Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “building analytics”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Proton nuclear magnetic resonance (1H NMR) of flammable organic chemicals in radioactive high–level supernatant waste at the Savannah River Site (SRS)

The Savannah River Site stores approximately 36 million gallons of radioactive and hazardous waste that contains approximately 245 million curies. The waste is sent through various chemical processes to reduce its volume and to separate various components. The facility plans to replace formic acid (a chemical used to reduce soluble mercury) with glycolic acid. Recycle solution with glycolate may flow back to the tank farm, where the glycolate can generate hydrogen gas by thermal and radiolytic mechanisms. The current analytical method for detecting glycolate (ion chromatography) in supernatant requires a large dilution to reduce interference from the nitrate anions. Hydrogen nuclear magnetic resonance is an analytical method that requires less sample dilution. It takes advantage of the CH 2 group in glycolate. Liquid samples were spiked with four different levels of glycolate to build a calibration line, as it is recommended in the standard addition method. The detection and quantitation limits determined were 1 and 5 ppm, respectively, for 32 scans, which is well below the process limit of 10 ppm. In one test, 800 scans of a supernatant spiked with 1 ppm glycolate resulted in a -CH 2 peak with a signal-to-noise ratio of 36.

1H↗
DOE OSTI2024

DECOVALEX-2023: Task C Final Report

The Full-scale Emplacement (FE) heater experiment at the Mont Terri Underground Rock Laboratory (URL) was designed and conducted by Nagra to replicate an emplacement tunnel of Nagra’s reference repository design at 1:1 scale. Alongside testing the technical feasibility of constructing disposal tunnels, emplacing waste containers in the tunnels and then backfilling them, the main goals of the FE experiment are (1) to obtain a better understanding of the coupled effects of induced thermo-hydro-mechanical (THM) processes that may occur and (2) to validate existing coupled THM models (Müller et al., 2017). A key aspect of ensuring safety for repositories located in low-permeability rock involves minimizing any damage to the rock itself, thereby preserving its integrity and promoting a stable environment Amongst a number of processes that could damage the rock is the increase in pore pressure due to thermal loading caused by heat emitted from the waste. To reduce the potential damage of the rock, it is important to analyse the evolution of heat over time due to the heat load of the containers and assess possible consequences by coupled THM models. The aim of Task C of DECOVALEX-2023 was to build 3D numerical models of the FE experiment, focussing in particular on the heating induced pore pressure change in the Opalinus Clay. Data from a large number of sensors were available from the FE experiment for model comparison. These sensors measured temperature and relative humidity in the bentonite around the heaters, and temperature, pressure and displacement/strain in the surrounding Opalinus clay. Data were available from the start of excavation (April 2012) up to August 2020 for most sensors (more than 5 years from the start of heating in December 2014). To fulfil the overall aim of the task, the work was broken down into a number of steps, starting with simpler models to build confidence in each team’s approach and then moving to more complex models that better represent the FE experiment. Step 0 consisted of 2D benchmark models, gradually increasing the number of processes that are represented from thermal (T) only models in Step 0a, to coupled thermal hydraulic (TH) models in Step 0b with a representation of changing porosity, to coupled thermo-hydro-mechanical (THM) models in Step 0c, where porosity changes are calculated by the mechanical model. A detailed specification of processes, parameters, initial and boundary conditions was provided for this step, with the ambition that all teams would work towards close agreement in their model results, thus building confidence in the model implementations. vi It was not straightforward to achieve agreement between the teams, so additional steps (Step 0b2, 0b3, 0c2, 0c3) were added along with derivation of some analytical solutions against which the models could be compared. The reasons for the differences between teams were investigated and found to be caused primarily by different conceptual model assumptions (including temperature dependence of the thermal expansion of water), different model formulations (including porosity evolution) and differences in modelled domain sizes, boundary conditions and grid discretisation. This demonstrates that comparisons between multiple modelling teams and/or comparison with analytical results and experimental data are highly beneficial in providing an indication of uncertainty in model predictions. At the conclusion of Step 0, almost all teams had achieved a close agreement in model results and those that had not achieved an agreement knew the reason for this. Step 1 moved from 2D models to 3D models of the FE experiment without adding technical features like shotcrete or EDZ, and only considering the heating phase. Initially the 3D model was tightly specified to continue to build confidence in the model implementations (Step 1a). The results of Step 1a were compared to the data from the FE-experiment without the teams seeing the data. The teams were then provided with a sub-set of the data from the FE-experiment and invited to consider how best to use the large dataset for model comparison (Step 1b). Teams were then asked to use the data provided to calibrate their models, only changing material property values rather than adding features or processes to their models (Step 1c). In Step 1, teams were asked to only model the heating phase of the experiment, so pressure in the Opalinus Clay was reported as change in pressure since the initial conditions were specified rather than modelled. The change from 2D to 3D models was accompanied by an increase in the dispersion of results between the teams. Some of this was resolved during the task, but some remained and is potentially due to model discretisation. Calibration of parameters was useful in improving the fit of the models to the data but the remaining differences indicated that the models were missing features or processes. In Step 2, the teams were asked to update their models with additional features and processes as well as calibrating parameters to try and improve the fit of the models to the data. Teams were encouraged to represent ventilation of the open FE tunnel prior to backfilling with heaters and bentonite and in Step 2, the absolute pressure in the Opalinus Clay was compared between the teams. Teams took different approaches, but there was consideration of adding shotcrete and an EDZ into the model, representing stress change during excavation and different approaches to modelling ventilation of the FE tunnel. Overall, the documented results showed a very good agreement for temperature. The results for porewater pressure evolution showed a significant improvement for most teams compared to Step 1c with a good agreement to the measurements for several teams whereas some teams overpredicted the pressure increase and others overpredicted the drainage effect especially for the sensors close to the heater. Step 3 was an opportunity for teams to use the models developed in Step 1 and Step 2 to make predictions about the temperature and pressure changes that will be expected at the FE experiment over the next few years in light of the planned changes in thermal output of the heaters.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Selection of site specific vibration equation by using analytic hierarchy process in a quarry

