An analysis of the radiation field in LHC by means of the upgraded version of the RadMon sensor.

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Università degli Studi di Pisa

Dipartimento di Ingegneria dell’Informazione

Corso di Laurea Magistrale in Ingegneria Elettronica

An analysis of LHC radiation levels

by means of the

upgraded version of the RadMon sensor

Laureando

Riccardo Castellotti

Matricola: 496764

Relatore

Prof. Roberto Saletti

Dr. Salvatore Danzeca

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Abstract

This work contains the results of an analysis of the radiation levels in the Large Hadron Collider of CERN measured by the RadMon (Radi-ation Monitoring system) sensors. CERN provides particle accelerators and detectors to accelerate beams of particles and observe their colli-sions. LHC is the accelerator where the highest energy experiments are installed. The unprecedented beam intensity and energy together with the physical dimensions of the collider and the amount of equip-ment involved make it unique in the world. One of the major issues for availability has historically been equipment faults and long term degradation due to radiation effect on the electronics. The R2E project (Radiation to Electronics) began its activities in 2008 with the target of reducing the beam dumps due to radiation effects to electronics. In the framework of this project, radiation levels monitoring takes an important role and the RadMon sensor was developed and installed in LHC. This thesis contains some results of the data extraction from these sensors, with particular emphasis on the improvements of the most recent iteration of the RadMon, called V6.

A brief overview of the most relevant effects of radiation to modern electronics and an illustration of the peculiarities of the challenges posed by LHC forego a detailed physical description of the sensor and a comparison of the specifications of the V5 and V6 iterations. The CERN’s accelerator control stack is then presented including some modification to the CERN-wide acquisition software performed as part of this work in order to retrieve the data from the CERN logging system. Some of the software used during the commissioning is illustrated. The

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leveraging the API bridges developed by the CERN community and the most widely used libraries for data analysis and visualization.

In the final chapter, some results of the mesaurements are shown: a first distributed measurement of the R-factor (made possible by the V6 sensors) for the LHC tunnel is presented. The baseline sensitivity to TID in the tunnel is vastly improved by the new ADC. An overview of the factors that allow the results normalization and to simulate the radiation levels is included.

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1 Introduction

And the LORD said, Behold, the people is one, and they have all one language; and this they begin to do: and now nothing will be restrained from them, which they have imagined to do.

Genesis, 11:6

CERN (European Organization for Nuclear Research) is the largest particle physics laboratory in the world. Its main function is t o provide the particle accelerators and the infrastructure needed for high-energy physics research, which are then used by international collaborations. Its flagship accelerator, LHC, has been built between 1998 and 2008 and has been operative since 2009.

The goal of the LHC is to accelerate and collide particle beams, producing interactions generating particles that are then revealed in the experiments. As the interaction cross sections of the events investigated by high energy physics are extremely low, a vast quantity of interactions is needed in order to produce them. The ratio between the number of interactions per unit of time and their cross section is known as instantaneous luminosity, while its time integral is referred to as integrated luminosity. The nominal value for

LHC is 1034_cm-2_s-1 _{for the first; during 2017 a total of 50.2 fb}-1 _{(1 fb = 10}-43

mˆ2) have been delivered to the experiments.

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The availability of a machine as complex as LHC is a very broad and complex topic. The particles are injected in two counter-circulating vacuum pipes and accelerated to their final energy (7 TeV). Once this energy is reached, the “STABLE BEAMS” phase begins, where the particles are collided and the experiments can finally take data. This phase can last as much as 35 hours, but typically the machine’s operators dump the beam after ~10 hours in order to increase the machine’s luminosity level. Homewer, beams are often dumped by the protection systems of the machine, yielding an average beam duration of ~6 hours. Once the beam is dumped, a ‘tournarond’ of at least 2 hours is necessary, even though premature dumps are caused by a fault that needs some intervention, resulting in an average downtime of 5.5 hours per dump.

From what is introduced above, it can be seen that in order to increase the availability, it is necessary to (i) reduce the the number of faults and (ii) reduce the average fault time. The number of dumps attributed to effects

of radiation on electronics were 70 out of 409 in 2012, an year with 23 fb-1

of luminosity, resulting in 3 dumps per fb-1_{. This was already a four times}

improvement over year 2011, which has been further improve to 0.15 dumps

per fb-1_{, but the final goal for High Luminosity LHC is 0.1 dumps per fb}-1_.

This works contains a survey upon the radiation levels measured in LHC areas with RadMons and a proof of the improved resolution provided by V6 RadMons over V5 ones and is structured as folows:

• Chapter 2 outlines effects of radiation on electronic system and devices,

• Chapter 3 introduces the state of the art of radiation monitoring in

CERN machines and the environment in which they operate,

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in the differences between the two,

• Chapter 5 describes the control software managing the RadMons,

• Chapter 6 contains the measurements performed in LHC with the V6

RadMons, including the first measurements of the R-factor during operation.

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2 Radiation effects on electronic components

Radiation effects on electronics can be divided in three main categories: Total Ionizing Dose (TID), Displacement Damage (DD) and Single Event Effects (SEE). While the first two mentioned effects are cumulative, the third one is of stochastic nature. Single Event Effects are individual events which occur when a single incident ionizing particle deposits in a volume enough energy to cause an effect. SEEs are classified in two categories: destructive and non-destructive. For this work, out of all the SEEs, only the Single Event Upsets (SEUs) are considered. In order to understand the sensing mechanism of the sensors used in this work, an overview of the radiation effects on electronics is necessary. The figure below summarizes the effects of radiation and the sensors employed.

Effects DD TID SEE Measures 1 MeV flu-ence Dose HEH and th fluences Sensors PiN RadFET SRAM

Figure 1: The “arrows” schematization for radiation effects on electronics

2.1 TID

The total ionizing dose is a cumulative effect due to the Coulomb interaction between the incident particle and the electrons of the lattice of the medium.

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an electron-hole pair. The International System of Units uses the Gray (Gy) for measuring ionizing radiation dose. 1 Gy is defined as the absorption of one Joule of radiation energy by one kilogram of matter, therefore 1 Gy= 1 N/ 1 Kg. D = dE dm e (1) The TID mainly depends on the type and energy of the impinging particle as well as on the medium density. For this reason, TID is proportional to the Linear Energy Transfer of the impinging particle:

LET = 1 ρ dE dx _e (2)

where ρ is the density of the medium and dE

dx

e is the lost energy per

length unity of the impinging particle. The conversion from LET to dose is straightforward for a mono-energetic beam of a single particle type that impinges perpendicularly into a block of material. In this circumstance, the

absorbed dose D can be calculated with {eq.1} as:

D = E m = E ρ· V = E ρ· A · ∆x,

where m is the mass of the block, E the deposited energy and ρ the mass density. Since the energy E can be considered as the sum of the energy deposited by each particle times the number of particles impinging:

D = Nparticles· ∆E1particle

ρ· A · ∆x = Nparticles A · 1 ρ ∆E1particle ∆x .

