduction), proteasome components, amino acid transporters, and the iron regulon. At T30, the expression profile shifted to expression of transcripts related to catabolic processes (oxidoreductase activity, peptidase activity). Transcripts common to both T15 and T30 suggested an up-regulation of catabolic events, including UV damage response genes, and protein catabolism via proteasome and peptidase activity. Specific genes encoding tRNAs were among the down-regulated genes adding to the suggestion that control of protein biosynthesis was a major response to long-wave UV laser irradiation. These transcriptional responses bring light to the remarkable ability of the yeast cell to respond to a UV-induced environmental insult.
Higgs production in bins of PhaseSpace:mHatMin. Cross sections depend on pT and not given. All decays are included. 1000 events per file, 100 files per pT bin. Cross sections are included in the log files. How to decode name: Name: tev100_pythia8_ptPTMIN_PTMAX_NUMBER.promc where PTMIN is min pT for PhaseSpace:ptHatMin, PTMAX - PhaseSpace:pTHatMax*2, NUMBER corresponds to the cluster production node. The actual gen-level cut is PhaseSpace:pTHatMax=2*TMAX to reduce fluctuations on the tails. How to use: To get a sample with a given pT, use "glob" regular expressions (in Jython, Python etc). Example for the code: pT>100 corresponds to "glob.glob(*pt100_*)". Slimmed as: Particle records are slimmed (all stable with pT>0.3 GeV) and (PID=5 || PID=6) or PID>22 && PID<38) or PID>10 && PID<17).
A model for spatial distributions of reflectivity in storm cells was fitted to digital radar data. The data were taken with a modified WSR-57 weather radar with 2.6-km resolution. The data consisted of modified B-scan records on magnetic tape of storm cells tracked at 0 deg elevation for several hours. The MIT L-band radar with 0.8-km resolution produced cross-section data on several cells at 1/2 deg elevation intervals. The model developed uses ellipses for contours of constant effective-reflectivity factor Z with constant orientation and eccentricity within a horizontal cell cross section at a given time and elevation. The centers of the ellipses are assumed to be uniformly spaced on a straight line, with areas linearly related to log Z. All cross sections are similar at different heights (except for cell tops, bottoms, and splitting cells), especially for the highest reflectivities; wind shear causes some translation and rotation between levels. Goodness-of-fit measures and parameters of interest for 204 ellipses are considered.
We propose Multiscale Flow, a generative Normalizing Flow that creates samples and models the field-level likelihood of two-dimensional cosmological data such as weak lensing. Multiscale Flow uses hierarchical decomposition of cosmological fields via a wavelet basis and then models different wavelet components separately as Normalizing Flows. The log-likelihood of the original cosmological field can be recovered by summing over the log-likelihood of each wavelet term. This decomposition allows us to separate the information from different scales and identify distribution shifts in the data such as unknown scale-dependent systematics. The resulting likelihood analysis can not only identify these types of systematics, but can also be made optimal, in the sense that the Multiscale Flow can learn the full likelihood at the field without any dimensionality reduction. We apply Multiscale Flow to weak lensing mock datasets for cosmological inference and show that it significantly outperforms traditional summary statistics such as power spectrum and peak counts, as well as machine learning–based summary statistics such as scattering transform and convolutional neural networks. We further show that Multiscale Flow is able to identify distribution shifts not in the training data such as baryonic effects. Finally, we demonstrate that Multiscale Flow can be used to generate realistic samples of weak lensing data.
Residential biomass combustion is a source of carbonaceous aerosol. Inefficient combustion, particularly of solid fuels produces large quantities of black and brown carbon (BC and BrC). These particle types are important as they have noted effects on climate forcing and human health. One method of measuring these quantities is by measurement of aerosol light-absorption and scattering, which can be performed using an aethalometer and nephelometer, respectively. These instruments are widely deployed in the study of ambient air and are frequently used in air quality modeling and source apportionment studies. In this study, we will describe (1) a method for measuring primary BC and BrC emissions from two residential log-fired wood hydronic heaters and (2) the BC and BrC emission from these devices over a wide range of operating conditions, such as cold-starts, warm-starts, four different levels of output ranging from 15% to 100% maximum rated output, and periods of repeated cycling. The range in flue-gas BC concentrations, measured using an aethalometer at the 880 nanometer (nm) wavelength, were between 5.09 × 10 2 and 2.24 × 10 4 micrograms per cubic meter (µg/m 3 ) while the scattering coefficient of the flue-gas, measured by a nephelometer at 880 nm, ranged between 2.20 × 10 3 and 8.56 × 10 5 inverse megameters (Mm –1 ). The BrC concentrations, measured using the 370 nm wavelength of an aethalometer, were between 9.10 × 10 1 and 3.56 × 10 4 µg/m 3 . The calculated Angstrom Absorption Exponent (AAE) of the flue-gas aerosol ranged between 1.54 and 3.63. Performing a comparison between the measured BC concentration and an external particulate matter (PM) concentration showed that overall BC makes up roughly a quarter of the PM emitted by either of the two appliances. Further for both appliances, the cold-start and the test phase immediately following it had the highest BC and BrC concentrations, the highest measured scattering coefficient, as well as a low AAE.