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At least 397 records · Page 22

Clustering of red sequence galaxies in the fourth data release of the Kilo-Degree Survey

We present a sample of luminous red sequence galaxies as the basis for a study of the large-scale structure in the fourth data release of the Kilo-Degree Survey. The selected galaxies are defined by a red sequence template, in the form of a data-driven model of the colour-magnitude relation conditioned on redshift. In this work, the red sequence template was built using the broad-band optical+near infrared photometry of KiDS-VIKING and the overlapping spectroscopic data sets. The selection process involved estimating the red sequence redshifts, assessing the purity of the sample and estimating the underlying redshift distributions of redshift bins. After performing the selection, we mitigated the impact of survey properties on the observed number density of galaxies by assigning photometric weights to the galaxies. We measured the angular two-point correlation function of the red galaxies in four redshift bins and constrain the large-scale bias of our red sequence sample assuming a fixed ΛCDM cosmology. We find consistent linear biases for two luminosity-threshold samples (‘dense’ and ‘luminous’). We find that our constraints are well characterised by the passive evolution model.

79 ASTRONOMY AND ASTROPHYSICS↗

Energy considerations regarding pulsed arc production of nanomaterials

Atmospheric arc discharge volumes have been estimated from the light distribution emitted during evaporation of graphite and molybdenum disulphide (MoS 2 ) anodes. These data have been correlated to the peak power in the case of pulsed arc discharge held at different frequencies (1, 2 and 5 Hz). The measured power density values and the corresponding specific energies per particle have been compared to DC values, and showed that pulsed arc discharges deliver electrical power more efficiently than DC arc discharges do with yet lower thermal loads. In particular, the power density of ≈1 kW/cm 3 characteristic of pulsed arcs (10-20 kW/cm 3 in DC) suffices to provide 15 eV/particle to the arc plasma (≈10 eV/particle or less in DC). Such an energy balance resulted in high ionization rates of the ablated material and production yields of carbon nanotubes around 10 11 cm -2 kWh -1 . Lastly, in situ probe experiments showed that pulsed arcs enhance the transport to substrate of the generated nanoparticles, such as graphene and MoS 2 monolayers. Pulsed anodic arcs open the possibility to generate further nanomaterials thanks to a more rational power investment and a better control of the discharge region.

42 ENGINEERING↗

Looking at the bigger picture: Identifying the photoproducts of pyruvic acid at 193 nm

Here, photodissociation of pyruvic acid (PA) was studied in the gas-phase at 193 nm using two complementary techniques. The time-sliced velocity map imaging arrangement was used to determine kinetic energy release distributions of fragments and estimate dissociation timescales. The multiplexed photoionization mass spectrometer setup was used to identify and quantify photoproducts, including isomers and free radicals, by their mass-to-charge ratios, photoionization spectra, and kinetic time profiles. Using these two techniques, it is possible to observe the major dissociation products of PA photodissociation: CO 2 , CO, H, OH, HCO, CH 2 CO, CH 3 CO, and CH 3 . Acetaldehyde and vinyl alcohol are minor primary photoproducts at 193 nm, but products that are known to arise from their unimolecular dissociation, such as HCO, H 2 CO, and CH 4 , are identified and quantified. A multivariate analysis that takes into account the yields of the observed products and assumes a set of feasible primary dissociation reactions provides a reasonable description of the photoinitiated chemistry of PA despite the necessary simplifications caused by the complexity of the dissociation. These experiments offer the first comprehensive description of the dissociation pathways of PA initiated on the S 3 excited state. Most of the observed products and yields are rationalized on the basis of three reaction mechanisms: (i) decarboxylation terminating in CO 2 + other primary products (~50%); (ii) Norrish type I dissociation typical of carbonyls (~30%); and (iii) O—H and C—H bond fission reactions generating the H atom (~10%). The analysis shows that most of the dissociation reactions create more than two products. This observation is not surprising considering the high excitation energy (~51 800 cm –1 ) and fairly low energy required for dissociation of PA. We find that two-body fragmentation processes yielding CO 2 are minor, and the expected, unstable primary co-fragment, methylhydroxycarbene, is not observed because it probably undergoes fast secondary dissociation and/or isomerization. Norrish type I dissociation pathways generate OH and only small yields of CH 3 CO and HOCO, which have low dissociation energies and further decompose via three-body fragmentation processes. Experiments with d 1 -PA (CH 3 COCOOD) support the interpretations. The dissociation on S 3 is fast, as indicated by the products’ recoil angular anisotropy, but the roles of internal conversion and intersystem crossing to lower states are yet to be determined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Temporal Characterization and Filtering of Sensor Data to Support Anomaly Detection

