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DOE OSTI2015

Comparison of beam emission spectroscopy and gas puff imaging edge fluctuation measurements in National Spherical Torus Experiment

In this study, the close physical proximity of the Gas Puff Imaging (GPI) and Beam Emission Spectroscopy (BES) diagnostics on the National Spherical torus Experiment (NSTX) is leveraged to directly compare fluctuation measurements, and to study the local effects of the GPI neutral deuterium puff during H-mode plasmas without large Edge Localized Modes. The GPI and BES views on NSTX provide partially overlapping coverage of the edge and scrape-off layer (SOL) regions above the outboard midplane. The separation in the toroidal direction is 16°, and field lines passing through diagnostic views are separated by ∼20 cm in the direction perpendicular to the magnetic field. Strong cross-correlation is observed, and strong cross-coherence is seen for frequencies between 5 and 15 kHz. Also, probability distribution functions of fluctuations measured ∼3 cm inside the separatrix exhibit only minor deviations from a normal distribution for both diagnostics, and good agreement between correlation length estimates, decorrelation times, and structure velocities is found at the ±40% level. While the two instruments agree closely in many respects, some discrepancies are observed. Most notably, GPI normalized fluctuation levels exceed BES fluctuations by a factor of ∼9. BES mean intensity is found to be sensitive to the GPI neutral gas puff, and BES normalized fluctuation levels for frequencies between 1 and 10 kHz are observed to increase during the GPI puff.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2011

STOCHASTIC STAR FORMATION AND A (NEARLY) UNIFORM STELLAR INITIAL MASS FUNCTION

Recent observations indicate a lower H{alpha} to FUV ratio in dwarf galaxies than in brighter systems, a trend that could be explained by a truncated and/or steeper initial mass function (IMF) in small galaxies. However, at low star formation rates (SFRs), the H{alpha} to FUV ratio can vary due to stochastic sampling even for a universal IMF, a hypothesis that has, prior to this work, received limited investigation. Using SLUG, a fully stochastic code for synthetic photometry in star clusters and galaxies, we compare the H{alpha} and FUV luminosity in a sample of {approx}450 nearby galaxies with models drawn from a universal Kroupa IMF and a modified IMF, the integrated galactic initial mass function (IGIMF). Once random sampling and time evolution are included, a Kroupa IMF convolved with the cluster mass function (CMF) reproduces the observed H{alpha} distribution at all FUV luminosities, while a truncated IMF as implemented in current IGIMF models underpredicts the H{alpha} luminosity by more than an order of magnitude at the lowest SFRs. We conclude that the observed luminosity is the result of the joint probability distribution function of the SFR, CMF, and a universal IMF, consistent with parts of the IGIMF theory, but that a truncation in the IMF in clusters is inconsistent with the observations. Future work will examine stochastic star formation and its time dependence in detail to study whether random sampling can explain other observations that suggest a varying IMF.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2013