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The first factor is defined as the fluence Φ, the latter is the LET as can be

seen with the eq.2, so that a final expression is:

D = Φ· LET. (3)

When a beam composed of different particles and energies, different con-tributes have to be considered and the calculation of the dose through the

eq.3becomes more complex:

D = Z

LET (E)· dΦ(E)

dE ·dE. (4)

In the next section, the TID effects on MOS devices at micro- and macro-scopic levels are analyzed in order to understand the mechanism of dosime-try and estabilish the electrical parameters that carry the cumulated TID information.

2.1.1 TID effects on MOS devices

When an ionizing particle passes through a MOS device, it triggers a physical process that changes the electrical properties of the oxide. One of the most

sensitive parts is the SiO2 below the gate terminal. Positive charges are

stacked inside the oxide layer, while positive or negative ones can be trapped

in the Si-SiO2 interface. The phenomenon is explained in detail in (1) and

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M O S + - - +- - + + – ++ - + - - + + - –+- ++- +- + + – ++ - + – -+ ++ V+ V− 1 t = 0− preirradiation M O S + + + + -- -- + + + +-- + + - + - - -+ V+ V− 2 t = 0 ionizing burst M O S V+ V− 3 t = 0+ after initial recombination M O S + + + + + + + + + + + + ++ + + + + + V+ V− 4 t = 0+ after electron transport M O S + + + + + + + + + + + + V+ V− 5 t = t1 hole transport M O S + + + + + + V+ V− 6 t = t2 after hole transport

Figure 2: Evolution in time of charged particles inside the oxide of a MOS structure due to ionizing radiation

The scheme in fig.3summarizes the four major physical processes

contribut-ing to the charge accumulation in the oxide layer and on Si/SiO2 interface

under positive bias conditions.

1. As a particle passes through the oxide, electron-hole pairs (e-h) are generated along its track. Some of these pairs immediately recombine with each other, while some of them are separated by the electrical field applied. As the electrons have higher mobility, they quickly reach

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2. Holes slowly move toward the Si substrate causing a partial recovery

in Vth. This process is strongly depend on external conditions such as

applied field and temperature.

3. When they reach the Si interface, a fraction of the holes fall into deep, long-live trap sites, causing a long-lasting voltage shift.

4. Finally, the radiation induces traps formation right at Si/SiO2 interface.

Their occupancy is determined by the the applied bias, giving rise to a voltage-dependent component in the threshold shift.

GATE SiO2 Si --+ + + + + + + + + 1.1eV -+ (1) E-H PAIRS GENERATED BY IONIZING RADIATION (2) HOPPING TRANSPORT OF HOLES THROUGH LOCALIZED STATES (3) DEEP HOLE TRAPPING NEAR Si/SiO2 INTERFACE (4) RADIATION INDUCED INTERFACE TRAPS WITHIN Si BANDGAP

Figure 3: Schematic energy band diagram for MOS structure, indicating phsyical processes underlying radiation response

2.2 Displacement damage

The displacement damage (DD) is a non-ionizing effect that is cumulative over time. When a free particle hits an atom in the Si crystal structure, it can transfer to the atom enough energy to displace it from its original position, thus creating a vacancy in the crystal and an interstitial atom, the so called Frenkel point defect. In order to induce a single Frenkel defect in the Si

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lattice, the free particle should transfer to the Si atom a mininimum of 21

eV (2), while if the transferred energy is more than 1 KeV, a region of high

defects density, called cluster, is created. Electrons generate point defects for energies higher than 270 keV and clusters for energies higher than 8

MeV, thus a60_{Co source can induce DD via Compoton electrons. Protons}

and neutroni induce point defects and clusters for energies from 185 eV and 35keV respectively.

These defects in the lattice of the medium lead to the generation of new

energy levels in the bandgap of the semiconductor. In fig.4 five different

types of microscopic consequcences of DD are shown:

Ec Ev Ei 1 Generation Leakage current 2 Recombination Minority carriers lifetime 3 Trapping Minority CTE 4 Compensation Carrier removal 5 Tunneling Leakage current

Figure 4: DD effects in semiconductors

1. Thermal generation of e-h pairs: the defects are close to the center of the gap, allowing electrons in the valence band to pass in conduction band, thus leaving a hole in the valence band. This results in an

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tween electrons in conduction band and holes in the valence band. This decreases carriers’ lifetime, causing a degradation of the direct current of p-n junctions.

3. Trapping of carriers: new energy levels introduced by DD close to valence and conduction bands. Holes or electrons are temporarily trapped in these levels, reducing the Carrier Transfer Efficiency in CCD devices and particle detectors.

4. Compensation: new acceptor levels in the band gap cause a compen-sation of donor atoms followed by a decrease of the Fermi level. In case of strong radiation levels, this can lead to doping type inversion from n to p. In BJT devices the carrier compensation increases the collector resistance.

5. Tunneling: tunnel effect under strong electric fields is facilitated by traps.

As for the TID, the effect depends on both the particle type and its energy.

Two equations similar to eq. 1and eq.2can be written:

S = dE dx n , NIEL = 1 ρ dE dx n

where the subscript n is used to indicate the energy loss is due to nuclear interaction. NIEL is the Non Ionizing Energy Loss and quantifies the displacement damage cause by the different particle types and energies.

Similar to the eq.4, the displacement damage dose DDD is defined as:

D = Z

LET (E)· dΦ(E)

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In practical circumstancies, the effect of a broad particle spectrum is ex-pressed in relation to an arbitrary unit. At CERN, 1MeV neutrons are used,

therefore the equivalent fluence Φ1MeV is indicated. This quantity gives the

equivalent fluence of 1 MeV neutrons which would generate the same DD

effects on the device. The conversion from DDD to Φ1Mev is carried out by

dividing the DDD by the NIEL of 1MeV neutrons in silicon.

2.3 Single Event Effects (SEE)

SEEs are a broad cathegory of events caused by single particles which result in data corruption, transient disturbs, high current condition, loss of functionality. The representative value for SEEs is taken as the fluence of Hadron with energy higher than 20MeV, which is the low limit below which charged particle are generally considered not able to reach the device sensitive volume with an energy large enough to induce an SEE. However, there are four points to be kept in mind while considering the HEH fluence as a whole:

1. the fall-of below 20 MeV does not apply to neutrons, which have to be considered also at energies as low as 0.2 eV,

2. the effect of thermal neutrons (detailed in sec.2.3.1)

3. errors induced by high-Z particles have a strong dependence on energy even at energies higher than 20 MeV;

4. low-energy singly-charged particles present in mixed-fields can lead to SEUs through direct ionization in deep sub-micron SRAMs.

