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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

A partial list of southern clusters of galaxies

An inspection of 34 SRC/ESO J southern sky fields is the basis of the present list of clusters of galaxies and their approximate classifications in terms of cluster concentration, defined independently of richness and shape-symmetry. Where possible, an estimate of the cluster morphological population is provided. The Bautz-Morgan classification was applied using a strict comparison with clusters on the Palomar Sky Survey. Magnitudes were estimated on the basis of galaxies with photoelectric or photographic magnitudes.

Quintana, H.↗
NASA NTRS2016

Estimating the Rate of Occurrence of Renal Stones in Astronauts

Changes in urine chemistry, during and post flight, potentially increases the risk of renal stones in astronauts. Although much is known about the effects of space flight on urine chemistry, no inflight incidence of renal stones in US astronauts exists and the question "How much does this risk change with space flight?" remains difficult to accurately quantify. In this discussion, we tackle this question utilizing a combination of deterministic and probabilistic modeling that implements the physics behind free stone growth and agglomeration, speciation of urine chemistry and published observations of population renal stone incidences to estimate changes in the rate of renal stone presentation. The modeling process utilizes a Population Balance Equation based model developed in the companion IWS abstract by Kassemi et al. (2016) to evaluate the maximum growth and agglomeration potential from a specified set of urine chemistry values. Changes in renal stone occurrence rates are obtained from this model in a probabilistic simulation that interrogates the range of possible urine chemistries using Monte Carlo techniques. Subsequently, each randomly sampled urine chemistry undergoes speciation analysis using the well-established Joint Expert Speciation System (JESS) code to calculate critical values, such as ionic strength and relative supersaturation. The Kassemi model utilizes this information to predict the mean and maximum stone size. We close the assessment loop by using a transfer function that estimates the rate of stone formation from combining the relative supersaturation and both the mean and maximum free stone growth sizes. The transfer function is established by a simulation analysis which combines population stone formation rates and Poisson regression. Training this transfer function requires using the output of the aforementioned assessment steps with inputs from known non-stone-former and known stone-former urine chemistries. Established in a Monte Carlo system, the entire renal stone analysis model produces a probability distribution of the stone formation rate and an expected uncertainty in the estimate. The utility of this analysis will be demonstrated by showing the change in renal stone occurrence predicted by this method using urine chemistry distributions published in Whitson et al. 2009. A comparison to the model predictions to previous assessments of renal stone risk will be used to illustrate initial validation of the model.

gravitational physiology↗
NASA NTRS1988

Radiation safety in commercial air traffic - A need for further study

The problem of radiation exposure of crewmembers in high altitude supersonic commercial aircraft is addressed. As a result of recent changes in the quality factors for radiological protection, it is found that worst case estimates of radiation exposure are now well above the exposure limits of the general population, and a reassessment of radiation impact on commercial aviation is needed, if the proposed quality factors are adopted. Calculations are presented from a study on neutron dosage equivalent rates. It is shown that a crew flying at altitudes near 13 km (43,000 ft) for 40 hr/mo would receive exposure levels of 47-75 Sv/yr, and it is suggested that such crewmembers be considered as radiation workers, rather than general population members. However, since present exposure estimates need to be improved, and the maximum permissible dose limits are currently under revision, the final exposure limits are, as yet, unclear, suggesting the need for further study to clarify the work status of commercial aircrews.

Wilson, John W.↗
DOE OSTI2020

A large-scale, agent-based simulation of metropolitan freight movements with passenger and freight market interactions

This study summarizes the first stage in the implementation of an agent-based freight modeling system that has a global representation of agents and detailed modeling of a large-scale transportation network. The model is used to evaluate the transportation and energy impacts of goods movement across urban and national scales. The framework is implemented within POLARIS, a C++-based Planning and Operations Language for Agent-based Regional Integrated Simulation, which consists of an activity-based modeling (ABM) and dynamic traffic assignment (DTA) system that has robust features for passenger travel. This platform provides a tool to model interactions among consumers, producers, and the transportation system. The main objective of this initial implementation is to implement a freight model within POLARIS following an agent-based paradigm with behavioral and simulation methods. This paper presents the initial framework and illustrates the application of the model. Building upon earlier works, a parcel location assignment algorithm for business establishments in the population is documented, along with a method for estimating establishment production and consumption volumes. In addition to population generation, other features of the model include push-pull supply chains, multimodal path choice, choice of transportation logistics node, and dynamic traffic assignment. A module with e-commerce supply and demand was also developed to analyze the effects of e-commerce delivery on last-mile energy use and congestion.

