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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Development and assessment of a model predictive controller enabling anticipatory control strategies for a heat-pipe system

To support the reliable and resilient operation of modular reactors and microreactors, anticipatory control strategies have been proposed for achieving faster-than-real-time predictions and decision-making capabilities in anticipation of potential anomalies, including setpoint changes and cyber incidents. Here this work presents how anticipatory control strategies can be implemented via model predictive control (MPC) of a single heat pipe’s temperature. Considering the uncertainty in developing and applying MPC, this work evaluates MPC performance given three different model forms: a linear response surface model, an artificial neural network (ANN), and an autoregressive model with exogenous input (ARX). This work also evaluates the impacts of different input biases and variance on MPC performance in order to account for potential sensor reading variations due to cyber incidents. We observe that nonparametric models such as the ANN and ARX result in more fluctuated control actions compared to the MPC applied to the linear response surface model. However, when the cyber incidents are of a large magnitude, the linear response surface model produces smaller feasible regions than the nonparametric models under identical constraints.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

A 5 per cent measurement of the Hubble–Lemaître constant from Type II supernovae

ABSTRACT The most stringent local measurement of the Hubble–Lemaître constant from Cepheid-calibrated Type Ia supernovae (SNe Ia) differs from the value inferred via the cosmic microwave background radiation (Planck+ΛCDM) by ∼5σ. This so-called Hubble tension has been confirmed by other independent methods, and thus does not appear to be a possible consequence of systematic errors. Here, we continue upon our prior work of using Type II supernovae to provide another, largely independent method to measure the Hubble–Lemaître constant. From 13 SNe II with geometric, Cepheid, or tip of the red giant branch (TRGB) host-galaxy distance measurements, we derive H$_0= 75.4^{+3.8}_{-3.7}$ km s−1 Mpc−1 (statistical errors only), consistent with the local measurement but in disagreement by ∼2.0σ with the Planck+ΛCDM value. Using only Cepheids (N = 7), we find H$_0 = 77.6^{+5.2}_{-4.8}$ km s−1 Mpc−1, while using only TRGB (N = 5), we derive H$_0 = 73.1^{+5.7}_{-5.3}$ km s−1 Mpc−1. Via 13 variants of our data set, we derive a systematic uncertainty estimate of 1.5 km s−1 Mpc−1. The median value derived from these variants differs by just 0.3 km s−1 Mpc−1 from that produced by our fiducial model. Because we only replace SNe Ia with SNe II – and we do not find statistically significant difference between the Cepheid and TRGB H0 measurements – our work reveals no indication that SNe Ia or Cepheids could be the sources of the ‘H0 tension.’ We caution, however, that our conclusions rest upon a modest calibrator sample; as this sample grows in the future, our results should be verified.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Implementation of a Model Predictive Control Strategy to Regulate Temperature Inside Plug-Flow Solar Reactor With Countercurrent Flow

Abstract Solar-driven thermochemical energy storage systems are proven to be promising energy carriers (solar fuels) to utilize solar energy by using reactive solid-state pellets. However, the production of solar fuel requires a quasi-steady-state process temperature, which represents the main challenge due to the transient nature of solar power. In this work, an adaptive model predictive controller (MPC) is presented to regulate the temperature inside a tubular solar reactor to produce solid-state solar fuel for long-term thermal storage systems. The solar reactor system consists of a vertical tube heated circumferentially over a segment of its length by concentrated solar power, and the reactive pellets (MgMn2O4) are fed from the top end and flow downwards through the heated tube. A countercurrent flowing gas supplied from the lower end interacts with flowing pellets to reduce it thermochemically at a temperature range of 1000—1500 °C. A low-order physical model was developed to simulate the dynamics of the solar reactor including the reaction kinetics, and the proposed model was validated numerically by using a 7-kW electric furnace. The numerical model then was utilized to design the MPC controller, where the control system consists of an MPC code linked to an adaptive system identification code that updates system parameters online to ensure system robustness against external disturbances (sudden change in the flow inside the reactor), model mismatches, and uncertainty. The MPC controller parameters are tuned to enhance the system performance with minimum steady-state error and overshoot. The controller is tested to track different temperature ranges between 500 °C and 1400 °C with different particles/gas mass flowrates and ramping temperature profiles. Results show that the MPC controller successfully regulated the reactor temperature within ± 1 °C of its setpoint and maintained robust performance with minimum input effort when subjected to sudden changes in the amount of flowing media and the presence of chemical reaction.