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2.3.1 Single Event Upsets

An SEU is the change of state of a bistable element caused by the ionization by a single particle or the nuclear reaction products of an energetic hadron. The ionization induces a current pulse in a p-n junction. The charge injected by the current pulse at a sensitive (‘off’) node of a bistable element may exceed the critical charge needed to change the logical state of the element. In order to measure the SEUs, the device cross section σ is defined as the number of SEU divided by the fluence Φ of the mono-energetic beam the device is exposed to:

σ(E) = NSEU

Φ(E)

The SEU mechanism can affect both bipolar and MOS technologies: an example is reported for the latter.

Figure 5: An SRAM cell hit by an ion.

The evolution towards smaller device features decreases the minimum charge needed to flip a bit and the sensitive area depth: these two effects partly compensate each other so that the bit cross section remains constant.

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On the other hand, the number of devices integrated in each chip increases, resulting in an increased Single Event Rate per chip.

Charged particles such as protons must have ~50 MeV energy to overcome the Coulomb barrier and penetrate an atomic nucleus, while non charged particles (neutrons) have also effect at lower energies. In particular, thermal

neutrons (~25 meV) in memories containing10_{B are known to cause upsets}

thanks to the reaction 10_B(n,α)7_{Li and the energy deposited by the resulting}

alpha particle.

For the reason explained before, the effect of charged and non-charged particles with energies higher than 50 MeV cannot be distinguished and this particles are typically referred to as High Energy Hadrons (HEH).

With respect to SEU sources, a radiation spectrum is tipically with a Risk factor (referred to as R), which is the ratio between the fluences of thermal neutron and highly energetic hadrons.

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3 Radiation monitoring at CERN

3.1 LHC radiation environment

Particle accelerators create an unique environment from the ionizing radi-ation point of view. The main sources of radiradi-ation are: (1) beam losses, due to collimators or collimator-like objects or beam-gas interactions and (2) beam-beam collisions in the interaction points. The resulting radiation field is constituted by a wide range of particles and energies and is referred to as a mixed-field environment.

With regard to the different locations of LHC, one can distinguish between the experiments, where only radiation tolerant components are installed, the injector lines and the LHC tunnel. In the last two areas three sub-categories are identified:

1. tunnel, in which the amount of electronics is minimal and every com-ponent is validated against SEEs reported (the lethargy spectrum is

reported in fig.6),

2. heavily-shielded (UJs in LHC), spectrum in fig. 7 (the effects of the

heavy shielding are shown with a simulation result in fig.9),

3. lightly-shielded (RRs in LHC) with less intense but ‘harder’ spectra, in fig.8.

In tunnel and in alcoves (as UJs and RRs are typically referred to), exclusive use of radiation hardened components is not possible due to the high cost, limited market availability and poor performance. In the following plots

particles energy spectra are reported. They are obtained with FLUKA (3), a

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Figure 6: Particle energy spectra representative for tunnel areas in LHC for nominal operation (7 TeV). Normalized to one proton-proton collision.

Figure 7: Particle energy spectra representative for lightly-shielded (RR) areas in LHC for nominal operation (7 TeV). Normalized to one proton-proton collision.

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Figure 8: Particle energy spectra representative for heavily-shielded (UJ) areas in LHC for nominal operation (7 TeV). Normalized to one proton-proton collision.

Figure 9: Particle energy spectra representative for heavily-shielded (UJ) areas in LHC for nominal operation (7 TeV). Normalized to one year of HL-LHC operation.

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3.1.1 Comparison with other radiation environments

1. Atmosferic: the study of radiation effects avionics has become more important in recent years. With the technologic scaling, the sensitivity per integrated chip can increase to significant values. A confrontation with typical accelerator values leads to the following results:

i. flux levels significantly below those in critical accelerator areas; ii. the proportion of HEH is similar to that in accelerator-like

envi-ronments;

iii. the thermal neutrons contribution s much lower, with a strong dependence on the material surrounding the system;

2. Proton-belt: the Earth’s inner proton radiation belt is the environ-ment that most resembles that of an acceleratore. This environenviron-ment is relevant for LEO (Low-Earth Orbits), including those of ISS and Earth-observation missions. The main difference with respect to accel-erator tunnels is the only relevant hadrons here are protons, while in accelerators also pions and neutrons can be found

3. Proton interplanetary environment: in this context, protons are the 99% of the particles, but most of the SEE are caused by heavy ions, which have an LET large enough to induce errors through direct ionization

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Figure 10: A graphical representation of the different quantities and how they relate to typical environments.

3.2 The R2E project

As mentioned before, LHC operations began in 2009 and previously devel-oped high energy physics experiments only employed a limited amount of electronics. One of the first experiment making wide use of electronics was the Cern Neutrino to Gran Sasso experiment (2006-2012) and the negative impact of radiation on electronic devices was first noticed in 2007, when multiple SEUs occured on the facility’s PLCs (used for non safety-critical service, such as air venting), causing a 5-days downtime.

The Radiation to Electronics (R2E) monitoring project was then estabilished with the purpose of increasing the MTBF of LHC to 1 week or more. As will be shown in the following sections, this condition equals to 0.5 dumps

per inverse femtobar (fb-1_{) for nominal LHC conditions. This target is even}

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a peak luminosity increased of a factor 5 over the one delivered during Run 2. Since the end of LHC’s Run 1, additional emphasis has been also put on the injector chain, composed of Linac 3, PSB, PS and SPS as a part of the LHC Injectors Upgrade (LIU) project. In the case of HL-LHC, the large peak luminosity would lead to a too high collision rate for the experiment detectors to process, in an effect known as pile-up. In order to mitigate this effect while achieving the desired integrated luminosity, the luminosity is leveled to a value below its peak performance. Due to the fact that the leveled integrated luminosity is only larger than the nonleveled one after a certain fill duration, HL-LHC will require relatively long fills to operate in an efficient manner, thus tolerating a very low number of radiation induced dumps for an efficient operation.

Location HEH fluence 1 MeV fluence TID

cm−₂ _Gy

UJ 5 x 109 _{5 x 10}10 ₁₀

RR 3 x 109 _{3 x 10}10 ₆

DS 5 x 1010 _5x1010 ₁₀₀

ARC 109 ₁₀9 ₂

Table 1: Expected radiation levels for HL-LHC IP 1 and 5 for a yearly 250

fb−1 _luminosity.