Estimated Probability of a Cervical Spine Injury During an ISS Mission

Introduction: The Integrated Medical Model (IMM) utilizes historical data, cohort data, and external simulations as input factors to provide estimates of crew health, resource utilization and mission outcomes. The Cervical Spine Injury Module (CSIM) is an external simulation designed to provide the IMM with parameter estimates for 1) a probability distribution function (PDF) of the incidence rate, 2) the mean incidence rate, and 3) the standard deviation associated with the mean resulting from injury/trauma of the neck. Methods: An injury mechanism based on an idealized low-velocity blunt impact to the superior posterior thorax of an ISS crewmember was used as the simulated mission environment. As a result of this impact, the cervical spine is inertially loaded from the mass of the head producing an extension-flexion motion deforming the soft tissues of the neck. A multibody biomechanical model was developed to estimate the kinematic and dynamic response of the head-neck system from a prescribed acceleration profile. Logistic regression was performed on a dataset containing AIS1 soft tissue neck injuries from rear-end automobile collisions with published Neck Injury Criterion values producing an injury transfer function (ITF). An injury event scenario (IES) was constructed such that crew 1 is moving through a primary or standard translation path transferring large volume equipment impacting stationary crew 2. The incidence rate for this IES was estimated from in-flight data and used to calculate the probability of occurrence. The uncertainty in the model input factors were estimated from representative datasets and expressed in terms of probability distributions. A Monte Carlo Method utilizing simple random sampling was employed to propagate both aleatory and epistemic uncertain factors. Scatterplots and partial correlation coefficients (PCC) were generated to determine input factor sensitivity. CSIM was developed in the SimMechanics/Simulink environment with a Monte Carlo wrapper (MATLAB) used to integrate the components of the module. Results: The probability of generating an AIS1 soft tissue neck injury from the extension/flexion motion induced by a low-velocity blunt impact to the superior posterior thorax was fitted with a lognormal PDF with mean 0.26409, standard deviation 0.11353, standard error of mean 0.00114, and 95% confidence interval [0.26186, 0.26631]. Combining the probability of an AIS1 injury with the probability of IES occurrence was fitted with a Johnson SI PDF with mean 0.02772, standard deviation 0.02012, standard error of mean 0.00020, and 95% confidence interval [0.02733, 0.02812]. The input factor sensitivity analysis in descending order was IES incidence rate, ITF regression coefficient 1, impactor initial velocity, ITF regression coefficient 2, and all others (equipment mass, crew 1 body mass, crew 2 body mass) insignificant. Verification and Validation (V&V): The IMM V&V, based upon NASA STD 7009, was implemented which included an assessment of the data sets used to build CSIM. The documentation maintained includes source code comments and a technical report. The software code and documentation is under Subversion configuration management. Kinematic validation was performed by comparing the biomechanical model output to established corridors.

Brooker, John E.↗

NASA NTRS2015

Wear-Out Sensitivity Analysis Project Abstract

During the course of the Summer 2015 internship session, I worked in the Reliability and Maintainability group of the ISS Safety and Mission Assurance department. My project was a statistical analysis of how sensitive ORU's (Orbital Replacement Units) are to a reliability parameter called the wear-out characteristic. The intended goal of this was to determine a worst case scenario of how many spares would be needed if multiple systems started exhibiting wear-out characteristics simultaneously. The goal was also to determine which parts would be most likely to do so. In order to do this, my duties were to take historical data of operational times and failure times of these ORU's and use them to build predictive models of failure using probability distribution functions, mainly the Weibull distribution. Then, I ran Monte Carlo Simulations to see how an entire population of these components would perform. From here, my final duty was to vary the wear-out characteristic from the intrinsic value, to extremely high wear-out values and determine how much the probability of sufficiency of the population would shift. This was done for around 30 different ORU populations on board the ISS.

Harris, Adam↗

DOE OSTI2017

A backward Monte-Carlo method for time-dependent runaway electron simulations

Kinetic descriptions of runaway electrons (REs) are usually based on Fokker-Planck models that determine the probability distribution function of REs in 2-dimensional momentum space. Despite the simplification involved, the Fokker-Planck equation can rarely be solved analytically and direct numerical approaches [e.g., continuum and particle-based Monte Carlo (MC)] can be time consuming, especially in the computation of asymptotic-type observables including the runaway probability, the slowing-down and runaway mean times, and the energy limit probability. In this study, we present a novel backward MC approach to these problems based on backward stochastic differential equations that describe the dynamics of the runaway probability by means of the Feynman-Kac theory. The key ingredient of the backward MC algorithm is to place all the particles in a runaway state and simulate them backward from the terminal time to the initial time. As such, our approach can provide much faster convergence than direct MC methods (by significantly reducing the number of particles required to achieve a prescribed accuracy) while at the same time maintaining the advantages of particle-based methods (compared to continuum approaches). The proposed algorithm is unconditionally stable and can be parallelized as easy as the direct MC method, and its extension to dimensions higher than two is straightforward, thus paving the way for conducting large-scale RE simulation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Pore-resolved investigation of turbulent open channel flow over a randomly packed permeable sediment bed