agent-based freight↗
NASA NTRS1993

Triton's cratering record and its time of capture

Recent impact crater counts on the Voyager 2 high resolution images of Triton have resulted in a more accurate crater size/frequency distribution down to about 3 km diameter. These counts reveal a size/frequency distribution characterized by a differential -4 slope. This is consistent with the observation that there are no craters larger than 27 km diameter on the 20 percent of Triton viewed at resolutions capable of detecting them. A -4 slope is deficient in large craters and at the very low crater density on Triton no craters larger than about 30 km are expected on just 20 percent of the satellite. The Triton size distribution is significantly different from the differential -3 slope of the fresh crater population on Miranda, but both show leading/trailing asymmetries. Since Miranda is in prograde orbit this crater population is probably due to objects in heliocentric orbit, i.e., comets. If this crater population is due to comets, then the significantly different crater population on Triton is probably due to some other population of impacting objects. The most likely origin of these objects is planetesimals in planetocentric orbits. Because Triton is in retrograde orbit, objects in prograde planetocentric orbits will also produce a leading/trailing asymmetry. If the Triton craters are largely the result of objects in planetocentric orbit, then where are the comet craters that should be there if they have a differential -3 distribution function as inferred from the Miranda fresh crater population? The most likely answer is that they are there, but at such a low density that they can not be distinguished from the planetocentric population. An upper bound on this density can be estimated by determining the density of a crater population with a differential -3 slope where no craters larger than 27 km would be expected on the 20 percent of Triton viewed by Voyager at resolutions sufficient to detect them. This density is at the density of the largest crater. At this density the number of craters in size bins greater than 27 km is less than 1 for a -3 distribution function. The observed size distribution, the upper limit of the hypothetical comet crater size distribution, and the difference between the observed and the hypothetical comet crater populations is shown.

Strom, R. G.↗
NASA NTRS2011

The Conundrum of Impacts of Climate Change on Urbanization and the Urban Heat Island Effect

The twenty-first century is the first urban century according to the United Nations Development Program. The focus on cities reflects awareness of the growing percentage of the world's population that lives in urban areas. In 2000, approximately 3 billion people representing about 40% of the global population resided in urban areas. The United Nations estimates that by 2025, 60% of the world s population will live in urban areas. As a consequence, the number of megacities (those cities with populations of 10 million inhabitants or more) will increase by 100 by 2025. Thus, there is a critical need to understand the spatial growth of urban areas and what the impacts are on the environment. Moreover, there is a critical need to assess how under global climate change, cities will affect the local, regional, and even global climate. As urban areas increase in size, it is anticipated there will be a concomitant growth of the Urban Heat Island effect (UHI), and the attributes that are related to its spatial and temporal dynamics. Therefore, how climate change, including the dynamics of the UHI, will affect the urban environment, must be explored to help mitigate potential impacts on the environment (e.g., air quality, heat stress, vectorborne disease) and on human health and well being, to develop adaptation schemes to cope with these impacts.

Quattrochi, Dale A.↗
NASA NTRS2016

Improving the Accuracy of Predicting Maximal Oxygen Consumption (VO2pk)

Maximal oxygen (VO2pk) is the maximum amount of oxygen that the body can use during intense exercise and is used for benchmarking endurance exercise capacity. The most accurate method to determineVO2pk requires continuous measurements of ventilation and gas exchange during an exercise test to maximal effort, which necessitates expensive equipment, a trained staff, and time to set-up the equipment. For astronauts, accurate VO2pk measures are important to assess mission critical task performance capabilities and to prescribe exercise intensities to optimize performance. Currently, astronauts perform submaximal exercise tests during flight to predict VO2pk; however, while submaximal VO2pk prediction equations provide reliable estimates of mean VO2pk for populations, they can be unacceptably inaccurate for a given individual. The error in current predictions and logistical limitations of measuring VO2pk, particularly during spaceflight, highlights the need for improved estimation methods.

