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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Pulse shape measurements for neutron/gamma discrimination using the TOFPET2 ASIC

Many highly pixelated organic scintillator detection systems would benefit from independent readout of each scintillator pixel. Recent advances in Silicon Photomultiplier (SiPM) technology makes this goal feasible, however the data acquisition from potentially hundreds or thousands of channels requires a low-cost and compact solution. For pixelated neutron detection with organic scintillators, the capability to distinguish between neutron and gamma interactions using Pulse Shape Discrimination (PSD) is required along with pulse charge and time of arrival. The TOFPET2 ASIC from PETsys Electronics is a 64-channel readout chip providing pulse time and charge integration measurements from SiPMs, and is specifically designed for time-of-flight positron-emission tomography. Using an 8 × 8 array of 6 mm × 6 mm J-series SiPMs from SensL/OnSemi (ArrayJ-60035-64P-PCB), we have studied the energy and PSD performance of the TOFPET2 ASIC using a 4 × 4 array of 6 mm × 6 mm × 30 mm trans -Stilbene crystals from Inrad Optics and a custom SiPM routing board from PETsys Electronics. In conclusion, using a time-over-threshold method, we measure a maximum PSD figure-of-merit of approximately 1.2 at 478 keV (the Compton edge of 662 keV) for a J-series SiPM operating at an over-voltage of 3V.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Waveform processing using neural network algorithms on the front-end electronics

In a multi-channel radiation detector readout system, waveform sampling, digitization, and raw data transmission to the data acquisition system constitute a conventional processing chain. The deposited energy on the sensor is estimated by extracting peak amplitudes, area under pulse envelopes from the raw data, and starting times of signals or time of arrivals. However, such quantities can be estimated using machine learning algorithms on the front-end Application-Specific Integrated Circuits (ASICs), often termed as “edge computing”. Edge computation offers enormous benefits, especially when the analytical forms are not fully known or the registered waveform suffers from noise and imperfections of practical implementations. In this work, we aim to predict peak amplitude from a single waveform snippet whose rising and falling edges containing only 3 to 4 samples. We thoroughly studied two well-accepted neural network algorithms, Multi-Layer Perceptron (MLP) and Convolutional Neural Network (CNN) by varying their model sizes. Further, to better fit front-end electronics, neural network model reduction techniques, such as network pruning methods and variable-bit quantization approaches, were also studied. By combining pruning and quantization, our best performing model has the size of 1.5 KB, reduced from 16.6 KB of its full model counterpart. It can reach mean absolute error of 0.034 comparing to that of a naive baseline of 0.135. Such parameter-efficient and predictive neural network models established feasibility and practicality of their deployment on front-end ASICs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Search in diphoton and dielectron final states for displaced production of Higgs or Z bosons with the ATLAS detector in s = 13 TeV p p collisions

A search is presented for displaced production of Higgs bosons or Z bosons, originating from the decay of a neutral long-lived particle (LLP) and reconstructed in the decay modes H → γ γ and Z → ee . The analysis uses the full Run 2 dataset of proton-proton collisions delivered by the LHC at an energy of $\sqrt{s}$ = 13 TeV between 2015 and 2018 and recorded by the ATLAS detector, corresponding to an integrated luminosity of 139 fb -1 . Exploiting the capabilities of the ATLAS liquid argon calorimeter to precisely measure the arrival times and trajectories of electromagnetic objects, the analysis searches for the signature of pairs of photons or electrons which arise from a common displaced vertex and which arrive after some delay at the calorimeter. The results are interpreted in a gauge-mediated supersymmetry breaking model with pair-produced Higgsinos that decay to LLPs, and each LLP subsequently decays into either a Higgs boson or a Z boson. The final state includes at least two particles that escape direct detection, giving rise to missing transverse momentum. No significant excess is observed above the background expectation. The results are used to set upper limits on the cross section for Higgsino pair production, up to a $\bar{χ}^0_1$ mass of 369 (704) GeV for decays with 100% branching ratio of $\bar{χ}^0_1$ to Higgs (Z) bosons for a $\bar{χ}^0_1$ lifetime of 2 ns. A model-independent limit is also set on the production of pairs of photons or electrons with a significant delay in arrival at the calorimeter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Search for displaced photons produced in exotic decays of the Higgs boson using 13 TeV p p collisions with the ATLAS detector