Pore-resolved direct numerical simulations are performed to investigate the interactions between streamflow turbulence and groundwater flow through a randomly packed porous sediment bed for three permeability Reynolds numbers, Re K = 2.56 , 5.17 and 8.94, representative of natural stream or river systems. Time–space averaging is used to quantify the Reynolds stress, form-induced stress, mean flow and shear penetration depths, and mixing length at the sediment–water interface (SWI). Here, the mean flow and shear penetration depths increase with Re K and are found to be nonlinear functions of non-dimensional permeability. The peaks and significant values of the Reynolds stresses, form-induced stresses, and pressure variations are shown to occur in the top layer of the bed, which is also confirmed by conducting simulations of just the top layer as roughness elements over an impermeable wall. The probability distribution functions (p.d.f.s) of normalized local bed stress are found to collapse for all Reynolds numbers, and their root-mean-square fluctuations are assumed to follow logarithmic correlations. The fluctuations in local bed stress and resultant drag and lift forces on sediment grains are mainly a result of the top layer; their p.d.f.s are symmetric with heavy tails, and can be well represented by a non-Gaussian model fit. The bed stress statistics and the pressure data at the SWI potentially can be used in providing better boundary conditions in modelling of incipient motion and reach-scale transport in the hyporheic zone.

turbulence simulation↗

DOE OSTI2017

Spatial distribution of internal heat gains: A probabilistic representation and evaluation of its influence on cooling equipment sizing in large office buildings

Internal heat gains from occupants, lighting, and plug loads are significant components of the space cooling load in an office building. Internal heat gains vary with time and space. The spatial diversity is significant, even for spaces with the same function in the same building. The stochastic nature of internal heat gains makes determining the peak cooling load to size air-conditioning systems a challenge. The traditional conservative practice of considering the largest internal heat gain among spaces and applying safety factors overestimates the space cooling load, which leads to oversized air-conditioning equipment and chiller plants. In this study, a field investigation of several large office buildings in China led to the development of a new probabilistic approach that represents the spatial diversity of the design internal heat gain of each tenant as a probability distribution function. In a large office building, a central chiller plant serves all air handling units (AHUs), with each AHU serving one or more floors of the building. Therefore, the spatial diversity should be considered differently when the peak cooling loads to size the AHUs and chillers are calculated. Finally, the proposed approach considers two different levels of internal heat gains to calculate the peak cooling loads and size the AHUs and chillers in order to avoid oversizing, improve the overall operating efficiency, and thus reduce energy use.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Lagrangian statistics in weakly forced two-dimensional turbulence

Measurements of Lagrangian single-point and multiple-point statistics in a quasi-two-dimensional stratified layer system are reported. The system consists of a layer of salt water over an immiscible layer of Fluorinert and is forced electromagnetically so that mean-squared vorticity is injected at a well-defined spatial scale r i . Simultaneous cascades develop in which enstrophy flows predominately to small scales whereas energy cascades, on average, to larger scales. Lagrangian correlations and one- and two-point displacements are measured for random initial conditions and for initial positions within topological centers and saddles. Some of the behavior of these quantities can be understood in terms of the trapping characteristics of long-lived centers, the slow motion near strong saddles, and the rapid fluctuations outside of either centers or saddles. We also present statistics of Lagrangian velocity fluctuations using energy spectra in frequency space and structure functions in real space. We compare with complementary Eulerian velocity statistics. We find that simultaneous inverse energy and enstrophy ranges present in spectra are not directly echoed in real-space moments of velocity difference. Nevertheless, the spectral ranges line up well with features of moment ratios, indicating that although the moments are not exhibiting unambiguous scaling, the behavior of the probability distribution functions is changing over short ranges of length scales. Furthermore, implications for understanding weakly forced 2D turbulence with simultaneous inverse and direct cascades are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