Downs, Meghan E.↗
NASA NTRS2017

Comprehensive Measurement of Microbial Burden in Nutrient-Deprived Cleanrooms

Spacecraft surfaces that are destined to land on potential life-harboring celestial bodies are required to be rigorously cleaned and continuously monitored for spore bioburden as a proxy for spacecraft cleanliness. The NASA standard spore assay (NSA), used for spacecraft bioburden estimates, specifically measures spores that are cultivable, aerobic, resistant to heat shock, and grow at 30˚C in a nutrient-rich medium. Since the vast majority of microorganisms cannot be cultivated using the NSA assay, it is necessary to utilize state-of-the art molecular techniques to better understand the presence of all viable microorganisms, not just those measured with the NSA. In this study, the nutrient-deprived low biomass cleanrooms, where spacecraft are assembled, were used as a surrogate to spacecraft surfaces to measure the ratio of NSA spores in relation to the total viable microorganism population to compare with a 2006 space studies report that estimates that for every 1 spore there is approximately 50,000 viable organisms. Ninety-eight surface wipe samples were collected from the spacecraft assembly facility (SAF) cleanroom at the Jet Propulsion Laboratory (JPL) over a 6-month period. The samples were processed and analyzed using classical microbiology along with molecular assays. Traditional microbiology plating methods were used to determine the cultivable bacterial, fungal, and spore populations. Molecular assays were used to determine the total organisms (TO, dead and live) and the viable organisms (VO, live). The TO was measured using adenine triphosphate (ATP) and quantitative polymerase chain reaction (qPCR) assays. The VO was measured using internal ATP, propidium monoazide (PMA)-qPCR, and flow cytometry (after staining for viable microorganisms) assays. Based on the results, it was possible to establish a ratio between spore counts and VO for each viability assay. The ATP based spore to VO ratio ranged from 149 – 746 and the bacterial PMA-qPCR assay based ratio ranged from 314 – 1491 VO. The most conservative estimate came from FACS, which estimated the ratio to be 12,091 VO per 1 NSA spore. Since archaeal (<1%) and fungal (~2%) populations were negligible, the spore to VO ratios were based on bacterial population estimates. The most conservative ratio from this study can be used as a replacement for the SSB estimate on nutrient-deprived (oligotrophic) desiccated spacecraft surfaces, to estimate the VO from NSA measurements without utilizing state-of-the art molecular methods that are costly and require more biomass than is typically found of spacecraft surfaces.

Venkateswaran, Kasthuri↗
NASA NTRS2004

Human-Induced Climate Variations Linked to Urbanization: From Observations to Modeling

The goal of this session is to bring together scientists from interdisciplinary backgrounds to discuss the data, scientific approaches and recent results focusing on the impact of urbanization on the climate. The discussion will highlight current observational and modeling capabilities being employed for investigating the urban environment and its linkage to the change in the Earth's climate system. The goal of the session is to identify our current stand and the future direction on the topic. Urbanization is one of the extreme cases of land use change. Most of population of the world has moved to urban areas. By 1995, more than 70% of population of North America and Europe were living in cities. By 2025, the United Nations estimates that 60% of the worlds population will live in cities. Although currently only 1.2% of the land is urban, better understanding of how the atmosphere-ocean-land-biosphere components interact as a coupled system and the influence of human activities on this system is critical. Our understanding of urbanization effect is incomplete, partly because human activities induce new changes on climate in addition to the original natural variations, and partly because previously few data available for study urban effect globally. Urban construction changes surface roughness, albedo, heat capacity and vegetation coverage. Traffic and industry increase atmospheric aerosol. It is suggested that urbanization may modify rainfall processes through aerosol-cloud interactions or dynamic feedbacks. Because urbanization effect on climate is determined by many factors including land cover, the city's microscale features, population density, and human lifestyle patterns, it is necessary to study urban areas over globe.

Shepherd, J. Marshall↗
DOE OSTI2023

Population Aging and Heat Exposure in the 21st Century: Which U.S. Regions Are at Greatest Risk and Why?