Here, we present an approach for characterizing complex temporal behavior in the sensor measurements of a system in order to support detection of anomalies in that system. We first characterize typical behavior by extending a hidden Markov model-based approach to time series alignment. We then use a trace of that learned behavior to develop a particle filter that enables efficient estimation of the filtering distribution on the state space. This produces filtered residuals that can then be used in an anomaly detection framework. Our motivating example is the daily behavior of a building’s heating, ventilation, and air conditioning (HVAC) system, using sensor measurements that arrive every minute and induce a state space with 15,120 states. We provide an end-to-end demonstration of our approach showing improved performance of anomaly detection after application of alignment and filtering compared to the unaligned data. The proposed model is implemented as a computationally efficient R package alignts (align time series) built with R and Fortran 95 with OpenMP support.

47 OTHER INSTRUMENTATION↗

Investigations on a fuzzy process: effect of diffusion on calibration and particle identification in Liquid Argon Time Projection Chambers

Ionization electron diffusion in Liquid Argon Time Projection Chambers (LArTPCs) has typically been considered at the detector design stage, but little attention has been given to its effects on calibration and particle identification. We use a GEANT4-based simulation to study how diffusion impacts these techniques, and give consideration to how this effect is simulated. We find that diffusion can cause a drift-dependent bias to both the median and Most Probable Value (MPV) of dQ/dx distributions. The bias is estimated to be ~2.5% (median) and ~5.0% (MPV) for typical maximum drift times in currently running LArTPCs before adding detector specific considerations such as electric field non-uniformities. This information indicates that these metrics should not be used for calibration without care, contrary to the conventional wisdom. The impact of diffusion on the ability of LArTPCs to separate muons and protons is small, and not expected to pose any problems in future detectors. Diffusion may however be a significant source of systematic uncertainty when separating particles of more similar masses (muons and pions, kaons and protons). Separation of such populations may be improved by implementation of a drift-time dependent particle identification.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Generative adversarial networks for scintillation signal simulation in EXO-200

Generative Adversarial Networks trained on samples of simulated or actual events have been proposed as a way of generating large simulated datasets at a reduced computational cost. In this work, a novel approach to perform the simulation of photodetector signals from the time projection chamber of the EXO-200 experiment is demonstrated. The method is based on a Wasserstein Generative Adversarial Network — a deep learning technique allowing for implicit non-parametric estimation of the population distribution for a given set of objects. Our network is trained on real calibration data using raw scintillation waveforms as input. We find that it is able to produce high-quality simulated waveforms an order of magnitude faster than the traditional simulation approach and, importantly, generalize from the training sample and discern salient high-level features of the data. In particular, the network correctly deduces position dependency of scintillation light response in the detector and correctly recognizes dead photodetector channels. Furthermore, the network output is then integrated into the EXO-200 analysis framework to show that the standard EXO-200 reconstruction routine processes the simulated waveforms to produce energy distributions comparable to that of real waveforms. Finally, the remaining discrepancies and potential ways to improve the approach further are highlighted.

47 OTHER INSTRUMENTATION↗

Rapid Shifts in the Temperature Dependence of Locomotor Performance in an Invasive Frog, Xenopus laevis , Implications for Conservation

Abstract Temperature is a critical abiotic factor impacting all aspects of the biology of organisms, especially in ectotherms. As such, it is an important determinant of the potential invasive ability of organisms and may limit population expansion unless organisms can physiologically respond to changes in temperature either through plasticity or by adapting to their novel environment. Here, we studied the African clawed frog, Xenopus laevis, which has become invasive on a global scale. We compared adults from an invasive population of western France with individuals from two populations in the native range in South Africa. We measured the thermal dependence of locomotor performance in adults given its relevance to dispersal, predator escape, and prey capture. Our results show significant differences in the limits of the 80% performance breadth interval for endurance with the French population showing a left shift in its limits congruent with the colder climate experienced in France. The French invasive population was introduced only about 40 years ago suggesting a rapid shift in the thermal physiology. Given that all individuals were acclimated under laboratory conditions at 23°C for 2 months this suggests that the invasive frogs have adapted to their new environment. These data may allow the refinement of physiologically informed species distribution models permitting better estimates of future ranges at risk of invasion.