Engineering↗
DOE OSTI2021

Comparative analysis of model-free and model-based HVAC control for residential demand response

In this paper, we present a comparative analysis of model-free reinforcement learning (RL) and model predictive control (MPC) approaches for intelligent control of heating, ventilation, and air-conditioning (HVAC). Deep-Q-network (DQN) is used as a candidate for model-free RL algorithm. The two control strategies were developed for residential demand-response (DR) HVAC system. We considered MPC as our golden standard to compare DQN's performance. The question we tried to answer through this work was, What % of MPC's performance can be achieved by model-free RL approach for intelligent HVAC control?. Based on our test result, RL achieved an average of ≈ 62% daily cost saving of MPC. Considering the pure optimization and model-based nature of MPC methods, the RL showed very promising performance. We believe that the interpretations derived from this comparative analysis provide useful insights to choose from various DR approaches and further enhance the performance of the RL-based methods for building energy managements.

Kurte, Kuldeep↗
DOE OSTI2023

Hierarchical multi-time-scale predictive thermal management and fuel optimization for heavy-duty compression ignition engines

For heavy-duty diesel engines, NO X emissions reduction is strongly constrained by fuel efficiency. This paper presents a hierarchical model predictive controller (H-MPC) for coordinated control of tailpipe NO X emissions and fuel consumption. The H-MPC uses the separation of slow and fast dynamics that exist in the engine and its aftertreatment system. The controller is synthesized with an architecture in which a high-level MPC uses a longer prediction horizon compared to the low-level predictive controller which tracks the high-level controller command and manages the thermal dynamics of the aftertreatment system. Engine load preview enables the high-level controller to estimate the desired catalyst temperature ahead of time and addresses the selective catalytic reduction (SCR) slow thermal dynamics. Calculated by the high-level controller, the intake manifold pressure, and the start of injection (SOI) crank angle is used as reference trajectories in the low-level controller that regulates fast dynamical behaviors such as engine out NO X emissions. Hardware-in-the-loop (HIL) validation of this integrated H-MPC on a rapid prototype controller shows that when the SCR catalyst temperature is above light-off temperature (warmed-up condition), the engine operation is shifted to operate with the best fuel economy since the warmed-up SCR can efficiently reduce the engine-out NO X emissions. Results indicate that up to 0.8% benefit in cycle averaged BSFC along with a 13% reduction in tailpipe NO X compared to a stock engine calibration can be achieved with the coordinated engine and aftertreatment system through H-MPC.

Engineering↗
DOE OSTI2024

Remaining Life Prediction of SNF Storage Canisters Exposed to CISCC Environments

• DOE Standardized SNF Storage Canisters o DOE designed standard spent nuclear fuel (SNF) storage canisters for storage of DOE SNF. o DOE canisters are significantly different from commercial MultiPurpose Canisters (MPC) in size. o MPC canisters are large, a height = 15.8 ft, OD = 68”, WT = 0.5”. o DOE canisters are small with 18” / 24” diameter, 10’ / 15’ length. • Integrity Evaluation of DOE versus MPC Canisters o Many investigations have been performed for MPC canisters. o Limit investigations were performed for DOE standard canisters. Most were done at Idaho National Lab (INL). o DOE has sponsored integrity studies to evaluate weld integrity using drop tests and FEA simulations. o No evaluation on CISCC/service life of DOE canister in literature. o MPC canister: 4 axial welds, 1 center girth weld, 2 closing welds.