This paper presents a new approach for the selection of the most accurate SSVA (Site Specific Vibration Attenuation) equation for blasting processes in a quarry located near settlements in Istanbul, Turkey. In this context, the SSVA equations obtained from the same study area in the literature were considered in terms of distance between the shot points and buildings and the amount of explosive charge. In this purpose, 11 different SSVA equations obtained from the study area in the past 12 years, forecasting capabilities according to designated new conditions, using 102 vibration records as test data obtained from the study area was investigated. In this study, AHP (Analytic Hierarchy Process) was selected as an analysis method in order to determine the most accurate equation among 11 SSAV equations, and the parameters such as year, distance, charge, and r{sup 2} of the equations were used as criteria for AHP. Finally, the most appropriate equation was selected among the existing ones, and the process of selecting according to different target criteria was presented. Furthermore, it was noted that the forecasting results of the selected equation is more accurate than that formed using the test results. - Highlights: • The optimum Site Specific Vibration Attenuation equation for blasting in a quarry located near settlements was determined. • It is indicated that SSVA equations changing over the years don’t give always accurate estimates at changing conditions. • Selection of the blast induced SSVA equation was made using AHP. • Equation selection method was highlighted based on parameters such as charge, distance, and quarry geometry changes (year).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2007

Build-up Approach to Updating the Mock Quiet Spike(TradeMark) Beam Model

A crucial part of aircraft design is ensuring that the required margin for flutter is satisfied. A trustworthy flutter analysis, which begins by possessing an accurate dynamics model, is necessary for this task. Traditionally, a model was updated manually by fine tuning specific stiffness parameters until the analytical results matched test data. This is a time consuming iterative process. NASA Dryden Flight Research Center has developed a mode matching code to execute this process in a more efficient manner. Recently, this code was implemented in the F-15B/Quiet Spike(TradeMark) (Gulfstream Aerospace Corporation, Savannah, Georgia) model update. A build-up approach requiring several ground vibration test configurations and a series of model updates was implemented in order to determine the connection stiffness between aircraft and test article. The mode matching code successfully updated various models for the F-15B/Quiet Spike(TradeMark) project to within 1 percent error in frequency and the modal assurance criteria values ranged from 88.51-99.42 percent.