Araspin, Laurie↗

Direct observation of the momentum distribution and renormalization factor in lithium

We have measured the momentum distribution and renormalization factor $Z_{k_F}$ in liquid and solid lithium by high-resolution Compton scattering. High-resolution data over a wide momentum range exhibit a clear feature of the renormalization and a sharp drop of momentum densities at the Fermi momentum $k_F$. In this work, these results are compared with those computed by quantum Monte Carlo simulation performed both on a disordered crystal and a liquid exhibiting very good agreement. Asymptotic behavior of the experimental and theoretical momentum distributions are examined to estimate $Z_{k_F}$. The experimentally obtained $Z_{k_F} = 0.43^{+0.11}_{–0.01}$ for liquid Li and $0.54^{+0.11}_{–0.02}$ for solid Li are in good agreement with theoretical results of 0.54 ± 0.01 and 0.64 ± 0.01, respectively.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Theory for the Response of Tropical Moist Convection to Mechanical Orographic Forcing

Abstract Spatial patterns of tropical rainfall are strongly influenced by mountains. Although theories for precipitation induced by convectively stable upslope ascent exist for the midlatitudes, these do not represent the interaction of moist convection with orographic forcing. Here, we present a theory for convective precipitation produced by the mechanical interaction of a tropical ridge with a basic-state horizontal wind. Deviations from this basic state are represented as the sum of a “dry” perturbation, due to the stationary orographic gravity wave, and a “moist” perturbation that carries the convective response. The moist component dynamics are subject to the weak temperature gradient approximation; they are forced by the dry mode’s influence on lower-tropospheric moisture and temperature. Analytical solutions provide estimates of the precipitation distribution, including peak precipitation, upstream extent, and rain shadow extent. The theory can be used with several degrees of complexity depending on the technique used to compute the dry mode, which can be drawn from linear mountain wave theory or full numerical simulations. To evaluate the theory, we use a set of convection-permitting simulations with a flow-perpendicular ridge in a long channel. The theory makes a good prediction for the cross-slope precipitation profile, indicating that the organization of convective rain by orography can be quantitatively understood by considering the effect of stationary orographic gravity waves on a lower-tropospheric convective quasi-equilibrium state.

54 ENVIRONMENTAL SCIENCES↗

1999 Puget Sound Household Travel Survey

The 1999 Puget Sound Household Travel Survey was conducted between July and November. NuStats Research and Consulting conducted the survey on behalf of the Puget Sound Regional Council. The purpose of the study was to provide data to continue developing and refining the Regional Travel Demand Forecasting Model, as well as to provide a better understanding of travel behavior in the Puget Sound region. The study area consists of King, Kitsap, Pierce, and Snohomish counties. The resultant dataset will be used to fulfill the model's functions of estimating trip generation and distribution, mode choice, and assignments. The study had household members 16 years old or older keep track of travel for a 48-hour period. A total of 9,028 households were recruited to participate in the study. Of these, 6,000 households (66.5%) completed travel diaries, and the information was retrieved from all household members regardless of age. An “attitude” survey about transportation and land use issues was also mailed to household members 16 years old or older.

1Hz data↗

1998/99 Thurston County Household Travel Study

The survey was conducted under the auspices of the Thurston Regional Planning Council, and it was funded through a state grant awarded to Intercity Transit of Olympia, Washington. Data collection was from September 1998 through March 1999. The purpose of the study was to provide data for the continuing development and refinement of the Regional Travel Demand Forecasting Model, as well as to provide a better understanding of travel behavior in the southern Puget Sound region of Washington. The resultant data set will be used to fulfill the model's functions of estimating trip generation and distribution, mode choice, and assignments. Participating households were assigned specific “travel days” to record their travel over a 48-hour period. A total of 2,465 households were recruited to participate in the study. Of these, 1,537 households completed travel diaries, and the information was retrieved from 3,653 household members regardless of age. Households member made 25,278 total trips during their 48-hour diary period.

