National Instrument List Mode Data Acquisition (NILA) System User Manual
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As applications for radiation detection become more demanding, and in turn improvements are made in the technology of radiation detection, there is a need for high speed digital detector readout electronics matching these improvements. Specifically, full control over the on-line processing resources of modern digital electronics is desirable so that researchers can develop custom algorithms for special applications.In the proposed effort, the 500 MHz digital readout electronics previously developed by our company will be redesigned to allow user access to the on-line processing resources. In Phase I, the division of online processing into vendor and user firmware sections has been studied on existing hardware. In Phase II, the hardware will be upgraded to better facilitate the division, and the firmware will be restructured into a robust vendor logic block (providing standard functions such as host I/O, on-board memory I/O, energy computation, MCA spectra, timestamps, waveform capture, run statistics, and triggering and timing) and a user logic block for custom algorithms (with templates and examples for frequently used functions). Investigating several options to divide online processing, it was determined that the most promising approach is to “partition” a single FPGA integrated circuit into a vendor and user section, which is supported in newer devices. The analog front end of the existing electronics proved suitable for most applications, in particular high rate measurements with germanium detectors. The design architecture for new electronics was developed, combining one of the new FPGA device with the analog front end.
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Metal additive manufacturing (AM) is a processing technology which builds 3D components from the bottom-up by selectively melting metal precursors to build a component part in a layer by layer fashion. This advanced manufacturing process promises to initiate a digital renaissance in American manufacturing by decreasing costs, increasing energy efficiency, enabling new component designs, and providing a manufacturing pathway for novel materials which cannot be processed by traditional means. In particular, additively produced parts offer designs that are otherwise impossible to fabricate, custom designs for a single part at no additional cost, and considerable weight savings when compared to conventional production techniques.
The Fermilab Test Beam Facility (FTBF) is a high-energy test beam used for precision tests of high-energy physics detectors. The FTBF has two beams lines, MTest and MCenter, which provides a variety particle types such as proton beam and secondary beams with muons, electrons, and kaons. The beam is variable in energy and intensity, and a target can be inserted into the beam to convert the protons to other particle types for users.
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DOE Alignment: Reduce the cost of floating offshore wind energy in deep waters to $45/MWh by 2035 from today’s estimated $150/MWh20 by: Developing operations and maintenance strategies and increasing wind turbine reliability to reduce periods of non-operation and reduce labor at sea through remote system health monitoring, inspection, and maintenance capabilities incorporating artificial intelligence and predictive maintenance.
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The report discusses the commissioning of the DAQ system of the Mu2e experiment. We studied how the tracker works and especially the tracker readout. We used a generator to send pulses and we tried to understand the output and non-output of the DTC, in order to validate the event and run format and all the failure modes. In section one, we describe Charged Lepton Flavour Violation, the main purpose of Mu2e, in section two we describe Mu2e experiment. Section three presents the tracker description and readout, meanwhile section four the DAQ system and event building. In section five, we start explaining the analysis we have done on events and all the failure modes we discovered. In section six, we have done an analysis of the logger and boardreader rate, we validated the generator frequency in section seven and studied the number of hits in function of the channel number in section eight. To conclude we investigated the channel to channel time differences in section nine and in section ten we explain our Monte Carlo simulation, reproducing ROCs readout.
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