Herrera, Claudia Y.↗
NASA NTRS2007

Build-up Approach to Updating the Mock Quiet Spike(TM)Beam Model

A crucial part of aircraft design is ensuring that the required margin for flutter is satisfied. A trustworthy flutter analysis, which begins by possessing an accurate dynamics model, is necessary for this task. Traditionally, a model was updated manually by fine tuning specific stiffness parameters until the analytical results matched test data. This is a time consuming iterative process. The NASA Dryden Flight Research Center has developed a mode matching code to execute this process in a more efficient manner. Recently, this code was implemented in the F-15B/Quiet Spike (Gulfstream Aerospace Corporation, Savannah, Georgia) model update. A build-up approach requiring several ground vibration test configurations and a series of model updates was implemented to determine the connection stiffness between aircraft and test article. The mode matching code successfully updated various models for the F-15B/Quiet Spike project to within 1 percent error in frequency and the modal assurance criteria values ranged from 88.51-99.42 percent.

Herrera, Claudia Y.↗
DOE OSTI2016

Combined multi-analytical approach for study of pore system in bricks: How much porosity is there?

During the firing of bricks, mineralogical and textural transformations produce an artificial aggregate characterised by significant porosity. Particularly as regards pore-size distribution and the interconnection model, porosity is an important parameter to evaluate and predict the durability of bricks. The pore system is in fact the main element, which correlates building materials and their environment (especially in cases of aggressive weathering, e.g., salt crystallisation and freeze-thaw cycles) and determines their durability. Four industrial bricks with differing compositions and firing temperatures were analysed with “direct” and “indirect” techniques, traditional methods (mercury intrusion porosimetry, hydric tests, nitrogen adsorption) and new analytical approaches based on digital image reconstruction of 2D and 3D models (back-scattered electrons and computerised X-ray micro-Tomography, respectively). The comparison of results from different analytical methods in the “overlapping ranges” of porosity and the careful reconstruction of a cumulative curve, allowed overcoming their specific limitations and achieving better knowledge on the pore system of bricks. - Highlights: •Pore-size distribution and structure of the pore system in four commercial bricks •A multi-analytical approach combining “direct” and “indirect” techniques •Traditional methods vs. new approaches based on 2D/3D digital image reconstruction •The use of “overlapping ranges” to overcome the limitations of various techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Qualification of Daiichi Units 1, 2, and 3 Data for Severe Accident Evaluations - Process and Illustrative Examples from Prior TMI-2 Evaluations

The accidents at the Three Mile Island Unit 2 (TMI-2) Pressurized Water Reactor (PWR) and the Daiichi Units 1, 2, and 3 Boiling Water Reactors (BWRs) provide unique opportunities to evaluate instrumentation exposed to severe accident conditions. Conditions associated with the release of coolant and the hydrogen burn that occurred during the TMI-2 accident exposed instrumentation to harsh conditions, including direct radiation, radioactive contamination, and high humidity with elevated temperatures and pressures. As part of a program initiated in 2012 by the Department of Energy Office of Nuclear Energy (DOE-NE), a review was completed to gain insights from prior TMI-2 sensor survivability and data qualification efforts. This initial review focused on the set of sensors deemed most important by post-TMI-2 instrumentation evaluation programs. Instrumentation evaluation programs focused on data required by TMI-2 operators to assess the condition of the reactor and containment and the effect of mitigating actions taken by these operators. In addition, prior efforts focused on sensors providing data required for subsequent forensic evaluations and accident simulations. To encourage the potential for similar activities to be completed for qualifying data from Daiichi Units 1, 2, and 3, this report provides additional details related to the formal process used to develop a qualified TMI-2 data base and presents data qualification details for three parameters: primary system pressure; containment building temperature; and containment pressure. As described within this report, sensor evaluations and data qualification required implementation of various processes, including comparisons with data from other sensors, analytical calculations, laboratory testing, and comparisons with sensors subjected to similar conditions in large-scale integral tests and with sensors that were similar in design to instruments easily removed from the TMI-2 plant for evaluations. As documented in this report, results from qualifying data for these parameters led to key insights related to TMI-2 accident progression. Hence, these selected examples illustrate the types of activities completed in the TMI-2 data qualification process and the importance of such a qualification effort. These details are documented in this report to facilitate implementation of similar process using data and examinations at the Daiichi Units 1, 2, and 3 reactors so that BWR-specific benefits can be obtained.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Development of National New Construction Weighting Factors for the Commercial Building Prototype Analyses (2008-2022)

