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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Simulation of the ATLAS New Small Wheel (NSW) System. In: Proceedings of International Conference on Technology and Instrumentation in Particle Physics 2017

New Small Wheel (NSW) is a major detector upgrade project of the ATLAS muon spectrometer for the LHC luminosity upgrade. NSW comprises sTGC and Micromegas as muon tracking detectors of high rate capability, and front- and back-end electronics for upgrading the muon level-1 trigger. Detailed simulation of the detectors and the electronics has been developed and used for the study of expected performance. An overview of the NSW system and some results of the trigger performance with the Micromegas are presented.

ATLAS↗
DOE OSTI2018

Tracking and Vertexing with the ATLAS Inner Detector in the LHC Run-2. In: Proceedings of International Conference on Technology and Instrumentation in Particle Physics 2017

Run-2 of the Large Hadron Collider (LHC) has provided new challenges to track and vertex reconstruction with higher centre-of-mass energies and luminosity leading to increasingly high-multiplicity environments, and boosted, highly-collimated physics objects. We present an overview of the ATLAS Inner Detector tracker in Run-2 including the track reconstruction algorithm, time-dependent alignment, tracking and vertexing performance.

ATLAS Inner Detector↗
DOE OSTI2018

CMOS Pixel Development for the ATLAS Experiment at HL-LHC. In: Proceedings of International Conference on Technology and Instrumentation in Particle Physics 2017

The high luminosity upgrade of the LHC necessitates a complete exchange of the current ATLAS Inner Tracker for a purely silicon one. Large areas therefore have to be covered by radiation tolerant, low cost and low material budget silicon detectors. New approaches are being explored using CMOS pixel sensors, providing charge collection in a depleted layer. They are based on technologies that allow to use high depletion voltages and high resistivity wafers for large depletion depths with multiple nested wells, enabling for CMOS electronics to be embedded safely into the sensor substrate. We are investigating depleted CMOS pixel detectors with monolithic or hybrid designs in view of their suitability for high trigger rates, fast timing and the high radiation environment at HL-LHC. This paper will discuss recent results of the main candidate technologies and the current developments towards a monolithic solution.

ATLAS ITk↗
DOE OSTI2021

Evaluation and Applications of Multi-Instrument Boundary-Layer Thermodynamic Retrievals

Recent reports have highlighted the need for improved observations of the atmosphere boundary layer. In this study, we explore the combination of ground-based active and passive remote sensors deployed for thermodynamic profiling to analyze various boundary-layer observation strategies. Optimal-estimation retrievals of thermodynamic profiles from Atmospheric Emitted Radiance Interferometer (AERI) observed spectral radiance are compared with and without the addition of active sensor observations from a May–June 2017 observation period at the Atmospheric Radiation Measurement Southern Great Plains site. In all, three separate thermodynamic retrievals are considered here: retrievals including AERI data only, retrievals including AERI data and Vaisala water vapour differential-absorption lidar data, and retrievals including AERI data and Raman lidar data. First, the three retrievals are compared to each other and to reference radiosonde data over the full observation period to obtain a bulk understanding of their differences and characterize the impact of clouds on these retrieved profiles. These analyses show that the most significant differences are in the water vapour field, where the active sensors are better able to represent the moisture gradient in the entrainment zone near the boundary-layer top. Furthermore, we also explore how differences in retrievals may affect results of applied analyses including land–atmosphere coupling, convection indices, and severe storm environmental characterization. Overall, adding active sensors to the optimal-estimation retrieval shows some added information, particularly in the moisture field. Given the costs of such platforms, the value of that added information must be weighed for the application at hand.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Chemistry imaging and distribution analysis of rare earth elements in coal using LIBS and LA-ICP-MS instruments

Currently, demand for rare earth elements (REEs) increased significantly. Coal is actively evaluated as potential economic sources for extraction of REEs. Here, in this work, laser-induced breakdown spectroscopy (LIBS) was evaluated for rapid estimation of REEs content and their distribution in the natural coal samples. The results were compared with similar laser ablation–inductively coupled plasma–mass spectrometry (LA-ICP-MS) measurements. Thirteen coal samples (nine standard samples and five natural samples) were used in this study. Powder samples were pressed into pellets while coal chunks were directly ablated for data recording. Pellets of the powder standard samples were used to optimize the data acquisition system and then data recorded with this optimized system was used to identify the proper data acquisition and analysis models. After establishing the proper data acquisition system and analysis model using the standard samples, natural coal samples in powder form and their chunks were utilized to record LIBS and LA-ICP-MS spectra. Multivariate calibration models were developed using four of the natural samples, which were evaluated by predicting the REE content in the fifth sample. Principal component analysis was performed on the LIBS data obtained from the natural samples and it classified all the samples with high accuracy. Two-dimensional (2D) elemental mapping on coal chunk samples was also performed using both LIBS and LA-ICP-MS to study the distribution of REEs in the samples. The resulting elemental images and their correlations can be used to infer mineral distributions.

01 COAL, LIGNITE, AND PEAT↗