A search is performed for delayed and nonpointing photons originating from the displaced decay of a neutral long-lived particle (LLP). The analysis uses the full run 2 dataset of proton-proton collisions delivered by the LHC at a center-of-mass energy of $\sqrt{s}$ = 13 TeV between 2015 and 2018 and recorded by the ATLAS detector, corresponding to an integrated luminosity of 139 fb -1 . The capabilities of the ATLAS electromagnetic calorimeter are exploited to precisely measure the arrival times and trajectories of photons. The results are interpreted in a scenario where the LLPs are pair produced in exotic decays of the 125 GeV Higgs boson, and each LLP subsequently decays into a photon and a particle that escapes direct detection, giving rise to missing transverse momentum. No significant excess is observed above the expectation due to Standard Model background processes. The results are used to set upper limits on the branching ratio of the exotic decay of the Higgs boson. A model-independent limit is also set on the production of photons with large values of displacement and time delay.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Ride Pingo to Transit

In this project, we developed an on-demand microtransit first- and last-mile service. To integrate the service with fixed-route transit, we developed a feature called Transit Connect that prioritized riders’ on-time arrival at the transit station over other service requirements. We first prototyped service and related algorithms in a simulated environment, and then piloted the service in the city of Kent, Washington. Our algorithm incorporates request-specific hard drop-off deadlines to ensure timely arrivals for transit transfers. In the pilot, these constraints were obtained from GTFS Realtime data to accurately determine the schedule of the transit and the location of the stations. This approach introduced the ability to accept or decline new requests based on the timing of transit connections for these new requests and connection status of onboarding customers. The pilot (called “Ride Pingo to Transit”) deployed a fleet of three 14-person vans, ran from September 2021 to March 2023, and served a total of 21,329 trips. Transit Connect was offered for drop-offs at both Kent Station and the Kent Valley hub. In total, 2,844 such trips were completed. This dataset was collected from our pilot, which includes the following: - Requests: List of all trip requests, including those that were actually served and those not materialized. - Fleet: Daily vehicle service logs. - Service details: Daily vehicle stop logs (boarding and alighting). - Trip types: First mile, last mile, or point-to-point. ![pingo to transit](pingo-to-transit.jpg)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

A data-driven operational model for traffic at the Dallas Fort Worth International Airport

Airports are on the front line of significant innovations, allowing the movement of more people and goods faster, cheaper, and with greater convenience. As air travel continues to grow, airports will face challenges in responding to increasing passenger vehicle traffic, which leads to lower operational efficiency, poor air quality, and security concerns. This paper evaluates methods for traffic demand forecasting combined with traffic microsimulation, which will allow airport operations staff to accurately predict traffic and congestion. Using two years of detailed data describing individual vehicle arrivals and departures, aircraft movements, and weather at Dallas-Fort Worth (DFW) International Airport, we evaluate multiple prediction methods including the Auto Regressive Integrated Moving Average (ARIMA) family of models, traditional machine learning models, and DeepAR, a modern recurrent neural network (RNN). We find that these algorithms are able to capture the diurnal trends in the surface traffic, and all do very well when predicting the next 30 minutes of demand. Longer forecast horizons are moderately effective, demonstrating the challenge of this problem and highlighting promising techniques as well as potential areas for improvement. Traffic demand is not the only factor that contributes to terminal congestion, because temporary changes to the road network, such as a lane closure, can make benign traffic demand highly congested. Combining a demand forecast with a traffic microsimulation framework provides a complete picture of traffic and its consequences. The result is an operational intelligence platform for exploring policy changes, as well as infrastructure expansion and disruption scenarios. To demonstrate the value of this approach, we present results from a case study at DFW Airport assessing the impact of a policy change for vehicle routing in high demand scenarios. This framework can assist airports like DFW as they tackle daily operational challenges, as well as explore the integration of emerging technology and expansion of their services into long term plans.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

CryoFold: Determining protein structures and data-guided ensembles from cryo-EM density maps

