Test beam results of ATLAS DBM pCVD diamond detectors using a novel threshold tuning method

This chapter describes some of the many pitfalls that may be encountered when developing the calorimeter system for a particle physics experiment. Several of the examples chosen for this chapter are based on the author’s own experience. Typically, the performance of a new calorimeter is tested in a particle beam provided by an accelerator. The potential pitfalls encountered in correctly assessing this performance both concern the analysis and the interpretation of the data collected in such tests. The analysis should be carried out with unbiased event samples. Several consequences of violating this principle are illustrated with practical examples. For the interpretation of the results, it is very important to realize that the conditions in a testbeam are fundamentally different than in practice. This has consequences for the meaning of the term “energy resolution”. It is shown that the way in which the results of beam tests are quoted may create a misleading impression of the quality of the tested instrument.

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Upgrade of CMS Full Simulation for Run 2

EPJ Web of Conferences ◽

10.1051/epjconf/201921402012 ◽

2019 ◽

Vol 214 ◽

pp. 02012

Author(s):

Vladimir Ivanchenko ◽

Sunanda Banerjee

Keyword(s):

Monte Carlo ◽

Simulation Software ◽

Pixel Detector ◽

Test Beam ◽

Hadronic Calorimeter ◽

Cms Detector ◽

The Status ◽

Full Simulation

We report on the status of the CMS full simulation software for Run 2 operations of the LHC. Initially, Geant4 10.0p02 was used and about 16 billion events were produced for analysis of 2015-2016 data. In 2017, the CMS detector was updated with a new tracking pixel detector, a modified hadronic calorimeter electronics, and extra muon detectors added. Corresponding modifications were introduced in the full simulation and Geant4 10.2p02 was adopted for 2017 simulation productions; that includes an improved Geant4 for multi-threaded mode, which became the default for 2017. For the 2018 Monte Carlo productions, the full simulation has been updated further. The new Geant4 version 10.4 is used, adopted for the production after detailed validations using test-beam and collision data. The results of validations will be described in details. Several aspects of the migration to Geant4 10.4 and modifications in CMSSW simulation software will be also discussed.

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Denitrification Control in a Recirculating Aquaculture System—A Simulation Study

Processes ◽

10.3390/pr8101306 ◽

2020 ◽

Vol 8 (10) ◽

pp. 1306

Author(s):

Pedro Almeida ◽

Laurent Dewasme ◽

Alain Vande Wouwer

Keyword(s):

Carbon Source ◽

Carbon Sources ◽

Aquatic Organisms ◽

Operating Conditions ◽

Toxic Substances ◽

Recirculating Aquaculture System ◽

Treatment Technology ◽

Tuning Method ◽

Recirculating Aquaculture ◽

Aquaculture System

The recirculating aquaculture system (RAS) is a land-based water treatment technology, which allows for farming aquatic organisms, such as fish, by reusing the water in the production (often less than 5%). This technology is based on the use of filters, either mechanical or biological, and can, in principle, be used for any species grown in aquaculture. Due to the low recirculation rate, ammonia accumulates in the system and must be converted into nitrate using nitrification reactors. Although less toxic for fish, nitrate can also be further reduced into nitrogen gas by the use of denitrification biofilters which may create several issues, such as incomplete denitrification, resulting in toxic substances, such as nitrite and nitric oxide, or a waste of carbon source in excess. Control of the added quantity of carbon source in the denitrification biofilter is then mandatory to keep nitrate/nitrite concentrations under toxic levels for fish and in accordance with local effluent regulations, and to reduce costs related to wasted organic carbon sources. This study therefore investigates the application of different control methodologies to a denitrification reactor in a RAS. To this end, a numerical simulator is built to predict the RAS behavior and to allow for the comparison of different control approaches, in the presence of changes in the operating conditions, such as fish density and biofilter removal efficiency. First, a classical proportional-integral-derivative (PID) controller was designed, based on an SIMC tuning method depending on the amount of ammonia excreted by fish. Then, linearizing and cascade controllers were considered as possible alternatives.

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High-Order Filtered PID Controller Tuning Based on Magnitude Optimum

Mathematics ◽

10.3390/math9121340 ◽

2021 ◽

Vol 9 (12) ◽

pp. 1340

Author(s):

Damir Vrančić ◽

Mikuláš Huba

Keyword(s):

A Priori ◽

Higher Order ◽

Process Models ◽

Pid Controllers ◽

Tuning Method ◽

Output Noise ◽

Pid Controller Tuning ◽

Output Time ◽

Tuning Methods ◽

Measured Input

The paper presents a tuning method for PID controllers with higher-order derivatives and higher-order controller filters (HO-PID), where the controller and filter orders can be arbitrarily chosen by the user. The controller and filter parameters are tuned according to the magnitude optimum criteria and the specified noise gain of the controller. The advantages of the proposed approach are twofold. First, all parameters can be obtained from the process transfer function or from the measured input and output time responses of the process as the steady-state changes. Second, the a priori defined controller noise gain limits the amount of HO-PID output noise. Therefore, the method can be successfully applied in practice. The work shows that the HO-PID controllers can significantly improve the control performance of various process models compared to the standard PID controllers. Of course, the increased efficiency is limited by the selected noise gain. The proposed tuning method is illustrated on several process models and compared with two other tuning methods for higher-order controllers.

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A Modified 2-DOF Control Framework and GA Based Intelligent Tuning of PID Controllers

Processes ◽

10.3390/pr9030423 ◽

2021 ◽

Vol 9 (3) ◽

pp. 423

Author(s):

Gun-Baek So

Keyword(s):

Disturbance Rejection ◽

Pid Controller ◽

Weighting Function ◽

Pid Controllers ◽

Set Point ◽

Tuning Method ◽

Point Tracking ◽

Load Disturbance ◽

Control Framework ◽

Feedforward Controller

Although a controller is well-tuned for set-point tracking, it shows poor control results for load disturbance rejection and vice versa. In this paper, a modified two-degree-of-freedom (2-DOF) control framework to solve this problem is proposed, and an optimal tuning method for the pa-rameters of each proportional integral derivative (PID) controller is discussed. The unique feature of the proposed scheme is that a feedforward controller is embedded in the parallel control structure to improve set-point tracking performance. This feedforward controller and the standard PID con-troller are combined to create a new set-point weighted PID controller with a set-point weighting function. Therefore, in this study, two controllers are used: a set-point weighted PID controller for set-point tracking and a conventional PID controller for load disturbance rejection. The parameters included in the two controllers are tuned separately to improve set-point tracking and load dis-turbance rejection performances, respectively. Each controller is optimally tuned by genetic algo-rithm (GA) in terms of minimizing the IAE performance index, and what is special at this time is that it also tunes the set-point weighting parameter simultaneously. The simulation results performed on four virtual processes verify that the proposed method shows better performance in set-point tracking and load disturbance rejection than those of the other methods.

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