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↗

NASA NTRS2002

Mountain-Top-to-Mountain-Top Optical Link Demonstration

A mountain-top-to-mountain-top optical link was demonstrated between JPL's Table Mountain Facility (TMF), Wrightwood, California, and Strawberry Peak (SP), Lake Arrowhead, California, during the months of June, August, and September of 2000. The bidirectional laser link was nearly horizontal at an altitude of 2 km and spanned a range of 46.8 km. The 780-nm beacon laser transmitted from TMF comprised eight co-propagating mutually incoherent laser beams. The normalized variance or scintillation index (SI) of the individual beacon lasers measured by recording the signal received through 8.50-cm-diameter spotting telescopes on three different nights (June 28-30, 2000) was 1.05 +/- 0.2, 1.76 +/- 0.6, and 0.96 +/- 0.24, respectively. These measurements agreed with values predicted by a heuristic model. The SI of the signal received at SP was found to decrease progressively with an increasing number of beams, and a factor of 3 to 3.5 reduction was achieved for all eight beams. The beam divergence determined by mapping out the point spread function of a few of the individual laser footprints received at SP was 85 to 150 microrad, compared to a design goal of 120 microrad. The 852-nm communications laser beam received at TMF through a 60-cm-diameter telescope on the nights of August 4 and September 14 and 15, 2000, yielded SI values of 0.23 +/- 0.04, 0.32 +/- 0.01, and 0.49 +/- 0.18, respectively, where the reduction was attributed to aperture averaging. The probability distribution functions of the received signal at either end, mitigated by multi-beam averaging in one direction and by aperture averaging in the other direction, displayed lognormal behavior. Consequently, the measured fade statistics showed good agreement with a lognormal model.

Biswas, A.↗

NASA NTRS1995

Probabilistic simulation of long term behavior in polymer matrix composites

A methodology to compute cumulative probability distribution functions (CDF) of fatigue life for different ratios, r of applied stress to the laminate strength based on first ply failure criteria has been developed and demonstrated. Degradation effects due to long term environmental exposure and mechanical cyclic loads are considered in the simulation process. A unified time-stress dependent multi-factor interaction equation model developed at NASA Lewis Research Center has been used to account for the degradation/aging of material properties due to cyclic loads. Fast probability integration method is used to perform probabilistic simulation of uncertainties. Sensitivity of fatigue life reliability to uncertainties in the primitive random variables are computed and their significance in the reliability based design for maximum life is discussed. The results show that the graphite/epoxy (0/+45/90) deg laminate with ply thickness 0.125 in. has 500,000 cycles life for applied stress to laminate strength ratio of 0.6 and a reliability of 0.999. Also, the fatigue life reliability has been found to be most sensitive to the ply thickness and matrix tensile strength. Tighter quality controls must therefore be enforced on ply thickness and matrix strength in order to achieve high reliability of the structure.

Shah, A. R.↗

NASA NTRS1999

Statistical Perspectives on Stratospheric Transport

Long-lived tropospheric source gases, such as nitrous oxide, enter the stratosphere through the tropical tropopause, are transported throughout the stratosphere by the Brewer-Dobson circulation, and are photochemically destroyed in the upper stratosphere. These chemical constituents, or "tracers" can be used to track mixing and transport by the stratospheric winds. Much of our understanding about the stratospheric circulation is based on large scale gradients and other spatial features in tracer fields constructed from satellite measurements. The point of view presented in this paper is different, but complementary, in that transport is described in terms of tracer probability distribution functions (PDFs). The PDF is computed from the measurements, and is proportional to the area occupied by tracer values in a given range. The flavor of this paper is tutorial, and the ideas are illustrated with several examples of transport-related phenomena, annotated with remarks that summarize the main point or suggest new directions. One example shows how the multimodal shape of the PDF gives information about the different branches of the circulation. Another example shows how the statistics of fluctuations from the most probable tracer value give insight into mixing between different regions of the atmosphere. Also included is an analysis of the time-dependence of the PDF during the onset and decline of the winter circulation, and a study of how "bursts" in the circulation are reflected in transient periods of rapid evolution of the PDF. The dependence of the statistics on location and time are also shown to be important for practical problems related to statistical robustness and satellite sampling. The examples illustrate how physically-based statistical analysis can shed some light on aspects of stratospheric transport that may not be obvious or quantifiable with other types of analyses. An important motivation for the work presented here is the need for synthesis of the large and growing database of observations of the atmosphere and the vast quantities of output generated by atmospheric models.