Cryoelectron microscopy requires molecular modeling for refinement of structures. Ensemble models arrive at low free-energy molecular structures, but are computationally expensive and limited to resolving only small proteins. Here, we introduce CryoFold, a pipeline of molecular dynamics simulations that determines ensembles of protein structures by integrating density data of varying sparsity at 3–5 Å resolution with sequence information and coarse-grained topological knowledge of the protein folds. We present six examples, folding proteins between 72 and 2,000 residues, including large membrane and multi-domain systems, and results from two Electron Microscopy Data Bank (EMDB) competitions. Driven by data from a single state, CryoFold discovers ensembles of common low-energy models together with rare low-probability structures that capture the equilibrium distribution of proteins constrained by the density maps. Many of these conformations are experimentally validated and functionally relevant. We arrive at a set of best practices for data-guided protein folding that are controlled using a Python graphical user interface (GUI).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Use of Systems Engineering in Repurposing Coal-Fired Power Plants with Malta Pumped Thermal Energy Storage System

he electric sector across North America is facing a transition. Both economics and policy decisions have pointed towards a broad retirement of fossil assets across markets. Owners are facing the problem of how to evolve the base of the electric sector from fossil asset to greener alternative. Coal-fired power plants built the modern electricity grid. Their rotating machinery are the beating heart of the grid, providing essential resiliency and reliability services. Power plant retirements are disruptive to plant workforces and cause outsized impacts on surrounding communities. The transition from thermal power plants that use rotating machinery to generate electricity (e.g., coal- and gas-fired plants) to variable, inverter-based generation (e.g., solar and wind) is affecting the reliability of the electric grid. Grid operators and national regulators have issued warnings about known and anticipated risk. In 2021, Malta Inc. was awarded a Department of Energy (DOE) grant to study how to integrate a Malta 100MW Pumped Heat Energy Storage (PHES) system with a retiring coal-fired power plant to meet emissions requirements, retain plant workforces, preserve communities, and maintain grid reliability. This presentation provides a summary of this study, focusing on how systems engineering approach was used to arrive at a proposed design concept that met multiple objectives and requirements. There will be three main parts for this presentation. The first part of the presentation will focus on how different systems engineering was applied for this work. In particular, the following areas: stakeholder engagement, site selection process, developing requirements and use cases for the integrated system, defining the system and its boundary, coming up with different system architecture/option, performing a techno-economic analysis to compare the different options and down selection of the preferred option, will be discusses. For these areas, discussion on the decisions on how much breadth and depth to go into each area will be provided. These discussions provide good insights into how to apply systems engineering. The second part of the presentation will provide a deeper dive into the two recommended integration options that repurpose coal-fired power plants with Malta PHES system. The comparison of the two options and general guidance of how to choose an option will be provided. This is particularly useful for utilities who are facing coal-plant retirements. The two options will be compared based on its performance (such as power output, efficiency), complexity, and cost. The social impact on local communities of the two options will also be discussed. The final part of the presentation will discuss the impact that this work has had, including Malta Inc. being invited to the White House to discuss progress and outcomes of this work with the Interagency Working Group on Coal and Power Plant Communities and Economic Revitalization. In summary, this presentation aims to provide a showcase of how sy

25 ENERGY STORAGE↗
DOE OSTI2020

DISCOVR: Development of Integrated Screening, Cultivar Optimization, and Verification Research

The DISCOVR consortium has developed and is applying an integrated platform and workflow for standardized, deep characterization of highly productive and resilient microalgae strains. New strains are screened using three consecutive tiers in a conceptual down-selection funnel to arrive at the most promising strains. At tier I, strains are screened on gradient incubators to determine their temperature and salinity tolerance range, and to evaluate their resistance to infectious agents (e.g., chytrids). At tier II, the strains’ winter and summer season biomass productivities are quantified in Laboratory Environmental Algae Pond Simulator (LEAPS) photobioreactors, and biomass composition is determined under N-replete and N-deplete conditions. At tier III, the best winter and summer season strains are evaluated in indoor crash ponds to determine their resilience to induced infections, and strains are tested in outdoor raceway ponds to confirm high biomass productivity and culture stability. The top strains are then evaluated in seasonal SOT outdoor pond culture trials at AzCATI, the dedicated Department of Energy SOT (State of Technology) testbed. Additional research is carried out on evaluating growth promoting molecules, reducing the impact of oxygen inhibition, optimizing pond operational conditions, measuring compositional shift dynamics, developing integrated pest management strategies, analysing culture health using 96 well-plate tools, implementing spectroradiometric monitoring and using machine learning to predict culture crashes.