The U.S. Department of Energy (DOE) tasked Pacific Northwest National Laboratory (PNNL) with updating commercial building construction weights for the purpose of estimating national and state-by-state energy savings impacts of changes made to various commercial energy codes and standards. A similar activity was last completed by PNNL in 2020 using disaggregate construction volume data acquired from the Dodge Data & Analytics database (formerly McGraw Hill) for the years 2003-2018 (Lei et al, 2020). As time passes, changes in economic and social demand reshape construction volume trends. For the current update, PNNL reviewed the same data source with the latest construction data for the years 2008-2022. For commercial building analyses, PNNL typically uses a suite of 16 prototype buildings simulated in the 19 ASHRAE climate zones with 16 of them present in the United States. The 2008-2022 commercial building weighting factors were derived using the same approach employed to develop the 2003-2018 set (Lei et al, 2020). Applying the construction volume data from the database to the prototypes and climate zones resulted in the following new construction area-based weighting factors. Table ES.1 shows the weighting factors including all building categories found in the database, and Table ES.2 shows the weighting factors normalized to include only buildings represented by the 16 prototypes. Section 3.0 also includes national- and state-level weighting factors by area and building count.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Myna: Connecting powder bed fusion build data to simulation tools for digital twin applications

Additive manufacturing (AM), as a digital process, can generate a detailed digital thread linking a part’s design and manufacturing to its operational performance. As AM systems advance, an increasing amount of process data is stored in manufacturing databases. In principle, this data can be utilized by simulation-based digital twin approaches, such as real-time process control and asynchronous post-processing guidance. However, few tools currently exist for systematically integrating digital thread data with computational tools. Here, in this study, we propose a software package, called Myna, for connecting data from powder bed fusion processes to simulation tools. The utility of such a platform is demonstrated using build data from the Oak Ridge National Laboratory Manufacturing Demonstration Facility “Peregrine v2023-10” public dataset to automatically configure and run 54 semi-analytical 3DThesis melt pool simulations, 78 numerical Additive FOAM melt pool simulations, and 3 ExaCA microstructure simulations. The simulated, spatially registered microstructures are then compared directly with electron backscatter diffraction characterization of the corresponding as-built part locations. The resulting simulated microstructure showed variation as a function of process parameters, particularly stripe width; however, the experimental data had little variation between the microstructure texture and grain size resulting from different processing conditions. Analysis of the discrepancies suggest that it is possible a two-phase ferritic-austenitic solidification model is needed to accurately predict grain size and texture for certain stainless steel 316L feedstock compositions under powder bed fusion conditions, providing direction for future research. As illustrated here, due to the number and complexity of the simulations involved in AM process-structure–property predictions, automated methods to connect process data and simulations will remain necessary tools for testing hypotheses and implementing digital twin applications.

Knapp, Gerald L. [Oak Ridge National Laboratory (O↗
DOE OSTI2020

Automated calculation and convergence of defect transport tensors

Defect diffusion is a key process in materials science and catalysis, but as migration mechanisms are often too complex to enumerate a priori, calculation of transport tensors typically have no measure of convergence and require significant end-user intervention. These two bottlenecks prevent high-throughput implementations essential to propagate model-form uncertainty from interatomic interactions to predictive simulations. In order to address these issues, we extend a massively parallel accelerated sampling scheme, autonomously controlled by Bayesian estimators of statewide sampling completeness, to build atomistic kinetic Monte Carlo models on a state-space irreducible under exchange and space group symmetries. Focusing on isolated defects, we derive analytic expressions for drift and diffusion coefficients, providing a convergence metric by calculating the Kullback–Leibler divergence across the ensemble of diffusion processes consistent with the sampling uncertainty. The autonomy and efficacy of the method is demonstrated on surface trimers in tungsten and Hexa-interstitials in magnesium oxide, both of which exhibit complex, correlated migration mechanisms.