ZHU, Xiankui↗
DOE OSTI2022

Model predictive control for robust quantum state preparation

A critical engineering challenge in quantum technology is the accurate control of quantum dynamics. Model-based methods for optimal control have been shown to be highly effective when theory and experiment closely match. Consequently, realizing high-fidelity quantum processes with model-based control requires careful device characterization. In quantum processors based on cold atoms, the Hamiltonian can be well-characterized. For superconducting qubits operating at milli-Kelvin temperatures, the Hamiltonian is not as well-characterized. Unaccounted for physics (i.e., mode discrepancy), coherent disturbances, and increased noise compromise traditional model-based control. This work introduces model predictive control (MPC) for quantum control applications. MPC is a closed-loop optimization framework that (i) inherits a natural degree of disturbance rejection by incorporating measurement feedback, (ii) utilizes finite-horizon model-based optimizations to control complex multi-input, multi-output dynamical systems under state and input constraints, and (iii) is flexible enough to develop synergistically alongside other modern control strategies. We show how MPC can be used to generate practical optimized control sequences in representative examples of quantum state preparation. Specifically, we demonstrate for a qubit, a weakly-anharmonic qubit, and a system undergoing crosstalk, that MPC can realize successful model-based control even when the model is inadequate. These examples showcase why MPC is an important addition to the quantum engineering control suite.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Galaxy Alignments with Surrounding Structure in the Sloan Digital Sky Survey

Using data from the Sloan Digital Sky Survey Legacy Survey, we study the alignment of luminous galaxies with spectroscopic data with the surrounding larger-scale structure as defined by galaxies with only photometric data. We find that galaxies from the red sequence have a statistically significant tendency for their apparent long axes to align parallel to the projected surrounding structure. Red galaxies more luminous than the median of our sample (M r < –21.78) have a mean alignment angle $\langle$Φ$\rangle$ < 45°, indicating preferred parallel alignment, at a significance level >4.5σ on projected scales 0.1 Mpc < r p ≤ 7.5 Mpc. Fainter red galaxies have $\langle$Φ$\rangle$ < 45° at a significance level >4.3σ at scales 1 Mpc < r p < 3 Mpc. At a projected scale r p = 3.0 Mpc, the mean alignment angle decreases steadily with increasing luminosity for red galaxies with M r ≲ –22.5, reaching $\langle$Φ$\rangle$ = 40$^{°}_{.}$49 ± 0$^{°}_{.}$56 for the most luminous 1% (M r ~ –23.57). Galaxies from the blue sequence show no statistically significant tendency for their axes to align with larger-scale structure, regardless of galaxy luminosity. Galaxies in higher-density regions do not show a statistically significant difference in the mean alignment angle from galaxies in lower-density regions; this holds true for the faint blue, luminous blue, faint red, and luminous red subsets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Model Predictive Control for a Grid-interactive Efficient Thermal Storage-integrated Heat Pump System

Building heating and cooling systems can be used to overcome the mismatch between the intermittent supply of renewable power and the fluctuating demand for electricity. A novel underground thermal energy storage integrated with a dual-source heat pump has been proposed to mitigate the mismatch while meeting the thermal demand of buildings efficiently. Conventional thermostat control with heuristic rules cannot provide intelligent decisions to maximize the thermal efficiency and flexibility of the proposed system. Advanced control strategies like model predictive control (MPC) have provided a new paradigm for grid-interactive efficient building operation with the advancement of computation and sensing. This study developed an MPC for the proposed system to provide grid service for Demand Side Management and minimize the operating cost of building owners. A control-oriented dynamic model of the proposed system has been developed. Given an objective function and proper constraints, an optimization problem is formulated to determine the optimal control strategy of the system. Dynamic Programming is adopted to solve the optimization problem. A rule-based control (RBC) is also developed to achieve similar goals. Short-term simulations are conducted to compare the system performance resulting from the two controls. The simulation results indicate that the MPC performs more intelligently than the RBC in charging thermal energy storage and selecting heat pump sources by taking advantage of the predicted cooling demands of the building and the performance of the integrated system. As a result, the MPC could save energy and reduce operating costs compared with the RBC. A case study shows that, for a 3-day operation, the MPC saves 36.9% energy and reduces 38.5% operating cost compared with the RBC.