Huesemann, Michael H↗
DOE OSTI2024

Enabling Scale-Up Through Multi-Fidelity Adaptive Computing

We present ideas from our ongoing work in adaptive computing - an optimization framework that allows us to strategically deploy various fidelity level experiments and simulations to guide decision making. The framework aims to enable uncertainty quantified scale-up of simulations and experiments, which causes increased complexity. A key feature of the framework is the integration of user-specified local model trustworthiness estimates. Adaptive sampling strategies allow us to optimally exploit the multiple fidelity level information and trustworthiness measures to arrive at the best decisions within a highly limited budget of objective function evaluations.

adaptive sampling↗
DOE OSTI2022

Arrival Directions of Cosmic Rays above 32 EeV from Phase One of the Pierre Auger Observatory

A promising energy range to look for angular correlations between cosmic rays of extragalactic origin and their sources is at the highest energies, above a few tens of EeV (1 EeV ≡ 10$^{18}$ eV). Despite the flux of these particles being extremely low, the area of ∼3000 km$^{2}$ covered at the Pierre Auger Observatory, and the 17 yr data-taking period of the Phase 1 of its operations, have enabled us to measure the arrival directions of more than 2600 ultra-high-energy cosmic rays above 32 EeV. We publish this data set, the largest available at such energies from an integrated exposure of 122,000 km$^{2}$ sr yr, and search it for anisotropies over the 3.4π steradians covered with the Observatory. Evidence for a deviation in excess of isotropy at intermediate angular scales, with ∼15° Gaussian spread or ∼25° top-hat radius, is obtained at the 4σ significance level for cosmic-ray energies above ∼40 EeV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

A Review of Resilience and Long-Term Planning in Power and Water Systems in the United States

There is recognition among power and water utilities that the frequency and magnitude of high consequence and low probability events could increase as a result of climate change. The interconnected nature of energy-water systems raises the possibility of cascading failures, increasing complexity and risks. Resilience and long-term planning are important ways of weathering the effects of climate change. First, to understand more about resilience, we reviewed existing literature on resilience definitions, metrics, and modeling, focusing on integrated water-power systems. Second, to understand how resilience and planning are being applied in practice, we interviewed utilities and organized, curated, and synthesized the interview data to arrive at several key findings, which are presented here. We found that there is not a consistent definition for resilience, yet it is something that utilities regularly plan for, often with different names and varying methods/measures. However, there is a tangible shift in the industry towards defining and determining measurable resilience metrics. While the exact metrics are a work in progress, utilities are taking steps forward by (1) putting people and culture at the center of resilience, (2) recognizing their own interdependencies, and (3) pursuing better cross-sector collaboration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Shared automated vehicle fleet operations for first-mile last-mile transit connections with dynamic pooling

Shared automated vehicles (SAVs) have the potential to promote transit ridership by providing efficient first-mile last-mile (FMLM) connections through reduced operational costs to fleet providers and lower out-of-pocket costs to riders. To help plan for a future of integrated mobility, this paper investigates the impacts of SAVs serving FMLM connections, as a mode that provides flexibility in access/egress decisions and is well coordinated with train station schedules. To achieve this objective, a novel dynamic pooling algorithm was introduced to match SAVs with riders while coordinating the riders' arrival times at the light-rail station to a known train schedule. Microsimulations of SAVs and travelers throughout two central Austin neighborhoods show how larger service areas, higher levels of SAV demand, and longer arrival times between successive trains require larger SAV fleet sizes and higher SAV utilization rates to deliver close traveler wait times. Four-person SAVs appear to perform similar to 6-seat SAVs but will cost less to provide. Using a dynamic pooling algorithm tightly coordinated with train arrivals (every 15 min) delivers 87% of travelers to their stations in time to catch the next train, whereas uncoordinated assignments deliver just 58% of travelers in time.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Emigration and Survival of Hatchery‐Reared Coho Salmon Released as Parr and Smolts in a Reintroduction Program