36 MATERIALS SCIENCE↗
DOE OSTI2014

Communication: A density functional investigation of structure-property evolution in the tetrakis hexahedral C{sub 4}Al{sub 14} nanocluster

Nanoclusters are prime objects of study in modern nanotechnology and offer a variety of applications promoted by their properties tunable by size, shape, and composition. DFT calculations are employed to analyze structure, stability, and selected electronic properties of a core-shell C{sub 4}Al{sub 14} species. With insertion of the carbon core, the original low-symmetry aluminum cluster is predicted to undergo a considerable reshaping and acquire a striking D{sub 4h} tetrakis-hexahedral geometry, with proportions controlled by a near-degenerate spin state or charge. The system also becomes more stable to dissociation. Surprisingly, other properties such as ionisation energy and electron affinity do not change significantly, although still exhibit some interesting features including opposite variations for vertical and adiabatic values. The stability and property evolutions are analyzed in terms of contributions from reshaping of the shell and its further interaction with the core. The system thus has potential applications as a symmetric building unit and a molecular device for nano-electronics/spintronics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Lorentzian OPE inversion formula: A geometric perspective

We give a new perspective on the Lorentzian operator product expansion inversion formula [S. Caron-Huot, Analyticity in spin in conformal theories, .; D. Simmons-Duffin, D. Stanford, and E. Witten, A spacetime derivation of the Lorentzian OPE inversion formula, .], building on [P. Agarwal , companion paper, Embedding space approach to Lorentzian CFT amplitudes and causal spherical functions, .]. We introduce an “auxiliary” fourpoint function that can be related to the traditionally defined ones via a Radon transform. The Mellin amplitudes associated with this auxiliary function can be shown to be equivalent to the conventional partial wave amplitudes. This has the intuitive geometrical meaning of a generalization of the projection-slice theorem. Published by the American Physical Society 2025

Agarwal, Pulkit (ORCID:0000000346581691)↗
DOE OSTI2024

SNNVis: Visualizing Graph Embedding of Evolutionary Optimization for Spiking Neural Networks

While Spiking Neural Networks (SNNs) show a lot of promise, it is difficult to optimize them because applying traditional gradient-based optimization techniques is difficult. Even though evolutionary algorithms (EAs) have been shown to promise to optimize SNNs, understanding the relationship between evolving the characteristics of SNNs and their performance to improve the optimization algorithm is challenging because of the complex characteristics and huge population size. We propose visual analytics with novel graph embedding for evolutionary SNNs to address the challenges. While existing graph embedding techniques have limitations in preserving the specific features of the nodes and edges, our approach maintains them. Also, we develop visual analytics for understanding the relationship between the network performance and the features of nodes and edges and exploring and analyzing the evolving SNNs to build insights into improving the EA.

Chae, Junghoon [ORNL] (ORCID:0000000206016746)↗
DOE OSTI2018

A Charge Sensitive Pre-Amplifier for Smart Point-of-Care Devices Employing Polymer Based Lab-on-a-Chip

With increasing emphasis on implantable and portable medical devices, low-power, small-chip-area sensor readout system realized in lab-on-a-chip (LOC) platform is gaining more and more importance these days. The main building blocks of the LOC system include a front-end transducer that generates an electrical signal in response to the presence of an analyte of interest, signal processing electronics to process the signal to comply with a specific transmission protocol and a low-power transmitter, all realized in a single integrated circuit platform. Low power consumption and compactness of the components are essential requirements of the LOC system. This paper presents a novel charge sensitive pre-amplifier developed in a standard 180-nm CMOS process suitable for implementing in an LOC platform. The pre-amplifier converts the charge generated by a pyroelectric transducer into a voltage signal, which provides a measurement of the temperature variation in biological fluids. The proposed design is capable of providing 0.8-mV/pC gain while consuming only 2.1 μW of power. Finally, the pre-amplifier composed of integrated components occupies an area of 0.038 mm 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2015