Shi, Liang↗
DOE OSTI2024

Decarbonization of heat pump dual fuel systems using a practical model predictive control: Field demonstration in a small commercial building

In the transition from fossil fuel to electrified heating, a concerning trend is emerging in certain regions of the US. Owners of buildings with gas-based systems leave them in place after adding heat pumps (HPs). Existing control solutions for these hybrid (dual fuel) systems are rudimentary and fall short of realizing the full carbon reduction potential of these systems. Model predictive control (MPC) is often regarded as the benchmark for achieving optimal control in integrated systems. However, in the case of small-medium commercial buildings (SMCBs), the control and communication infrastructure required to facilitate the implementation of such advanced controls is often lacking. This paper presents a field implementation of easy-to-deploy MPC for a dual fuel heating system consisting of HPs and a gas-fired furnace (GF) for SMCBs. The control system is deployed on an open-source middleware platform and utilizes low-cost sensor devices to be used for real SMCBs without major retrofits. Here, we demonstrated this MPC in a real office building with 5 HPs and 1 GF for 2 months. The test results showed that MPC reduced 27% of cost while completely eliminating GF usage by shifting 23% of the thermal load from occupied-peak time to non-occupied-non-peak times.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A Generic Two-Vector Model Predictive Control for Hybrid Multilevel Converters

In this article, a generic two-vector model predictive control (TV-MPC) strategy is proposed for the hybrid multilevel converters (HMCs). The proposed method selects two optimal voltage vectors among all the vector candidates using a geometric positioning approach to reduce the computational burden, which is a common issue in the existing MPC methods for HMC. Then duty cycles of the two selected vectors are optimized to minimize the current tracking error, such that the current tracking performance can be enhanced compared with the conventional MPC. In addition, the voltages of the floating dc capacitors can be balanced by evaluating all switching sequences that belong to the optimal voltage vectors with optimal duty cycles. Here, the concept of the proposed TV-MPC is generic and applicable for any HMCs. A typical HMC based on active neutral-point-clamped topology is adopted as a case study in this work. Comprehensive simulation and experimental studies are performed on an all silicon-carbide HMC prototype to validate the effectiveness of the proposed control scheme.

42 ENGINEERING↗
DOE OSTI2026

The Influence of Mesoscale Particle Structure on the Electrode Degradation and Resultant Electrochemistry of Lithium Ion Cells With Nickel Rich Lithium Nickel Manganese Cobalt Oxide Positive Electrodes

Nickel-rich lithium nickel manganese cobalt oxide, NMC (LiNi x Mn y Co z O 2 ), materials are desirable positive electrodes in lithium ion batteries, providing high capacity and energy density. The mesoscale structure of NMC materials is commonly a polycrystalline aggregate, providing opportunity for short lithium ion transport distance of the small primary particles, yet facile material handling due to the larger secondary particles. On (de)lithiation the NMC unit cell changes volume, where the anisotropic strain can result in secondary particle fracture. This secondary particle fracture process during cycling has been associated with several degradation modes of NMC materials in LIBs. In this work, a milling process was determined whereby the secondary particles could be pre-fractured with retention of the parent primary particle crystallographic structure, crystallite size, and morphology, providing the ability to unambiguously determine the influence of NMC secondary particle size and mesostructure on resultant functional behavior. The bulk and interfacial properties and electrochemistry of as-received commercially obtained polycrystal NMC811 (LiNi 0.8 Mn 0.1 Co 0.1 O 2 , PC NMC) and its milled MPC NMC counterpart were compared. The smaller secondary particle size, higher surface area MPC NMC was found to result in 1) greater cathode tortuosity, 2) reduced surface Ni on the cycled MPC cathodes consistent with surface reconstruction, and 3) increased Ni deposition on the anodes from cathode-anode crosstalk. These factors manifested in unfavorable electrochemical behavior of MPC with lower functional capacity at both 1C and C/10 rates and higher impedance over extended moderate voltage (dis)charge cycling.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Model predictive control of mixing controlled compression ignition operation for low reactivity fuels