ABSTRACT Releasing fish at varied life stages is an underutilized hatchery‐rearing practice. Columbia River Treaty tribes have been working to reintroduce extirpated Coho Salmon to historical habitats in upper watersheds. This effort has included the release of hatchery‐origin fish at both the parr and smolt life stages in the Yakima River Basin (Washington State USA), a tributary to the Columbia River. We evaluated releases of parr and smolts tagged with passive integrated transponders over 11 brood years. We assessed emigration timing, fish survival, and age‐at‐return for the two release groups. Emigrating juveniles released as smolts had higher survival and arrived downstream earlier than fish released as parr. Survival from release locations to adult return did not significantly differ for the two release groups. However, we observed a difference in apparent marine survival as fish released as parr had mean juvenile‐to‐adult return rates greater than fish released as smolts. Parr releases also tended to return at older age than smolt releases. Our results indicate that implementing practices to reduce homogenization of hatchery releases may produce survival and diversity benefits as fish mature to later life stages. Given the rapid ecosystem changes Pacific Salmon are experiencing throughout their life cycles, practices such as this may have increasing utility and import.

Bosch, William J. [Yakama Nation Fisheries Toppeni↗
DOE OSTI2020

Uncertainty Analysis Framework for the Hospital Resource Supply Model for Covid-19

In March and April of 2020 there was widespread concern about availability of medical resources required to treat Covid-19 patients who become seriously ill. A simulation model of supply management was developed to aid understanding of how to best manage available supplies and channel new production. Forecasted demands for critical therapeutic resources have tremendous uncertainty, largely due to uncertainties about the number and timing of patient arrivals. It is therefore essential to evaluate any process for managing supplies in view of this uncertainty. To support such evaluations, we developed a modeling framework that would allow an integrated assessment in the context of uncertainty quantification. At the time of writing there has been no need to execute this framework because adaptations of the medical system have been able to respond effectively to the outbreak. This report documents the framework and its implemented components should need later arise for its application.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Characterization of Orography-Influenced Riming and Secondary Ice Production and Their Effects on Precipitation Rates Using Radar Polarimetry and Doppler Spectra (CORSIPP-SAIL)