Abstract Background and Objectives The co-occurring trends of population aging and climate change mean that rising numbers of U.S. older adults are at risk of intensifying heat exposure. We estimate county-level variations in older populations’ heat exposure in the early (1995–2014) and mid (2050) 21st century. We identify the extent to which rising exposures are attributable to climate change versus population aging. Research Design and Methods We estimate older adults’ heat exposure in 3,109 counties in the 48 contiguous U.S. states. Analyses use NASA NEX Global Daily Downscaled Product (NEX-GDDP-CMIP6) climate data and county-level projections for the size and distribution of the U.S. age 69+ population. Results Population aging and rising temperatures are documented throughout the United States, with particular “hotspots” in the Deep South, Florida, and parts of the rural Midwest. Increases in heat exposure by 2050 will be especially steep in historically colder regions with large older populations in New England, the upper Midwest, and rural Mountain regions. Rising temperatures are driving exposure in historically colder regions, whereas population aging is driving exposure in historically warm southern regions. Discussion and Implications Interventions to address the impacts of temperature extremes on older adult well-being should consider the geographic distribution and drivers of this exposure. In historically cooler areas where climate change is driving exposures, investments in warning systems may be productive, whereas investments in health care and social services infrastructures are essential in historically hot regions where exposures are driven by population aging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Robust and optimal alignment of high-dimensional data using maximum likelihood estimation through a random sample consensus framework

Abstract Correcting spatial orientations of groups of high-dimensional data sets such that they are all in a consistent coordinate system is often a time-consuming and error-prone process. Automation of this process can be accomplished by using Generalized Procrustes Analysis to estimate the relative orientations among a population of high-dimensional data sets. A least squares Procrustes solution is applied through a maximum likelihood estimation and random sample consensus framework for robustness. The likelihood model is comprised of a mixture distribution where inliers are modeled using t -distribution and outliers from a uniform distribution. Applications will focus on a synthetic data set that emulates triaxial acceleration data and also real shock data from a population of triaxial accelerometers. Outliers represent either non-rigid body responses, environmental noise, and/or sensor and data acquisition issues. The intended application for the methodology is to robustly automate the rotation of populations of experimentally collected triaxial accelerometer data sets to a single global coordinate system.

LOSAC↗
NASA NTRS2014

The Spitzer Survey of Interstellar Clouds in the Gould Belt. VI. The Auriga-California Molecular Cloud Observed with IRAC and MIPS

We present observations of the Auriga-California Molecular Cloud (AMC) at 3.6, 4.5, 5.8, 8.0, 24, 70 and 160 micrometers observed with the IRAC and MIPS detectors as part of the Spitzer Gould Belt Legacy Survey. The total mapped areas are 2.5 deg(exp 2) with IRAC and 10.47 deg2 with MIPS. This giant molecular cloud is one of two in the nearby Gould Belt of star-forming regions, the other being the Orion A Molecular Cloud (OMC). We compare source counts, colors and magnitudes in our observed region to a subset of the SWIRE data that was processed through our pipeline. Using color-magnitude and color-color diagrams, we find evidence for a substantial population of 166 young stellar objects (YSOs) in the cloud, many of which were previously unknown. Most of this population is concentrated around the LkH(alpha) 101 cluster and the filament extending from it. We present a quantitative description of the degree of clustering and discuss the fraction of YSOs in the region with disks relative to an estimate of the diskless YSO population. Although the AMC is similar in mass, size and distance to the OMC, it is forming about 15 - 20 times fewer stars.

Orion A Molecular Cloud (OMC)↗
DOE OSTI2022

A Method for Measuring Coupled Individual and Social Vulnerability to Environmental Hazards

