Nagham Abdelrahman
email: nagham.abdelrahmanalhajjchehade@cstb.fr

Alhajj Chehade

Amine Lahouar

Omar Al-Mansouri

Nicolas Pinoteau

Roberto Piccinin

Marco Abate

Sébastien Remond

Dashnor Hoxha

BOND BEHAVIOR OF POST-INSTALLED REBARS DURING COOLING PHASE AFTER HIGH TEMPERATURE EXPOSURE

Keywords: Post fire, Concrete, post installed rebars, Pull-out tests, Bond strength

) have developed the bond resistance integration method (Pinoteau's method) to predict the bond resistance variation at different temperatures. Regarding post-fire behavior, design codes do not reproduce the behavior of PIRs during the cooling phase after exposure to high temperatures.

This paper presents an experimental study on post-installed rebars using organic mortars in concrete after exposure to high temperatures. Fire tests were conducted under standard ISO 834-1 fire conditions and constant load, then post-fire pull-out tests were performed at different cooling times at lab temperature by increasing the tensile load applied during the heating phase. This experimental study provides a database for future development of post-fire assessment for design of the load-bearing capacity after high temperature exposure. The assessment procedure needs as entry data the thermal calculations during the cooling phase, and the residual bond-strength temperature relationship.

Introduction

In recent years, there has been a growing interest in using anchoring systems in reinforced concrete structures. Thus, anchorage systems for reinforcement applications are classified into two main categories: "Cast-in place rebars" and "post installed rebars (PIRs)". PIRs are very popular in the strengthening of concrete structures in construction projects. They offer a viable method for adding new concrete sections or attaching steel members to existing structures [START_REF] Van Gemert | Force Transfer in Epoxy Bonded Steel/Concrete Joints[END_REF] and provide the flexibility in the construction sequence. According to the bonding agents used for PIR applications, PIRs can be divided into two groups [START_REF] Needham | MICHIGAN DEPARTMENT OF TRANSPORTATION MDOT[END_REF]: "organic PIRs" where the bonding agent is organic such as epoxy, polyester and vinylester mortars, and "grouted rebars" where the bonding agent is inorganic such as cement grouts. In order to compare the mechanical behavior between the various existing anchorage systems, (Spieth et al.) had carried out a series of pull-out tests on cast-in place rebars, organic PIRs bonded with epoxy and polyester mortars and on hybrid PIRs bonded with a combination of vinylester and cementitious compounds. Results showed that the hybrid system had a mechanical behavior closest to a cast-in place rebar. While organic PIRs bonded with epoxy mortar showed a larger bond strength and a much higher stiffness than cast-in-place rebars, the organic PIRs bonded with polyester mortar showed a softer behavior and a significant lower bond strength than all other systems. The load-transfer between the rebar and the concrete in post-installed rebars made with mortars is achieved through shearing along the entire bond length [START_REF] Upadhyaya | Pull-out Capacity of Adhesive Anchors: An Analytical Solution[END_REF]. The mechanical properties of PIR's made with mortar is governed by several parameters such as materials, geometry and installation procedure (Çolak 2007), (Çolak 2001), [START_REF] Bingöl | Residual Bond Strength between Steel Bars and Concrete after Elevated Temperatures[END_REF]. PIRs have high mechanical properties at ambient temperature, however, for the majority of the mortars used in PIRs, when exposed to high temperatures, the bond resistance decreases. The material properties undergo major changes, particularly, the material strength and stiffness change with increasing temperatures. [START_REF] Lahouar | Mechanical Behavior of Adhesive Anchors under High Temperature Exposure_ Experimental Investigation[END_REF] showed that the mechanical properties of PIRs made with organic mortars increase when the bond temperature is up to values below the organic mortar glass transition temperature due to the mortar post-cure phenomenon. Whereas, when temperature exceeds the organic mortar glass transition temperature, a change in the viscoelastic properties of the polymer occurs, which results in creep and high sensitivity to temperature [START_REF] Tavares | Creep Behaviour of FRP-Reinforced Polymer Concrete[END_REF] [START_REF] Elalaoui | Mechanical and Physical Properties of Epoxy Polymer Concrete after Exposure to Temperatures up to 250°C[END_REF]. [START_REF] Pinoteau | Effect of Heating Rate on Bond Failure of Rebars into Concrete Using Polymer Adhesives to Simulate Exposure to Fire[END_REF] studied the influence of the increase of heating rate on bond failure of post-installed rebars made with mortar in concrete using organic mortars, and concluded that a new bond stress distribution is obtained due to the thermal gradient along the steel rebar caused by the increase of the heating rate. Previous pullout tests at high temperature have shown that bond capacity decreases rapidly with temperature [START_REF] Pinoteau | Effect of Heating Rate on Bond Failure of Rebars into Concrete Using Polymer Adhesives to Simulate Exposure to Fire[END_REF], [START_REF] Lahouar | Mechanical Behavior of Adhesive Anchors under High Temperature Exposure_ Experimental Investigation[END_REF]. [START_REF] Al-Mansouri | Influence of Testing Conditions on Thermal Distribution and Resulting Load-Bearing Capacity of Bonded Anchors under Fire[END_REF]) have studied the influence of testing conditions for evaluating anchors in concrete under fire on the evaluation of pull-out strength of bonded anchors. A design method at high temperature was developed allowing to predict the time of collapse of post-installed rebars using thermal calculations and bond resistance variation at different temperatures [START_REF] Pinoteau | Prediction of Failure of a Cantilever-Wall Connection Using Post-Installed Rebars under Thermal Loading[END_REF]) (Pinoteau's method). [START_REF] Lahouar | Fire Design of Post-Installed Bonded Rebars: Full-Scale Validation Test on a 2.94 × 2 × 0.15 M3 Concrete Slab Subjected to ISO 834-1 Fire[END_REF]) also proposed a non-linear shear lag model taking into account the displacement compatibility of PIRs made with organic mortars at high temperature in the design process (Lahouar's shear-lag model). Both approaches yielded accurate predictions of fire resistances. However, scarce are the studies that have been carried out to establish the behavior of PIRs during the cooling phase after exposure to high temperatures.