Using gasoline or other low reactivity fuels with a pilot injection or port fuel injection in a compression ignition engine has shown great potential in reducing NOx emissions while keeping high thermal efficiency compared to diesel. However, excessive combustion noise is caused by a high maximum pressure rise rate in the cylinder due to the higher fractions of premixed charge of the low-reactivity fuel. This noise can result in structural damage to engine components and as such, combustion noise limits the range of the operating parameters and makes the control of such engines challenging. In this study, a simulation environment was built up in MATLAB/Simulink leveraging a physics-based zero-dimension combustion model to capture the in-cylinder pressure time traces as well as metrics relevant to thermal efficiency and combustion noise. Here, in order to also facilitate the control of emissions, machine learning models were investigated to capture NOx emissions. A kernel-based extreme learning machine (K-ELM) performed best and had a coefficient of correlation (R-squared) of 0.998. The combustion and NOx emission models are valid for not only conventional gasoline fuel but also oxygenated alternative fuel blends at three different pilot injection strategies. In order to track key combustion metrics while keeping noise and emissions within constraints, a model predictive control (MPC) was applied for a compression ignition engine operating with a range of potential fuels and fuel injection strategies. The MPC is validated under different scenarios, including a load step change, fuel type change, and injection strategy change, with proportional–integral (PI) control as the baseline. The simulation results show that MPC reduces about 26% of ringing intensity in the transient process and 17% at the steady state for E30. Generally, MPC can optimize the overall performance through modifying the main injection timing, pilot fuel mass, and exhaust gas recirculation (EGR) fraction.

42 ENGINEERING↗
DOE OSTI2024

Influence of zwitterionic amphiphilic copolymers on heterogeneous gypsum formation: A promising approach for scaling resistance

Here, this study aims to investigate the influence of zwitterionic amphiphilic copolymers (ZACs) in the nucleation and growth of heterogeneous CaSO4 at the zwitterion-water interface, which is crucial for the prevention of mineral scaling and consequent downtime or suboptimal performance in industries like membrane desalination, heat exchangers, and pipeline transportation. In situ grazing incidence small angle X-ray Scattering (GISAXS), and quartz crystal microbalance with dissipation (QCM-D) techniques were used to analyze the evolution of CaSO 4 particles on two new ZAC coatings: poly-(trifluoroethyl methacrylate-random-sulfobetaine methacrylate) (PTFEMA-r-SBMA, or PT:SBMA) and poly(trifluoroethyl methacrylate-random-2-methacryloyloxyethyl phosphorylcholine) (PTFEMA-r-MPC, or PT:MPC). The results showed that PT:MPC coatings promoted nucleation but inhibited crystal growth, resulting in slower overall reaction kinetics on PT:MPC coatings compared to PT:SBMA coatings. Interfacial interactions involving the substrates, sulfate minerals, and ions were examined, revealing that calcium ion adsorption, primarily governed by electrostatic attraction, played a crucial role in the nucleation and growth processes on both ZAC coatings. The crystal characterization revealed a phase transition from bassanite to gypsum on both ZAC coatings, suggesting that these zwitterionic materials can influence the mineral phase of heterogeneously formed CaSO 4 crystals. These findings enhance our understanding of the fundamental mechanisms underlying heterogeneous CaSO 4 scaling in the presence of zwitterionic materials.

42 ENGINEERING↗
DOE OSTI2023

Investigating the large-scale environment of wide-angle tailed radio galaxies in the local Universe

We present a statistical analysis of the large-scale (up to two Mpc) environment of a homogeneous and complete sample, both in radio and optical selection, of wide-angle tailed radio galaxies (WATs) in the local Universe (i.e., with redshifts z ≲ 0.15). The analysis is carried out using the parameters obtained from cosmological neighbors within two Mpc of the target source. Results regarding the large-scale environments of the WATs are then compared with those of Fanaroff–Riley type I (FR Is) and type II (FR IIs) radio galaxies listed in two other homogeneous and complete catalogs and selected with the same criterion adopted for the WATs catalog. We obtain indication that at low redshift, WATs inhabit environments with a larger number of galaxies than those of FR Is and FR IIs. In the explored redshift range, the physical size of the galaxy group or cluster in which the WATs reside appears to be almost constant with respect to FR Is and FR IIs, being around one Mpc. From the distribution of the concentration parameter, defined as the ratio between the number of cosmological neighbors lying within 500 kpc and within one Mpc, we conclude that WATs tend to inhabit the central region of the group or cluster in which they reside, in agreement with the general paradigm that WATs are the brightest cluster or group galaxy.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

The DESI One-Percent Survey: Modelling the clustering and halo occupation of all four DESI tracers with U CHUU