Although models of social vulnerability to environmental hazards are commonly developed to support policy interventions in emergencies and disasters, their utility is hindered by a lack of contextual information on individuals exposed to and affected by hazards. We develop a novel approach to model social vulnerability that couples individuals and their varying forms of protective capacity with the social fabric of the communities in which they reside. The backbone of our model is the Public-Use Microdata Sample (PUMS), a product of the U.S. Census Bureau that preserves a representative sample of completed responses to the American Community Survey (ACS). The PUMS enables us to understand the full range of individual protective capacities against a hazard in an exposed area, which we term individual vulnerability profiles (IVPs). In this case, we examine IVPs in the Coney Island-Brighton Beach section of New York City, which suffered severe impacts during Hurricane Sandy in 2012. To manage the large number of unique IVPs in Coney Island-Brighton Beach, we perform a segmentation analysis to generalize them into thematic cohort vulnerability profiles (CVPs) representing a typology of vulnerable people in Coney Island-Brighton Beach during Sandy. From synthetic populations of CVPs, we then estimate how individuals in varying housing types were coexposed to Sandy at the census tract level by classifying these areas into community social vulnerability profiles (SVPs). Our results provide a topology of social vulnerability that simultaneously links individual, community, and population-wide concerns, enabling a more holistic understanding of resources and interventions beneficial to human security during events like Sandy than is attainable with area-level metrics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Estimating the Benefits of Sustainable Aviation Fuel Usage at Chicago O’Hare International Airport on Ultrafine Particle Exposure and Mortalities Reductions

The expanding commercial aviation sector necessitates diverse energy sources, and sustainable aviation fuels (SAFs) have emerged as a promising option. Widespread SAF adoption can help meet transportation fuel demand and offer health benefits for people residing near airports or along airport landing and takeoff (LTO) pathways, where elevated levels of aircraft-derived air pollution often exist. Blending SAF with traditional jet fuels can reduce ultrafine particle (UFP) emissions, which may improve health of near airport population. We analyzed a population of about 8 million people in 1925 census tracts around the Chicago O’Hare International Airport (ORD). We conducted a risk assessment to estimate anticipated UFP reductions for three adoption scenarios using blends of traditional jet fuels with 5, 25, and 50% SAF across all flights landing and taking off from ORD. We calculated baseline estimates of UFP emissions using ORD flight data, a dispersion model, and a calibration function derived from mobile monitoring data. We used this baseline UFP emission profile across the study area to estimate population-weighted UFP, as well as the attributable case reductions (ACRs) and attributable mortality rate reductions (AMRRs) across the demographic distribution around the airport, based on the SAF blending scenarios. We found a positive association of SAF blending with UFP reductions, particularly near the airport and along LTO flight pathways. Our study showed that the population-weighted UFP across different demographics was similar. ACRs were largely dependent on individual demographic populations, while AMRRs for all populations were relatively similar, with an estimated 0.3 (95% range: 0.2−0.3), 1.1 (0.9−1.4), and 1.8 (1.5−2.2) fewer mortalities per 100,000 people per year expected with the adoption of 5, 25, and 50% SAF blends, respectively. This study indicates that communities near ORD, across a range of demographics, may benefit similarly from SAF adoption, thus highlighting how SAF adoption may offer an opportunity to improve health outcomes like aviation UFP-related mortalities around airports.

10 SYNTHETIC FUELS↗
DOE OSTI2023

Survival, healing, and swim performance of juvenile migratory sea lamprey ( Petromyzon marinus ) implanted with a new acoustic microtransmitter designed for small eel-like fishes

Background: Little is known about the transformer stage of the parasitic lampreys, a brief but critical period that encompasses juvenile out-migration from rivers to lakes or oceans to begin parasitic feeding. Information about this life stage could have significant conservation implications for both imperiled and invasive lampreys. We investigated tag retention, survival, wound healing, and swim performance of newly transformed sea lamprey (Petromyzon marinus) implanted with a new micro-acoustic transmitter, the eel–lamprey acoustic transmitter (ELAT), in a controlled laboratory environment. Results: The 61-day survival of our tagged subjects was 71%, within the range reported in similar studies of juvenile lampreys. However, survival was significantly lower in the tagged animals (vs control), with no effect statistically attributable to measures of animal length, mass, condition, or population of origin (Great Lakes vs. Atlantic drainage). Mortality in tagged fish was concentrated in the first four days post-surgery, suggesting injury from the surgical process. An unusually long recovery time from anesthesia may have contributed to the increased mortality. In a simple burst swim assay, tagged animals swam significantly slower (– 22.5%) than untagged animals, but were not significantly different in endurance swim tests. A composite wound healing score at day four was a significant predictor of maximum burst swim speed at day 20, and wound condition was related to animal mass, but not length, at the time of tagging. Conclusions: Impairments to survival and swim performance of juvenile sea lamprey implanted with the ELAT transmitter were within currently reported ranges for telemetry studies with small, difficult to observe fishes. Our results could be improved with more refined anesthesia and surgical techniques. The ability to track migratory movements of imperiled and pest populations of parasitic lampreys will improve our ability to estimate vital rates that underlie recruitment to the adult population (growth, survival) and to investigate the environmental factors that regulate the timing and rates of movement, in wild populations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Probing cosmic velocities with the pairwise kinematic Sunyaev-Zel’dovich signal in DESI Bright Galaxy Sample DR1 and ACT DR6