The mitigation efforts of the project involve two working groups:

• the MCWG (Monitoring and Calaculation Working Group), concerned

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• the RadWG (Radiation Working Group), testing component failure due to exposure to radiation fields, validating their employability and discussing radiation-tolerant solutions for equipment design.

In order to keep the overall failure rate under control and reach the goal defined by the MTBF target (1 week in nominal HL-LHC conditions) the following actions have to be fulfilled:

1. a complete inventory of the equipment installed in the shielded area and in the tunnel;

2. an accurate knowledge of the radiation levels in the areas where the electronics will be placed;

3. an equipment analysis, concentrated on two different aspects relatively to the position of the equipment piece: a total cross section value for every destructive and non-destructive event with the related downtime for equipment in the shielded areas and (just for equipment in tunnel) the TID and DD limits have to be taken into account.

More than the single piece cross-section, the interesting quantity is the total cross-section for the LHC subsystem they belong to, which can be obtained multiplying the single cross-section with the number of pieces installed in the accelerator, which can be in the range of thousands.

3.2.1 Large systems and the unique dependency on COTS components The control of LHC requirements an amount of electronic systems to be installed in radiation areas unique for its size and diversification. From power converters to safety electronics, from monitoring devices to the vac-uum system, electronics is necessary in positions very close to the beam and

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interaction areas. Depending on the functionality, each equipment can be replicated up to 1000s of times and components may be used in multiple systems in multiple units. This amount of system cannot be created with custom designs as it happens, for example, in space applications, where this is an economically viable. A notable difference with the space environment is also that a possibility to replace most of the systems after a few years of operation exists and predictive maintenance are possible, while in space applications it is neither possible to do any kind of maintenance nor replace the components.

Radiation-hard and relation-tolerant components are also affected by limited computational power/ electrical characteristics. Given the small market (mainly limited to medical and space applications) and the inherent com-plexities added at every stage of design, from technologic nodes to single component tests, the design has a much longer development cycle compared to COTS systems.

3.2.2 The monitoring activity

Dosimeters used at CERN are mainly divided in two categories, according to their ability to be checked during the acquisition (active) or not (passive). The passive dosimeters currently employed are RPLs, based on photolumi-nescence of glass following exposure to ionizing radiation, and RadFETs. The latter are also used in the RadMon system and their working principle

is explained in sec.4.1.1.

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doserate) and could not be employed as long-term dosimeters. In 2003 the RadMon v5 development began and the operation started in 2008, radically improving the measurement capabilities. RadMon v6 has been developed in years 2013-2016, further enhancing the measurements quality.

The main LHC experiments use their own dosimeters: at ATLAS the Ra-diation Monitor Sensor Board (RSMB) is employed, which makes use of RadFETs and PIN diodes while CMS developed the Beam Conditions and Radiation Monitoring System (BRM). These dosimeters are more focused on time resolution and are used as to assess beam conditions rather than the equipment degradation.

During the last few years (4), data from the BLMs mentioned above has been

analyzed in depth in order to be able to remove the high integrated noise of the measurement: the BLMs are meant to measure the doserate, whereas the relevant value from an effect mitigation point of view is the dose (which is, as explained before, the integral over time of the doserate).

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4 RadMon system

The RadMon (5) is an embedded dosimetry system capable of measuring

various aspects of the radiation field. A total of ~450 systems is installed in CERN’s accelerator tunnels and test facilities. The key characteristics of this system are:

1. It only uses commercial components,

2. It is radiation tolerant up to a certain dose and certain HEH fluence, 3. It communicates with an industrial bus used in CERN accelerators

(WorldFIP),

4. It is capable of monitoring SEE, TID and DD.

A reliable monitoring system for ionizing radiation is required to improve performance and reliability of the accelerator. A detailed knowledge of the radiation field intensity enables more accurate choices for electronic systems sensible to radiation during design, positioning and shielding. This kind of online monitoring allows anticipating device degradation and to foresee components replacement before destructive failure, thus avoiding costly downtime to the LHC.

RadMons are also used to verify shielding efficiency and benchmark FLUKA simulations, monitoring of radiation field in test facilities where LHC radia-tion mixed field is reproduced.

In order to measure TID, DD and High Energy Hadrons fluence, it employs RadFETs, PIN diodes and commercial SRAM memories.

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4.1 The sensing mechanisms

4.1.1 Total Ionising Dose - RadFET

RadFETs are p-channel MOSFETs optimized for monitoring the TID with a thick gate oxide. These dosimeters operate by the build-up of positive

trapped charge in the gate silicon oxide layer as show in sec. 2.1.1. This

positive trapped charge is responsible for a threshold voltage(Vth) shift of

the transistor. The sensitivity is determined as the variation of Vth as the

dose increases, while the saturation condition is reached when the threshold voltage does not vary anymore with the dose increasing. Three different version of RadFET with different oxide techniques are available: 100 nm, 400 nm and 1000 nm.

The reading circuit used in RadMon shortcircuits the gate to ground and

injects a current pulse Ids of 30ms every second. The Vsgtension represents

therefore the Vth and is read with an ADC. By shortcircuiting both the gate

and the drain to ground, the electric field in the gate oxide is almost null, reducing the probability for holes to escape recombination effects. This so-called “zero bias mode” also increases the saturation limit but lowers the sensitivity. Other biasing methods achieve higher sensitivity at cost of lower

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Figure 11: Plots of a Co-60 calibration for a 100nm thick RadFet with 0V

bias. The right plot shows a detail for low values of δVth.

Figure 12: The different bias conditions that can be applied to RadFets and the reading process. a) shows the non biased condition, b) shows the 5V bias condition and c) shows the reading process: a current pulse is injected

from the source into the drain and Vgs is read.

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is bought. An important question for deploying RadFets in a mixed field environment is whether their measurement is still an accurate indication

of TID levels or the Vth is affected by different effects. Extensive research

has been devoted to this topic, both with FLUKA Montecarlo simulation

(3) and radiation tests performed at the Paul Scherrer Institute concur to

the conclusion that protons in the energy range below 100 MeV can be

responsible of the diminuition of the RadFet response. The work in (6)

shows that a Co-60 calibration curve can be used in mixed field if the thin versions of RadFETs (100nm) is used and a 25% incertainty is accepted. 4.1.2 Displacement Damage- PIN diode

Silicon PIN diodes are used in forward bias to monitor 1-MeV equivalent neutron fluence. Particles interacting with the silicon of the diode generate both stable and non-stable defects in the silicon lattice which act as recombi-nation centers. This leads to the reduction of the minority carrier lifetime and of the silicon conductivity.

The reading of the PBW34F diode is done with a current pulse with the

same shape as the one used for the RadFET: the Vf raises as a consequence

of the reduction of the diode’s conductivity. The Vf is then sent to the same

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Figure 13: Radiation response of a silicon p-i-n diode: the diode’s

for-ward voltage Vf measured at constant current pulse versus 1-MeV neutron

equivalent fluence.