1Hz data↗

Ion Trapping Studies and Mitigation Strategies for the EIC ERL-Based Strong Hadron Cooler

An Energy Recovery Linac based strong hadron cooler was previously considered for the Electron-Ion Collider. The required electron beam parameters for variable-energy strong hadron cooling place significant constraints on ion trapping and collective effects. This paper presents initial studies of these constraints through a combination of analytical modelling and numerical simulations of ion production, trapping behaviour, and mitigation strategies. A multi-bunch tracking framework based on ELEGANT with the ionEffects module is used to simulate machine operation over millisecond time scales, corresponding to more than 3 × 10^5 electron bunches. The simulations include modelling of ionisation processes together with transverse electron–ion dynamics, allowing the evolution and accumulation of ions to be investigated. Analytical expressions based on Gaussian beam distributions are used to estimate ion trapping conditions and benchmark the simulation results. A bi-periodic bunch spacing scheme is also investigated as a possible mitigation method by detuning the ion oscillation frequency. These studies provide an initial assessment of ion trapping in the strong hadron cooler and demonstrate possible approaches for reducing beam–ion effects.

Bi, R. [Lancaster University, Cockcroft Institute]↗

Simple Acceptance Decisions and Acceptance Risk

Acceptance risk may be estimated using cumulative probability distribution functions applied to populations of measurands and test measurement values. “Simple acceptance” is a decision rule that sets the acceptance range of a test result equal to the tolerance range specification. While acceptance risk is comprised of both consumer risk and producer risk, this paper compares the effects of simple acceptance decision rules and guardbanding decision rules on consumer risk. Consumer risk is also known as the probability of false acceptance. The terms describe the risk of accepting test results as passing when the actual values exceed specification limits. False acceptance is only possible when the true value of a measurand is out of tolerance and the test result indicates that the measurand is within tolerance. Metrologists generally have some information about the test uncertainty regarding a specific acceptance test result. Along with a general lack of knowledge regarding the measurand population parameters, the complicated interplay between risk, dispersion, and central values generally prevents calibration laboratories from fully characterizing acceptance probabilities. Organizations that model the measurand populations can reduce consumer risk by avoiding certification of items whose measurand populations are not well centered. The models in this paper present a recurring trend: guardbanding reduces nonnegligible risks of false acceptance when compared to simple acceptance. However, guardbanding is not the most effective means of acceptance risk mitigation. Systematic characterization of measurand populations can provide the information a calibration laboratory needs to reliably control acceptance risk.

42 ENGINEERING↗

Consumer Purchasing Behavior and Usage of Lighting in the Residential Sector

We present the results of a 2019 online survey of 1,800 adults in the United States who recently purchased a light bulb to understand how consumers make decisions about purchasing light bulbs and how light bulbs are used in the residential sector. From our survey, we found that purchases of LED bulbs made up the largest percentage of sales by lighting technology and respondents generally had positive impressions of LEDs. We estimated the average daily hours of use for bulbs being purchased depending on bulb shape. We also provide an estimate for the lumen distribution of purchased light bulbs and the distribution of installation locations by bulb shape. We found that incandescent bulb purchasers were primarily replacing a failed incandescent bulb and these purchasers were less likely to have favorable impressions of LEDs. However, we found that the majority of participants replacing an incandescent bulb purchased either a CFL or LED. Using an adaptive conjoint analysis technique, we found that the five most important factors to consumers when choosing a light bulb are purchase price, bulb lifetime, energy cost savings relative to an incandescent bulb, light appearance, and energy savings relative to an incandescent bulb. The results of this study provide an in-depth look at the lighting market in 2019 and may provide a basis for developing models of the residential lighting market.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Model-based quantification of margins and uncertainties in metal additive manufacturing for process design and qualification