We present a measurement of the pairwise kinematic Sunyaev-Zel’dovich (kSZ) signal using the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Sample (BGS) Data Release 1 (DR1) galaxy sample overlapping with the Atacama Cosmology Telescope (ACT) CMB temperature map. Our analysis makes use of 1.6 million galaxies with stellar masses log⁡ 𝑀 ⋆ /𝑀 ⊙ >10, and we explore measurements across a range of aperture sizes (2.1′ <𝜃 ap <3.5′) and stellar mass selections. This statistic directly probes the velocity field of the large-scale structure, a unique observable of cosmic dynamics and modified gravity. In particular, at low redshifts, this quantity is especially interesting, as deviations from General Relativity are expected to be largest. Notably, our result represents the highest-significance low-redshift (𝑧 ∼ 0.3) detection of the kSZ pairwise effect yet. In our most optimal configuration (𝜃 ap =3.3′, log⁡ 𝑀 ⋆ >11), we achieve a 5⁢𝜎 detection. Assuming that an estimate of the optical depth and galaxy bias of the sample exists via e.g., external observables, this measurement constrains the fundamental cosmological combination 𝐻 0 ⁡𝑓⁡𝜎$^2_8$. A key challenge is the degeneracy with the galaxy optical depth. We address this by combining CMB lensing, which allows us to infer the halo mass and galaxy population properties, with hydrodynamical simulation estimates of the mean optical depth, $\bar{𝜏}$ . We stress that this is a proof-of-concept analysis; with BGS DR2 data we expect to improve the statistical precision by roughly a factor of two, paving the way toward robust tests of modified gravity with kSZ-informed velocity-field measurements at low redshift.

Hadzhiyska, Boryana [Institute of Astronomy; Kavli↗
NASA NTRS1985

The Timing of Noise-Sensitive Activities in Residential Areas

Data from a nationally representative survey of time use was analyzed to provide estimates of the percentage of the population which is engaged in noise sensitive activities during each hour of the day on weekdays, Fridays, Saturdays and Sundays. Estimates are provided of the percentage engaged in aural communication activities at home, sleeping at home, or simply at home. The day can be roughly divided into four noise sensitivity periods consisting of two relatively steady state periods, night and day and the early morning and evening transition periods. Weekends differ from weekdays in that the morning transition period is one hour later and the numbers of people engaged in aural communication during the day at home are approximately one-half to three-quarters greater. The extent and timing of noise sensitive activities was found to be similiar for all parts of the United States, for different sizes of urban areas, and for the three seasons surveyed (September through May). The timing of activity periods does not differ greatly by sex or age even though women and people over 65 are much more likely to be at home during the daytime.

Fields, J. M.↗
DOE OSTI2022

Inferring subhalo effective density slopes from strong lensing observations with neural likelihood-ratio estimation

ABSTRACT Strong gravitational lensing has emerged as a promising approach for probing dark matter (DM) models on sub-galactic scales. Recent work has proposed the subhalo effective density slope as a more reliable observable than the commonly used subhalo mass function. The subhalo effective density slope is a measurement independent of assumptions about the underlying density profile and can be inferred for individual subhaloes through traditional sampling methods. To go beyond individual subhalo measurements, we leverage recent advances in machine learning and introduce a neural likelihood-ratio estimator to infer an effective density slope for populations of subhaloes. We demonstrate that our method is capable of harnessing the statistical power of multiple subhaloes (within and across multiple images) to distinguish between characteristics of different subhalo populations. The computational efficiency warranted by the neural likelihood-ratio estimator over traditional sampling enables statistical studies of DM perturbers and is particularly useful as we expect an influx of strong lensing systems from upcoming surveys.

Astronomy & Astrophysics↗