As can be seen in picture above, the Vf starts to be sensitive to radiation

damage only after few 1012_n

eq/cm. Therefore the diodes used in RadMon

are pre-irradiated for monitoring low fluence.

In the RadMon, three diodes are put in series in order to increase the

sensitivity. The conversion from Vf to 1MeV fluence uses a lookup table.

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Figure 14: Reading circuit for BPW34F PIN diode

4.1.3 Single Event Upsets - SRAM Memory

The key concept in using an SRAM memory as sensor is to consider the particle fluence as the source of its SEUs.

In RadMon system, the choice for memories is constrained by several pa-rameters:

1. the memory has to be latch-up free,

2. the effect of TID has to be negligible at least in the RadMon working lifetime,

3. an achievable resolution of minimum 1 × 108_pp/cm2,

4. commercial availability and price.

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a protons one: the latter can also be used to verify the cross section dependency with the accumulated TID.

A complete test campaign with a proton beam with energies higher than 50 MeV allows the calculation of the memory cross section with respect to HEH and thermal neutrons. This test has to be repeated with each new lot as the cross section have a strongly dependence on the analyzed lot. In order to assess the thermal neutrons cross section, irradiations with lower energies beams (in the thermal range) is necessary. The 200 MeV protons beam available in PIF facility at PSI laboratory in Switzerland and the thermal neutrons reactor in ILL in Grenoble are extensively used for this characterization.

4.2 V5

RadMon v5 development began in 2005 and it started to be operational at the same time of LHC (2008), where more than 300 sensors were employed (5).

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Figure 15: V5 block diagram.

The RadMon V5 architecture is reported in fig.15. Three main blocks can

be identified:

1. the communication block containing a MicroFIP controller, 2. the readout circuit for the SRAM chips,

3. the readout for RadFets and PIN diodes, including the ADC.

The communication block contains a MicroFIP controller which implements the WorldFIP protocol, manages the entire communication stack and is in charge of the readout timing for the sensors. It also contains a watchdog timer to recover from possible deadlock situations.

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The memories readout uses discrete components: a 24 bit free runner counter (made out of three 8 bits counter) is used to generate the addresses. The output is then stored in D-flipflop registers and compared with the initialization pattern (all 0s). The single event upsets are then stored in a triplicated register accessed by the MicroFIP controller. The triplication tecnique is commonly used to overcome the possible SEUs in the registers themselves. The voting on the correct values is carried out at control software level on the data read from the bus.

The SRAM sensor are assembled in a bank of four devices. The size of a single memory TC554001AF-70Lis 512 kbit × 8 bit, which results in 4 Mbits for chip and 16 Mbits per sensor. The memory bank is connected to a voltage regulator controlled with a mechanical switch placed on the RadMon board. The RadFet and PIN diode readout is entirely analog. In order to commu-nicate with the WorldFIP, an analog-digital conversion is necessary. The ADC used in V5 RadMons is a 12 bit ADC with a resolution of 2.44 mV and a maximum sampling rate of 125kSPS. The analog paths coming from PIN diodes and P-Mos RadFETs are connected to the ADC by means of a multiplexer (developed using discrete swithces) as the ADC is a single channel one.

The analog chain is similar for the two devices: a thermal-compensated current is supplied to the sensors and a tension is read, as explained in

(5). The current to the PIN diodes is 1 mA while for the RadFETs it is 10

µA. In order to improve the accuracy of the measurement, an additional

temperature compensation is be performed on both the sensors atsoftware level by means of the temperature as recorded by a PT100 RTD.

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the ADC.

A deported module is available for installations in order to deploy the RadFETs and PINs in zones where the radiation level is very high. Due to strict timing constraints, the memories can only be installed on the motherboard.

4.2.1 RadMon V5 operational issues

The main limit to the system lifetime is the increase in current consumption of the voltage regulators which results in RadMons motherboards only being able to withstand 80Gy of TID.

Most of the SEUs that happen on the MicroFIP controller are not critical thanks to the watchdog, but need to be filtered during during data analysis. In addition to that, physical presence is needed to switch between different settings. Physical access to the sensors is, during a typical operational year of LHC, possible only twice during the Technical Stops, when the whole operation of LHC is paused for one week for maintenance.

4.3 V6

A new version of the RadMon sensor, called V6, has been designed ias part

of (7) and of (8) and the main factors that drove the development can be

summarized as:

1. Higher radiation tolerance (> 200 Gy),

2. Modular architecture for easy replacement of parts and updates, 3. Remote reconfigurability,

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4. Improved measurement accuracy.

The higher radiation tolerance has been achieved thanks to extensive radia-tion test campaigns carried out on all the components.

4.3.1 Modular structure

The modular structure is depicted in fig. 16:

Figure 16: The modular structure of the V6 RadMon. The tree photos show: 1. the power supply board, 2. the main board, 3. the sensor board

POWER SUPPLY BOARD: allows connecting the RadMon to a standard 230 V supply available in CERN accelerators areas. No switching elements, which suffer from Single Event Burnout or Latchups, are employed. All the regulation is made by toroidal transformers, passive components and linear regulators. The maximum supplied power is 7W.

MAIN BOARD: is the core of the system, its block diagram is reported in

fig. 17. The central component is an Actel FPGA ProAsic3, a flash FPGA

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Figure 17: The block diagram for the V6 RadMon.

The FPGA implements all the logic needed to communicate with the external ADCs and to drive and analyze the memories.

On the main board two ADCs are employed, one for monitoring purposes, the other for the sensors readout. The ADCs employed in this version are 16 bits devices with a 250kSPS sampling rate with 8 independent channel that can be used synchronously. The monitoring ADC keeps track of all health signals, such as the supply voltages, the supplied current and the main board’s temperature,

SENSOR BOARD: consists in the RadFET, the PIN, their respective reading circuits and the SRAM memories blocks. The RadFET reading circuit has been modified in order to increase the dynamic range.

The RTD temperature sensor is installed in proximity of the RadFET and the PIN diodes. The temperature compensation is done in software.

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The SRAM memories are grouped in two banks of four chips: the first one uses the same Toshiba memories employed in the previous version, while the latter contains 4 Cypress 8MBit memories. Two voltage regulators capable of generating 18 V, 2.5V, 3.3 V and 5 V are controlled by means of analog switches connected to the FPGA. The use of the new memories is the main driver of measurement improvements, as will be investigated in the next sections.

4.4 V5 vs V6

As explained in (7), the upgrade of RadMon from V5 to V6 brought

im-provements in many areas, but the analysis of this work focuses on the measurement performance enhancement and the onboard diagnostics sub-system.