We present results from a set of mock lightcones for the DESI One-Percent Survey, created from the UCHUU simulation. This 8 h −3 Gpc 3 N-body simulation comprises 2.1 trillion particles and provides high-resolution dark matter (sub)haloes in the framework of the Planck-based ΛCDM cosmology. Employing the subhalo abundance matching (SHAM) technique, we populated the UCHUU (sub)haloes with all four DESI tracers – Bright Galaxy Survey (BGS), luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars (QSOs) – to z = 2.1. Our method accounts for redshift evolution as well as the clustering dependence on luminosity and stellar mass. The two-point clustering statistics of the DESI One-Percent Survey generally agree with predictions from UCHUU across scales ranging from 0.3 h −1 Mpc to 100 h −1 Mpc for the BGS and across scales ranging from 5 h −1 Mpc to 100 h −1 Mpc for the other tracers. We observed some differences in clustering statistics that can be attributed to incompleteness of the massive end of the stellar mass function of LRGs, our use of a simplified galaxy-halo connection model for ELGs and QSOs, and cosmic variance. We find that at the high precision of UCHUU, the shape of the halo occupation distribution (HOD) of the BGS and LRG samples is smaller bias values, likely due to cosmic variance. The bias dependence on absolute magnitude, stellar mass, and redshift aligns with that of previous surveys. These results provide DESI with tools to generate high-fidelity lightcones for the remainder of the survey and enhance our understanding of the galaxy-halo connection.

cosmology↗
DOE OSTI2024

Hybrid model predictive control techniques for safety factor profile and stored energy regulation while incorporating NBI constraints

Abstract A novel hybrid Model Predictive Control (MPC) algorithm has been designed for simultaneous safety factor ( q ) profile and stored energy ( w ) control while incorporating the pulse-width-modulation constraints associated with the neutral beam injection (NBI) system. Regulation of the q -profile has been extensively shown to be a key factor for improved confinement as well as non-inductive sustainment of the plasma current. Simultaneous control of w is necessary to prevent the triggering of pressure-driven magnetohydrodynamic instabilities as the controller shapes the q profile. Conventional MPC schemes proposed for q -profile control have considered the NBI powers as continuous-time signals, ignoring the discrete-time nature of these actuators and leading in some cases to performance loss. The hybrid MPC scheme in this work has the capability of incorporating the discrete-time actuator dynamics as additional constraints. In nonlinear simulations, the proposed hybrid MPC scheme demonstrates improved q -profile+ w control performance for NSTX-U operating scenarios.

Physics↗
DOE OSTI2021

Galaxy–galaxy lensing with the DES-CMASS catalogue: measurement and constraints on the galaxy-matter cross-correlation

ABSTRACT The DMASS sample is a photometric sample from the DES Year 1 data set designed to replicate the properties of the CMASS sample from BOSS, in support of a joint analysis of DES and BOSS beyond the small overlapping area. In this paper, we present the measurement of galaxy–galaxy lensing using the DMASS sample as gravitational lenses in the DES Y1 imaging data. We test a number of potential systematics that can bias the galaxy–galaxy lensing signal, including those from shear estimation, photometric redshifts, and observing conditions. After careful systematic tests, we obtain a highly significant detection of the galaxy–galaxy lensing signal, with total S/N = 25.7. With the measured signal, we assess the feasibility of using DMASS as gravitational lenses equivalent to CMASS, by estimating the galaxy-matter cross-correlation coefficient rcc. By jointly fitting the galaxy–galaxy lensing measurement with the galaxy clustering measurement from CMASS, we obtain $r_{\rm cc}=1.09^{+0.12}_{-0.11}$ for the scale cut of $4 \, h^{-1}{\rm \,\,Mpc}$ and $r_{\rm cc}=1.06^{+0.13}_{-0.12}$ for $12 \, h^{-1}{\rm \,\,Mpc}$ in fixed cosmology. By adding the angular galaxy clustering of DMASS, we obtain rcc = 1.06 ± 0.10 for the scale cut of $4 \, h^{-1}{\rm \,\,Mpc}$ and rcc = 1.03 ± 0.11 for $12 \, h^{-1}{\rm \,\,Mpc}$. The resulting values of rcc indicate that the lensing signal of DMASS is statistically consistent with the one that would have been measured if CMASS had populated the DES region within the given statistical uncertainty. The measurement of galaxy–galaxy lensing presented in this paper will serve as part of the data vector for the forthcoming cosmology analysis in preparation.

79 ASTRONOMY AND ASTROPHYSICS↗