Sparling, L. C.↗

NASA NTRS2006

Exploring the Connection Between Sampling Problems in Bayesian Inference and Statistical Mechanics

The Bayesian and statistical mechanical communities often share the same objective in their work - estimating and integrating probability distribution functions (pdfs) describing stochastic systems, models or processes. Frequently, these pdfs are complex functions of random variables exhibiting multiple, well separated local minima. Conventional strategies for sampling such pdfs are inefficient, sometimes leading to an apparent non-ergodic behavior. Several recently developed techniques for handling this problem have been successfully applied in statistical mechanics. In the multicanonical and Wang-Landau Monte Carlo (MC) methods, the correct pdfs are recovered from uniform sampling of the parameter space by iteratively establishing proper weighting factors connecting these distributions. Trivial generalizations allow for sampling from any chosen pdf. The closely related transition matrix method relies on estimating transition probabilities between different states. All these methods proved to generate estimates of pdfs with high statistical accuracy. In another MC technique, parallel tempering, several random walks, each corresponding to a different value of a parameter (e.g. "temperature"), are generated and occasionally exchanged using the Metropolis criterion. This method can be considered as a statistically correct version of simulated annealing. An alternative approach is to represent the set of independent variables as a Hamiltonian system. Considerab!e progress has been made in understanding how to ensure that the system obeys the equipartition theorem or, equivalently, that coupling between the variables is correctly described. Then a host of techniques developed for dynamical systems can be used. Among them, probably the most powerful is the Adaptive Biasing Force method, in which thermodynamic integration and biased sampling are combined to yield very efficient estimates of pdfs. The third class of methods deals with transitions between states described by rate constants. These problems are isomorphic with chemical kinetics problems. Recently, several efficient techniques for this purpose have been developed based on the approach originally proposed by Gillespie. Although the utility of the techniques mentioned above for Bayesian problems has not been determined, further research along these lines is warranted

Pohorille, Andrew↗

DOE OSTI2019

Precipitation characteristic changes due to global warming in a high‐resolution (16 km) ECMWF simulation

Changes in precipitation amount, intensity and frequency in response to global warming are examined using global high‐resolution (16 km) climate model simulations based on the European Centre for Medium‐range Weather Forecasts (ECMWF) Integrated Forecast System (IFS) conducted under Project Athena. Our study shows the increases of zonal‐mean total precipitation in all latitudes except the northern subtropics (15°–30°N) and southern subtropics‐to‐midlatitudes (30°–40°S). The probability distribution function (PDF) changes in different latitudes suggest a higher occurrence of light precipitation (LP; ≤1 mm/day) and heavy precipitation (HP; ≥30 mm/day) at the expense of moderate precipitation reduction (MP; 1–30 mm/day) from Tropics to midlatitudes, but an increase in all categories of precipitation in polar regions. On the other hand, the PDF change with global warming in different precipitation climatological zones presents another image. For all regions and seasons examined, there is an HP increase at the cost of MP, but LP varies. The reduced MP in richer precipitation zones resides in the PDF peak intensities, which linearly increase with the precipitation climatology zones. In particular in the Tropics (20°S to 20°N), the precipitation PDF has a flatter distribution (i.e. HP and LP increases with MP reduction) except for the Sahara Desert. In the primary precipitation zones in the subtropics (20°–40°) of both hemispheres, precipitation over land switches toward higher intensity (HP increases, but MP and LP decrease) in both winter and summer, while precipitation over ocean in both seasons shows a flattening trend in the intensity distribution. For the major precipitation zones of the mid‐to‐high latitude belt (40°–70°), PDF of precipitation tends to be flatter over ocean in summer, but switches toward higher intensities over land in both summer and winter, as well as over ocean in winter.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

The Impact of Nuclear Reaction Rate Uncertainties on the Evolution of Core-collapse Supernova Progenitors