4.4.1 Analog measurements

The readout of the RadFET has been improved in order to be able to select the gate voltage remotely and also a gain factor in order to increase the dynamic range in highly radioactive installations. The scheme is reported below:

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Figure 18: Acquisition subsytem of the RadFet. In order to avoid the early saturation of the ADC, the output voltage can be controlled with S1 and S2. The switch S3 can control the gate voltage while S1 and S2 allow the division factor to be chosen between 2 and 10: selecting the second division factor the dynamic range of the ADC increases.

4.4.2 High Energy Hadrons and Thermal Neutron fluences

V5 RadMons employ four chips of TC554001AF-70L Toshiba SRAM memory. These are 4 MBit memories built with a 400nm CMOS process and a SOP32 package, which can be powered at 5V or 3V. This memory has a large

thermal neutrons cross-section due to the presence of 10_{Bo. The already}

mentioned10_{B -> α + Li can induce SEUs with the two particles: the alpha}

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has a 5 µ m penetration depth, while the Li ion can only deposit 37 fC with a 2.5 µ m penetration depth, thus can only be effective with the lowest voltage setting, when the critical charge inducing the SEU is lower. In addition to that, V6 RadMons contain 4 chips of CY62157EV30 Cypress memory.

These are 8 MBit memories built with a 90nm MoBl Rprocess and a TSOP32

package, which can be powered at 3.3 V or 2.5 V. This memory has a thermal neutrons cross section 400 times lower than the Toshiba one, so that the HEH measurements are not influenced by the thermal section of the LHC spectra.

4.4.3 On-board diagnostics

A second ADC of the same model of the one that performs the conversion of the analog readings of the sensor is used to monitor the health of the sensor: the voltage levels generated by the power board, the system temperature and the sensing devices biasing conditions are recorded and sent on the bus

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5 The sensors preparation

5.1 The RadMon software stack

The RadMon control software communicates with the monitoring devices located in the underground tunnel over a WorldFIP fieldbus. A total of 24 fieldbus segments, with a maximum of 32 monitors, constitute the basis of the system architecture. Each WorldFIP segment is connected to a FEC that acts as the bus arbitrator for the segment. The Radiation Monitoring (C/C++) application has been developed in the CERN FESA framework. The FESA class carries out the acquisition actions of an entire segment by means of the FIP driver which provides the low level communication with the single radiation monitoring devices. Each radiation monitor has a unique hardware address which is used as a key field in the database acting as a link to the monitor settings (e.g. memory voltage) and to the associated types of sensors (e.g. RadFET thickness and batch) with their calibration factors and initial voltage threshold. Upon boot time, the FECs upload all the information the FESA class contains performing the association between hardware address and calibration data to interpret the raw data correctly. During operation, data from the monitors are stored on-line in a database, named the “Measurements database” which is accessed with the TIMBER API. The data in the measurements database is stored for a period of one week with a time resolution of ~2 second. A subset of the data from the measurement database is stored on a long term basis in the so-called “Logging database” which can be accessed with the same API as the “Measurement” one.

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coop-erate in performing the measurement. 5.1.1 FESA

In order to be installed in a CERN facility, devices need to be compliant with many requirements. From a software perspective, this means that a FESA class for the device has to be created. FESA stands for Front-End Software Architecture and is the environment used by the equipment specialists to develop and deploy the software controlling the equipment. While the actual implementation of the FESA software for RadMons esulates from the scope of this work, a short introduction to this system is useful to better understand how the data has been retrieved.

The FESA infrastructure is composed of many elements:

• Real-Time framework, which orchestrates the device activity and calls

the routines needed to provide the application-specific behaviour;

• Graphical tools, to define the XML files that describe the public

in-terface of the device, a collection of methods that can be remotely invocated by the device, the server actions corresponding to those methods, sets of logical events that trigger the real-time activity;

• Code generation, the generation of the actual C++ code that is run on

the front-end machines;

• Test environment

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5.1.2 CMW

When the FESA class for the device is ready, devices are enabled to work on the CMW (Controls MiddleWare), which is the software communication infrastructure used in all the CERN-managed facilities to exchange between the devices and the control infrastructure (both code running in the front-end machines and the technical datacenter in Prevessin and humans, the so called ‘device experts’ or the operators of the accelerator).

5.1.3 CALS / Timber

From this transport layer, data are accessed through clients which rely on an API implemented in JAVA. Automatic logging is centrally managed by the CALS (Cern Accelerator Logging Service) team and made available through the Timber public interface. The public API for accessing data

stored in Timber is described in (9) A python bridge for this API is available

at (10) and an extension of the functionality was necessary for this. The

getScaled function has been created to wrap the corresponding JAVA

functionality to obtain measurement scaled with various algorithms (sum, max, min, average) and time spans. The current CALS is being obsoleted and will be replaced during LS2 with the next iteration of the Accerator Logging Service, NXCALS, which is based on Big-Data technologies such as HBase, HDFS, Kafka and Spark that were not available when the LHC Logging Project was launched in 2001.

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5.1.4 JAPC

The Java API for Parameter Control can be used to access device parameters, read and set their values. It abstracts the implementation specific details, such as the transport layer API and the FESA API, enabling for easy access to parameters by providing the device and parameter names. For this API,

a Python bridge exists too at (11).

5.2 The RadMons preparation

All the sofware used for the RadMons preparation is hosted at (12).

The RadMon are built entirely at CERN and tested one by one with a test bench that logs some of the characteristics of the single sensor, such as the ADC or the RTD calibration values or the production lot codes for

the memory (as explained in sec. 4.1.3 ) . The instance files that will be

uploaded to the front-end machines are generated automatically with these informations. Following the installation of the RadFETs and the PIN diodes, the starting threshold has to be reset as it depends on the single device. The threshold also depends on temperature, so that this operation has to be performed a few hours after the installation. This operation is performed by the reset-thresholds.py script, which starts reading the values from the sensor using the JAPC interface and then resets the threshold, so that at the beginning the measurements for TID and 1-MeV fluence are 0 as expected. From this moment on, the measurements are temperature-compensated thank to a PT100 resistance temperature detector installed

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SEU generatormode, where the FPGA generates random readings and publishes this random data. By dividing the SEU counts and the HEH fluence published, it was possible to make sure that the calibration factor used by the FPGA was the correct one.

5.3 Operational follow-up

Once the sensors are put in place and begin the measurement, they also publish many diagnostics measurements, such as the temperature (for both the deported module and the mother board), the ADC readings for the various biasing voltages (18 V, 5 V, 3V. . . ) and the currents absorbed by the

various devices as shown in fig. 17. These data are read and stored every

hour by a custom system, in addition to the standard CALS logging. For each quantity, threshold values are set and in case these limits are exceeded, the device experts receive a notification. Before an intervention during the Technical Stops, an Excel report is generated showing which sensors need an intervention.