Submittal of SWMU Assessment Report for Building 9960 Surface Discharge

Sandia National Laboratories is a multi-purpose engineering and science laboratory owned by the U.S. Department of Energy (DOE)/National Nuclear Security Administration and managed and operated by Sandia Corporation (Sandia), a wholly-owned subsidiary of Lockheed Martin Corporation. This Solid Waste Management Unit (SWMU) Assessment Report (SAR) for the Sandia National Laboratories, New Mexico (SNL/NM), Coyote Test Field, Building 9960 Surface Discharge, has been prepared in accordance with Section V of the Compliance Order on Consent (the Consent Order) between the New Mexico Environment Department (NMED), DOE, and Sandia (NMED April 2004). The DOE and Sandia formally notified the NMED of this newly identified or suspected SWMU or Area of Concern (AOC) by letter dated December 9, 2014. This SAR is being submitted in accordance with the NMED Hazardous Waste Bureau (HWB) letter dated February 16, 2015 letter (Kieling February 2015). This SAR presents the available information for the Building 9960 Surface Discharge, including location, designation of type and function, a general description, the operational dates, waste characteristics, and a summary of existing analytical wastewater and soil data

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

A Theory of Growing Crystalline Nanorods

Energy harvesting and storage benefit from and depend on the design of nanomaterials such nanorods. Without design, the nanorods can take numerous configurations that correspond to local minima of energy. Focusing on the science of nanorod growth, the PI has developed a theoretical framework of nanorod growth, and designed and experimentally grown small and well-separated nanorods using physical vapor deposition. Building on the framework, this project in the next three years will focus on: (1) Identifying atomic mechanisms of step bunching and dissociation; (2) Analytically formulating the competition of monolayer and multiple-layer steps to derive closed-form expressions of monolayer and multiple-layer step populations and nanorod diameters; (3) Designing nanorods by using the scientific insights from the closed-form theory (as well as atomistic simulations); and (4) Exploring technological benefits of the scientific advancements. This research relies on the synergy of analytical formulations, atomistic simulations (density-functional-theory or DFT based ab initio, classical molecular dynamics, lattice kinetic Monte Carlo), and experiments; the prototype material is face-centered-cubic Cu. If successful, the proposed research will result in a scientific theory of nanorod growth, which in turn enables discoveries of new nanorods and subsequently innovations of energy technologies. As one example, the enabled discovery of small and well-separated metallic nanorods has subsequently led to the innovation of a technology - metallic glue in ambient. This technology has been covered in ~200 news reports in 20-30 countries during the first two months of 2016; examples of new agencies include Fortune Magazine, Popular Mechanics, Yahoo News, and Fox News.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Past and Future Trends of Severe Storms

The objective of this research is to use machine learning methods to establish past trends in the severe storm record and build on this information to provide severe storms projections in a future climate. This objective aligns with Focal Area 3, which emphasizes big data analytics in combination with knowledge-guided AI.

58 GEOSCIENCES↗
DOE OSTI2025

The DESI-Lensing Mock Challenge: large-scale cosmological analysis of 3x2-pt statistics

The current generation of large galaxy surveys will test the cosmological model by combining multiple types of observational probes. Realising the statistical promise of these new datasets requires rigorous attention to all aspects of analysis including cosmological measurements, modelling, covariance and parameter likelihood. In this paper we present the results of an end-to-end simulation study designed to test the analysis pipeline for the combination of the Dark Energy Spectroscopic Instrument (DESI) Year 1 galaxy redshift dataset and separate weak gravitational lensing information from the Kilo-Degree Survey, Dark Energy Survey and Hyper-Suprime-Cam Survey. Our analysis employs the 3x2-pt correlation functions including cosmic shear and galaxy-galaxy lensing, together with the projected correlation function of the spectroscopic DESI lenses. We build realistic simulations of these datasets including galaxy halo occupation distributions, photometric redshift errors, weights, multiplicative shear calibration biases and magnification. We calculate the analytical covariance of these correlation functions including the Gaussian, noise and super-sample contributions, and show that our covariance determination agrees with estimates based on the ensemble of simulations. We use a Bayesian inference platform to demonstrate that we can recover the fiducial cosmological parameters of the simulation within the statistical error margin of the experiment, investigating the sensitivity to scale cuts. This study is the first in a sequence of papers in which we present and validate the large-scale 3x2-pt cosmological analysis of DESI-Y1.

79 ASTRONOMY AND ASTROPHYSICS↗