We review properties of core-collapse supernova progenitors with respect to the composite uncertainties in the thermonuclear reaction rates by coupling the probability density functions of the reaction rates provided by the STARLIB reaction rate library with MESA stellar models. We evolve 1000 models of 15${M}_{\odot }$ from the pre-main sequence to core O-depletion at solar and subsolar metallicities for a total of 2000 Monte Carlo stellar models. For each stellar model, we independently and simultaneously sample 665 thermonuclear reaction rates and use them in a MESA in situ reaction network that follows 127 isotopes from 1 H to 64 Zn. With this framework we survey the core mass, burning lifetime, composition, and structural properties at five different evolutionary epochs. At each epoch we measure the probability distribution function of the variations of each property and calculate Spearman rank-order correlation coefficients for each sampled reaction rate to identify which reaction rate has the largest impact on the variations on each property. We find that uncertainties in the reaction rates of ${}^{14}{\rm{N}}{({\rm{p}},\gamma )}^{15}{\rm{O}}$, triple-α, ${}^{12}{\rm{C}}{(\alpha ,\gamma )}^{16}{\rm{O}}$, 12 C( 12 C,p) 23 Na, 12 C( 16 O, p) 27 Al, 16 O( 16 O,n) 31 S, 16 O( 16 O, p) 31 P, and 16 O( 16 O,α) 28 Si dominate the variations of the properties surveyed. We find that variations induced by uncertainties in nuclear reaction rates grow with each passing phase of evolution, and at core H-, He-depletion they are of comparable magnitude to the variations induced by choices of mass resolution and network resolution. Yet, at core C-, Ne-, and O-depletion, the reaction rate uncertainties can dominate the variation, causing uncertainty in various properties of the stellar model in the evolution toward iron core-collapse.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2016

Response Surface Modeling Tool Suite, Version 1.x

The Response Surface Modeling (RSM) Tool Suite is a collection of three codes used to generate an empirical interpolation function for a collection of drag coefficient calculations computed with Test Particle Monte Carlo (TPMC) simulations. The first code, "Automated RSM", automates the generation of a drag coefficient RSM for a particular object to a single command. "Automated RSM" first creates a Latin Hypercube Sample (LHS) of 1,000 ensemble members to explore the global parameter space. For each ensemble member, a TPMC simulation is performed and the object drag coefficient is computed. In the next step of the "Automated RSM" code, a Gaussian process is used to fit the TPMC simulations. In the final step, Markov Chain Monte Carlo (MCMC) is used to evaluate the non-analytic probability distribution function from the Gaussian process. The second code, "RSM Area", creates a look-up table for the projected area of the object based on input limits on the minimum and maximum allowed pitch and yaw angles and pitch and yaw angle intervals. The projected area from the look-up table is used to compute the ballistic coefficient of the object based on its pitch and yaw angle. An accurate ballistic coefficient is crucial in accurately computing the drag on an object. The third code, "RSM Cd", uses the RSM generated by the "Automated RSM" code and the projected area look-up table generated by the "RSM Area" code to accurately compute the drag coefficient and ballistic coefficient of the object. The user can modify the object velocity, object surface temperature, the translational temperature of the gas, the species concentrations of the gas, and the pitch and yaw angles of the object. Together, these codes allow for the accurate derivation of an object's drag coefficient and ballistic coefficient under any conditions with only knowledge of the object's geometry and mass.

Walker, Andrew↗

DOE OSTI2016

Response Surface Modeling Tool Suite, Version 1.x

Walker, Andrew↗

DOE OSTI2016

Environmental dependence of the galaxy stellar mass function in the Dark Energy Survey Science Verification Data

Measurements of the galaxy stellar mass function are crucial to understand the formation of galaxies in the Universe. In a hierarchical clustering paradigm it is plausible that there is a connection between the properties of galaxies and their environments. Evidence for environmental trends has been established in the local Universe. The Dark Energy Survey (DES) provides large photometric datasets that enable further investigation of the assembly of mass. In this study we use ~3.2 million galaxies from the (South Pole Telescope) SPT-East field in the DES science verification (SV) dataset. From grizY photometry we derive galaxy stellar masses and absolute magnitudes, and determine the errors on these properties using Monte-Carlo simulations using the full photometric redshift probability distributions. We compute galaxy environments using a fixed conical aperture for a range of scales. We construct galaxy environment probability distribution functions and investigate the dependence of the environment errors on the aperture parameters. We compute the environment components of the galaxy stellar mass function for the redshift range 0.15 < z < 1.05. For z < 0.75 we find that the fraction of massive galaxies is larger in high density environment than in low density environments. We show that the low density and high density components converge with increasing redshift up to z ~ 1.0 where the shapes of the mass function components are indistinguishable. As a result, our study shows how high density structures build up around massive galaxies through cosmic time.

79 ASTRONOMY AND ASTROPHYSICS↗