The data is published in an internal webpage, for which two screenshot are

reported below. In fig.19, the values of the monitoring are shown, while in

fig.20, the values of the sensors are reported. From these images it is also

possible to see that the RadMon 1LM.4L1-18 is broken (notice all the light

red warnings highlighted in fig.19) and will be replaced during the next

available maintenance interval. This device broke after just a few months of service because of the placement in a very harsh position: the RadFETs

measured more than 100 Gy in a short time interval, as shown in fig. 21,

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Figure 19: Example table containing monitoring values from the RadMons. Only a subset of LHC RadMons is shown (the ones in point 1). The Radmon

1LM.4L1-18is highlighted.

Figure 20: Example table containing real-time measurements of the deployed RadMons. Only a subset of LHC RadMons is shown (the ones in point 1). The dose measured by 1LM.4L1-18 is enlarged.

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Figure 21: The TID measured over time by the RadFet installed on the motherboard of 1LM.4L1-18

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6 LHC measurements

The LHC is a circular particle collider 27-km long built underneath the border between Switzerland and France in the Geneva area. In order to understand to which area of the LHC the measurements are related, a brief introduction to the physical structure of the accelerator is provided.

The Arcs of LHC are the 2.45 km long sections of the accelerator which bend the particles beam toward the following Insertion Region. Each Arc is divided in 23 cells, where the base unit of a regular lattice structure of magnets is installed. The Insertion Regions are themselves composed by a Long Straight Section (LSS), which, as the name implies, are the straight section where the experiments and other components of the accelerator are installed (the “insertion points”), and the Dispersion Suppressors, which are the transition regions between the LSS and the Arcs. The LSS includes cells from 1 to 7, the DS 8-12 while the remaining are in the proper Arc region. The part of the machine between two insertion points is called sector and there 8 sectors in the LHC, each of them identified by a number from 1 to 8 starting from the Meyrin Point 1 and increasing clockwise. Points 1 and 5 are entirely devoted to physics: the first hosts the ATLAS and LHCf experiments, while the latter contains the CMS detectors and TOTEM. Points 2 and 8 contain both experiment and the beam injection magnets for injecting the beam from the SPS accelerator. Point 4 contains the RF cavities, which are the systems used to accelerate particles from the injection energy of 450 GeV to 7TeV used to collide particles. In Point 6 the dump system (two water-cooled carbon cylinders 7 m long) is installed. Point 3 and 7

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inserted close to the beam. These two points are the most radioactive ones, which means that only normal conducting magnets can be installed (the radiation levels are such that they would quench at a too high rate). In order to have the best measurements for these two points, the v6 radmons have been installed already during 2016-2017 EYETS.

Figure 22: Layout of a regular octant of LHC, highlighting the various parts.

6.1 SRAM readings

6.1.1 Comparison between Cypress and Toshiba

As it was reported in the previous section, the Toshiba memories of V6 RadMons in points 3 and 7 during 2017 where powered at 5V in order to have a response to the particles fluence as similar as possible to the

one that is recorded by the Cypress memory. In the following fig. 23, a

comparison between the two memories is reported to show that the same data is recorded from the two memories.

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Figure 23: A comparison between the counts recorded from the Cypress (in blue) and the Toshiba (in red) memory banks of a v6 RadMon installed in cell 18L7 during 2017.

6.1.2 Strategy for HEH and thermal neutrons discrimination

The strategy employed in order to discriminate HEH and Thermal neutron

is based on the observation, mentioned in (13), that lowering the biasing

voltage of an SRAM cell the thermal neutron cross section becomes as large as the proton cross section.

The contribution of SEUs at a given voltage can be expressed as:

NSEU(V) = σHEH(V)· ΦHEH+ σth(V)· Φth (5)

where σHEH(V)and σth(V)are the HEH and thermal neutrons cross section

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mea-equalities as the one in eq.5 are obtained and one can simplify them as: ΦHEH = NSEU(V1) − σth(V1)· Φth σHEH(V1) (6) Φth =

NSEU(V2) − σHEH(V2)· ΦHEH

σth(V2)

(7) With elementary linear algebra, it can be obtained that the the highest precision is reached when V1 and V2 are the supply voltages at which the cross section for HEH and thn are higher, respectively and the cross sections at the same supply voltage should be very different for HEH and thermals. A very important factor of the radiation spectrum is the so called risk-factor

R as explained in {sec.2.3.1}. The method used in V5 is described in (7) and

exploits the increased Toshiba memories cross section for thermal neutrons

at 3V. Using eq.8and eq.7, the R factor can be expressed as This method

implies that the supply voltage of memories on the RadMon has to be changed in the middle of the measurement, but as mentioned before, this operation on V5 RadMons requires physical access.

With V6 RadMons Cypress memories can be used to evaluate the HEH fluence assuming this measurement is not affected by thermal neutrons, then Toshiba memories at 3V can measure thermal neutrons fluence. With

eq.5, the following system of linear equations is obtained:

    

NSEU−CY = σHEH−CY · ΦHEH+ σth−CY· Φth

NSEU−TB= σHEH−TB· ΦHEH+ σth−TB· Φth

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Substi-tuting eq. 8and eq.7in the system, the fluences are obtained:

Φth =

NSEU−TB· σHEH−CY− NSEU−CY· σHEH−TB

σth−TB· σHEH−CY− σth−CY· σHEH−TB

,

ΦHEH =

NSEU−CY · σth−TB− NSEU−TB· σth−CY

σth−TB· σHEH−CY− σth−CY· σHEH−TB

From here, the R factor is calculated as:

R = Φth

ΦHEH

= NSEU−TB· σHEH−CY− NSEU−CY · σHEH−TB NSEU−CY · σth−TB− NSEU−TB· σth−CY

(8) This method reaches higher accuracy due to the low sensitivity of the Cypress memory to thermal neutrons.

6.1.3 R-factor values from LHC

The first measurement of the R-factor in LHC occured in 2011 with a

dedicated MD2 ₍₁₄_{) where the value estimated for the R-factor in the tunnel}

is 1.5. This value has been taken into account for measurements made from the MCWG up to 2017.

In 2017, some preliminary measurements of R-factor were performed for points 3 and 7. These measurements necessitated some manual elaboration of the data (explained below).

The first point of this measurement is retrieving the measurement for the High Energy Hadrons (HEH) fluence from the Timber logging system. The

results of such an export can be seen in {fig. 24} where the raw values have

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to different scenarios (the one of main interest is the HL-LHC one) because they do not take into account the delivered luminosity nor the integrated intensity for the period of time of the measurement.