The Characterization of Orography-Influenced Riming and Secondary Ice Production and Their Effects on Precipitation Rates Using Radar Polarimetry and Doppler Spectra (CORSIPP) project was conducted to help improve the understanding of precipitation formation in orographically influenced terrain. Special focus is put on the two processes of riming and secondary ice production and their external drivers. Two instruments, a polarimetric W-band simultaneous transmission simultaneous reception (STSR) Doppler cloud radar manufactured by Radiometer Physics GmbH (RPG, instrument type RPG-FMCW-94-DP), from now on named LIMRAD94, and the video in situ snowfall sensor (VISSS), were deployed at the U. S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Surface Atmosphere Integrated Field Laboratory (SAIL) site in Gothic, Colorado between November 2022 and June 2023 during the second SAIL winter. Note that the exact dates of data availability differ between the instruments. Both instruments arrived at Gothic on November 2, 2022, 09:20 local time. VISSS, described by Maahn et al., is equipped with two camera systems with telecentric lenses. The two cameras are at a 90° angle to each other. This configuration allows for size-independent measurements by capturing images of hydrometeors from two sides at a high frame rate of 250 Hz. With a minimum detection size of 200 μm, VISSS provides valuable insights into particle size, number, shape, complexity, and fall velocity. The VISSS was deployed on the grassland next to the ARM facility with the amazing help of the ARM employees on site. The setup started on November 2, 2022, and was finished on November 5, 2022, without major problems. VISSS measurements were started on November 6, 2022. LIMRAD94 was installed on a scaffolding platform near Orehouse (Gothic) on November 9, 2022, with the great help of RMBL staff. LIMRAD94 was mounted on a cold temperature scanner prototype. After a short test of the setup on November 9, 2022, the digital control of the scanner elevation stopped working for (at that time) unknown reasons. All attempts to resolve the problem failed. This malfunction made it impossible to operate LIMRAD94 in scanning mode. The scanner was then manually moved to zenith pointing mode and between November 10 and November 15, 2022, vertical observations for polarimetric calibration were performed. On November 15, 2022, after the polarimetric calibration was applied, the scanner was manually moved to 40° elevation with azimuthal view towards the Ka-band ARM Zenith Radar (KAZR) and measurements were continued at constant elevation. Investigation of the scanner malfunction on February 6, 2023, by Benn Schmatz revealed a disengagement between the cogwheel of the elevation motor and the cogwheel moving the scanner in elevation. This mechanical issue was temporarily solved by re-engaging the cogwheels. This made the scanner operational again for about four weeks, until mechanical force disengaged the cogwheels again on March 15, 2023. This repeated scanner failure remained undetected for about three weeks until April 8, 2023; during this time the scanner was stuck at 72° elevation. However, the radar software continued to produce data files falsely indicating that the scanner was still operational. After the scanner failure was noticed, scanning was stopped again, and we returned to constant elevation measurements. On May 15, 2023, the cogwheels of the elevation motor were secured with additional screws sent by the manufacturer. At some point in May, the cogwheels of the azimuth motor were also disengaged by mechanical force, which still allowed for range height indicator (RHI) but no plan position indicator (PPI) scans in the last weeks of the campaign. The azimuth motor was repaired in Germany after the end of the campaign. Throughout the campaign, RMBL and ARM staff kept the radar and the VISSS free of snow.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Predicting multiphase flow and tracer transport for an underground chemical explosive test

Detecting radionuclide gas seepage from clandestine underground nuclear tests is central to nonproliferation explosion monitoring research. Yet, early-time (<6 day) gas transport driven by the explosive pressure wave remains poorly constrained due to scarcity of field data. We simulate multi-phase gas transport in the vadose zone using pre-shot data from a recent chemical explosion in P-Tunnel at the Nevada National Security Site, USA. Despite using a simplified 2D-radial model, predictions of tracer arrival matched observations within one order-of-magnitude. Our results show how transient blast forcing rapidly mobilizes gases from the cavity into surrounding rock – critical for optimizing sensor placement and test planning. This unique integration of field data and modeling represents a significant improvement in our ability to predict gas migration from underground explosions. More broadly, it offers insights into the coupled dynamics of pressure waves and contaminant transport in the vadose zone, with implications for monitoring and hazard assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Performance of the CMS electromagnetic calorimeter in pp collisions at √$_{s}$ = 13 TeV

The operation and performance of the Compact Muon Solenoid(CMS) electromagnetic calorimeter (ECAL) are presented, based ondata collected in pp collisions at√$_{s}$ =13 TeV at the CERN LHC, in the years from 2015 to 2018(LHC Run 2), corresponding to an integrated luminosity of151 fb$^{-1}$. The CMS ECAL is a scintillating lead-tungstatecrystal calorimeter, with a silicon strip preshower detector in theforward region that provides precise measurements of the energy andthe time-of-arrival of electrons and photons. The successfuloperation of the ECAL is crucial for a broad range of physics goals,ranging from observing the Higgs boson and measuring its properties,to other standard model measurements and searches for newphenomena. Precise calibration, alignment, and monitoring of theECAL response are important ingredients to achieve these goals. Toface the challenges posed by the higher luminosity, whichcharacterized the operation of the LHC in Run 2, the proceduresestablished during the 2011–2012 run of the LHC have been revisitedand new methods have been developed for the energy measurement andfor the ECAL calibration. The energy resolution of the calorimeter,for electrons from Z boson decays reaching theECAL without significant loss of energy by bremsstrahlung, wasbetter than 1.8%, 3.0%, and 4.5% in the |η| intervals[0.0,0.8], [0.8,1.5], [1.5, 2.5], respectively. This resultingperformance is similar to that achieved during Run 1 in 2011–2012,in spite of the more severe running conditions.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