Laser powder bed fusion (LPBF) Additive Manufacturing (AM) has the potential to enable the production of components with novel designs and material properties unachievable otherwise. However, process repeatability is a challenge, making qualification ill-defined and greatly reducing the utility of what could be an important manufacturing technology. In this work, a combination of modeling, uncertainty quantification (UQ), and experimentation are used in an effort to predict and bound the range of possible outcomes of the LPBF process. Quantities of interest predicted are melt pool dimensions, microstructure features, and mechanical distortions. A combination of high fidelity thermal-fluid models, microstructure growth models, and reduced fidelity, rapid thermal and mechanical models are used. Uncertainty propagation techniques are used to predict probability distributions of quantities of interest from estimates of process uncertainties. Repeated experiments are done to quantify observed probability distributions and compared to predicted distributions to determine if predictions are precise and accurate. Novel modeling methods are microstrucutre characterization techniques are also discussed. It is found that high fidelity models do a generally good job bounding experimentally observed melt pool morphologies for both bead-on-plate and powder bed cases. Microstructure models are able to bound a number of experimentally observed microstructure statistics, but with low precision due to challenges with calibrating the microstructure growth model parameters. A developed modified inherent strain distortion model does not accurately predict observed distortions. A lumped laser distortion model shows promise in being both accurately and precisely bounding observed outcomes from the deflection comb build, but requires further evaluation on more builds and geometries.

36 MATERIALS SCIENCE↗

Investigation of Best-Practices and Computationally Inexpensive Radiative Exchange Models for Discrete Element Method Modeling of Aluminosilicate Particles in Concentrating Solar Power Environments

Chemically inert, aluminosilicate based particles have been investigated as both a thermal transport and sensible energy storage medium for concentrating solar power facilities. These particles will experience a wide range of operating temperatures (300-1000 K) and handling conditions (dense to dilute falling particle curtains, dense granular flows, or dense structures), requiring specially-designed and optimized infrastructures. The relative influence of collisional and frictional interactions between particles varies based on temperature-dependent particulate properties and greatly impacts the bulk, granular flow behavior. These underlying physics are captured using discrete element method modeling tools. However, this modeling method is computationally expensive as each particle position and interaction is tracked during the simulation. These modeling methods are further complicated by introducing temperature-dependent particle properties, high-temperature radiative exchange, and directional irradiation sources experienced by granular flows in concentrating solar power environments. In this study, coupled experimental and numerical slump testing of aluminosilicate particles was performed and computationally efficient radiative exchange models were evaluated to establish best-practices for discrete element method models for concentrating solar power environments. The three particle types investigated included Carbobead HSP 30 /60, Carbobead CP 30/60, and Granusil 4030. Existing modeling limitations and computationally-efficient multi-modal heat transfer models were evaluated using Aspherix®, a commercial discrete element method software. High-temperature (< 1073 K) slump testing of aluminosilicate particles was performed to investigate the deviation between experimentally-observed and numerically-predicted angles of repose introduced by computation-time reduction practices including the relaxation of the particle elastic modulus and coarse-graining. Coarse-graining is used to use a single modeled particle that is representative of a collection of smaller particles, decreasing the computational cost at the expense of geometric accuracy. Additionally, relaxation of the elastic modulus is used to reduce computational time at the expense of an increased, modeled particle overlap. Prior studies have determined that aluminosilicate particles retain a high elastic modulus at high temperatures (< 1073 K), requiring small simulation timesteps to ensure resolved contact forces resemble appropriate solid mechanics. A parametric study was performed to evaluate the influence of computation time improvements on the deviation between experimental and modeled angle of repose across high temperatures < 1073 K. Additionally, numerical case studies were performed on candidate particle systems at varying porosities and temperatures. These studies were performed to investigate the influence of computationally-efficient radiative-exchange modeling methods coupled to Aspherix® on modeled accuracy and computation time. The recently-developed distance-based approximation was evaluated in estimating radiative exchange between particles and participating surfaces located in close proximity. The distance based approximation was developed to use tabulated estimates of the radiative distribution factor between individual particles and surfaces in close proximity (< 40 particle radii). These methods were expanded to the aluminosilicate particles of interest, including the influence of particle size distributions. To capture radiative exchange between particles and surfaces not in close proximity (> 40 particle radii) and to capture the absorption of directional irradiation from concentrating solar resources, a volumetrically-averaged radiative distribution factor was calculated between the modeled granular flow and surfaces using Monte Carlo ray-tracing for participating media. Volume-averaged absorption and scattering coefficients were predicted using a volumetric discretization of the modeled domain with monodisperse approximations based on geometric optics and experimentally-determined scattering phase functions for aluminosilicate particles.

14 SOLAR ENERGY↗