Figure 24: HEH fluence from RadMons installed in sector 7. On top of the 2015 and 2017 bars, the ratio with the 2016 values are annotated.

Subsequently, the fluence measured by the Cypress memories is to be considered as only due to HEH and as such subtracted to the one measured from the Toshiba memory, which is composed by both a HEH and a thermal neutrons component. After this step, it is possible to retrieve the number of SEU counts generated by thermal neutrons by multiplying the remaining fluence by the HEH cross section. This number can now be divided by the

thermal neutron cross section in order to obtain the Φth.

Φremaining= ΦTB− ΦCY

NSEU−th= Φremaining· σHEH−TB

Φth = NSEU−th/σth−TB

R = Φth

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The results of these calculations are reported in fig. 25.

Figure 25: The R-factors calculated from RadMons installed in sector 7. Two factors inhibited the accuracy:

1. the Toshiba memories where powered at 5V in order to be able to monitor the correct functioning of the system, while, as explained in sec.6.1.2it should have been set at 3V. This has been modified at the end of 2017, ensuring that the measurements for the following years are more accurate.

2. low statistics: while the LSS of point 7 has high radiation levels com-pared to the tunnel, the number of SEUs measured by the memories is below 10 in most cases.

These two effects explain why some of the values are too low (some of them are also negative, which does not make any sense from the physical perspective). Anyway, the values measured for the two cells in the LSS (cell

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6.1.4 R-factor in RR53

The following plots represent the HEH fluences measured by the Toshiba (in orange) and the Cypress (in blue) for two RadMons close to RR53. The first column represent values from RADMON.5LM.RR53-10: this RadMon is located in the tunnel right outside the RR entrance. The right column contains values from RADMON.5LM.RR53-12, located inside the shielding of the RR.

From these plots, many points can be highlighted:

1. the shapes of the fluences are similar for the Cypress and the Toshiba banks and between the two RadMons, this is a check that the two RadMons and their memories worked properly;

2. the value of the R-factor oscillates widely for the first values due to

statitical incertanties, which disappear after a few fb-1 _{of operation;}

3. the final values for the R-factor as it is expected: the RadMon lo-cated outside the shield show an R-factor of 0.5 while the one behind shows 1.5, which means that the percentage of thermal neutrons in the shielded area is 3 times higher than outside (neutrons are thermalized by the shielding);

4. the values for the HEH fluence measured outside the RR

(2.3 · 109_HEH/cm−2_{) are much higher than those measured}

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Figure 26: HEH fluences and R-factors as recorded by RADMON.5LM.RR53-10 (left) and RADMON.5LM.RR53-12 (right).

6.2 TID improvement

One of the most notable improvements in the V6 version of the RadMon has been the introduction of a new ADC in the acquisition chain of the RadFET transistors.

The following plot shows the difference between the values measured for TID in the same cell of LHC (the cell 4L3, in the straight section of sector 3, where beam collimators are installed and therefore the radiation level are highest) for two time periods where the luminosity delivered by LHC was the same, 6 fb-1_.

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average and thus enabling the removal of noise. These two time windows

share the same cumulated intensity of 1.2 10 ·20_{charges. As we will show in}

sec.6.3, this type of scaling is not proper for LSS areas. The result of this is

that the absolute values are much different and this measurement cannot be used to scale the values to different machine scenarios (namely the nominal conditions for HL-LHC). What we can see, howewer, is how the baseline TID can be measured in the arcs with the v6 RadMons while the v5 ones are not able to distinguish between 0 and the actual values.

Figure 27: TID values measured in 4L3 cell of LHC. The 2016 data (in light blue) are relative to the period 2016/08/26 - 2016/09/02 and have been measured with a V5 RadMon. The 2017 data (in orange) are relative to the period 2017/09/24-2017/10/01 and have been measured by a V6 RadMon.

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Figure 28: TID values in measured in the left of Point 3. Both the data have been taken during timeframes with the same cumulated intensity (1.2e20 charges).

6.3 Scaling quantities and settings

In order to be able to scale the measurements currently available, it is necessary to understand which quantities impact the final radiation levels.

A first report of a study in these quantities is in (15). The results are that the

radiation levels are driven by luminosity mainly in the interaction points (where the experiments are located and the collisions happen) and in the odd cells of those sectors, while in the ARCs the scaling quantity to be taken into account is the integrated beam intensity. In areas with collimators, their setting play a big role in the HEH fluence and the related faults, as

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after the collision point and used to clean the collision debris, is plotted with respect to the luminosity of CMS. When the TCL is closed more particles are stopped by the collimator, generating a stronger shower which is measured

by the RadMon. During year 2017 (see fig. 30), instead, the TCL6 where

always kept close due to phsyical constraints of the operation mode of the machine, leading to a cumulated fluence 3 times higher compared to a luminosity increased just by 10%.

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Figure 30: 2017 data for RR53 RadMon HEH fluence vs CMS luminosity (TCL6 collimators in closed configuration all the year).

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7 Conclusions and outlook

The work of this thesis included the realization of a software to assist during the commissioning of the RadMons, the health monitoring system and an analysis focusing of some novelties introduced by the latest iteration of the sensors. All the results of this thesis are included in the framework of the R2E project and the analysis of the data will be part of the overall analysis of LHC radiation levels of Run2.

Data recorded during 2018 will include the R-factor calculated for all the sensors in the sectors where experiments are installed and the measurements for points 3 and 7 will be improved with more statistical data. The baseline measurement (the lowest value that can be measured reliably) is improved for TID thanks to the new ADC of the RadFet reading subsystem.

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Acknowledgements

My deepest gratitude goes to my CERN supervisor, Salvatore, who believed in me, offering me such a positive working experience and guiding me through it.

I would like to thank all the people I have worked with: Chiara, for making me feel welcome and for all the insights she shared with me, Georgios for being an example of professionalism and a reference for all the students and Joan for having shared with me his experience and skills. Thanks go also to Gabriele, with whom it was a pleasure to work and complement our skills, to Matteo, Rudy, Thomas, Alex, Vlad and all the others.

I want to thank the "Fermilab-Pisa family" and my flatmates Paolo, Gurjeet and Francesco for all the good moments we shared together.

Neither this nor many other works would have been possible without Elisa, who always supports me and my choices enduring with me any difficulty. A special mention goes to Giorgio, your advice is the most valuable. I will always bring with the memories of the time spent in Hammamet, that first trip to Africa is unforgettable.

To Piero and Laura: "you have been my breakfast, lunch and dinner". To Jacopo, Paolo, Yuri, Stefano, Vladimir, Silvia and all the other people I met in Pisa: I bring with me many good memories of the time spent together wherever I am.