Post installed rebars may fail in different failure modes under tensile loading: concrete cone failure, steel failure, pull-out failure and splitting failure. This paper focuses on the pull-out failure mode. It presents an experimental study to investigate the bond behavior of PIRs made with organic mortars during cooling phase after high temperature exposure. The experimental protocol was divided into two parts: firstly, fire tests were carried out for exposure of 90 min according to the specifications of (EOTA TR 020 2005), on post-installed rebars made with organic mortars, installed as anchors in reinforced concrete beams (1200 mm × 300 mm × 400 mm) with standard ISO 834-1 fire conditions using a gas furnace at the fire resistance laboratory at CSTB. Then, post-fire pull-out tests were conducted at several cooling times through confined tension, displacement controlled tests in accordance with (TR 048). The aim of these tests is to understand the thermomechanical behavior of PIRs made with organic mortars during the cooling phase and to provide a database for a post-fire design method, based on Pinoteau's Method [START_REF] Pinoteau | Prediction of Failure of a Cantilever-Wall Connection Using Post-Installed Rebars under Thermal Loading[END_REF]. This paper shows the experimental post-fire failure loads, and a comparison between the experimental and calculated bond resistances using Pinoteau's method.

Materials and experimental procedure

Description of test materials

Fire tests were carried out on 6 reinforced uncracked concrete beams of 300 mm of width, 1200 mm of length and 400 mm of thickness. The fire tests were conducted on post installed rebars of 16 mm diameter (GEWI type), using epoxy-based mortar. The PIRs were anchored in concrete with 155 mm (±3mm) embedment depth. The hole was drilled to the required embedment depth with a hammer drill set in rotation-hammer mode with a medium size cutting diameter 𝑑 𝑐𝑢𝑡,𝑚𝑖𝑛 . The composition of the concrete used for the manufacturer of beams is presented in Table 1. Characterization tests were carried out on cubic concrete samples (150 mm × 150 mm × 150 mm) after 29 days of curing under ambient temperature and moisture conditions. The concrete used for casting was a C20/25, it showed a compressive strength equal to 25.8 MPa and a density equal to 2207 kg/m 3 . The ultimate tensile stress value and the yield stress value of the rebars were also determined (fu,test = 670 MPa, fy,test = 577 MPa). The steel failure of the used GEWI rebar occurred at 135 kN.

Description of the test set-up

Fire tests were conducted at the fire resistance laboratory at CSTB according to the specification of (EOTA TR 020, 2005). Two PIRs were installed on one side of each reinforced concrete beam, one of which was mechanically loaded, while the other was equipped with type K thermocouples along the embedment depth to measure the temperature profiles of the PIR at the steel/mortar interface. The PIRs were anchored in the concrete beams with the epoxy based mortar in beams B1 to B6 as in Table 2. The beam was then placed on a gas furnace with PIRs on the fire exposed surface. The fire exposed surface of the beam was 600 mm × 300 mm. The distance between the loaded PIR centered above the furnace and the unloaded PIR was equal to 150 mm. This aimed to replicate the same temperature profiles of the unloaded PIR in the loaded counterpart, where no thermocouples were positioned to avoid influencing the adherence between the mortar and the rebar. During exposure to fire conditions, the PIRs were loaded in tension under a constant load that represents 4,5% of the resistance at ambient temperature for the mortar. Linear Variable Differential Transformer (LVDT) sensors were used to measure the rebar displacement as presented in Figure 1.

The loading system during the heating phase used hydraulic jacks powered by hydraulic pumps, applying a downward mechanical load (presented by F in Figure 2) on a system of metallic frame surrounding the reinforced concrete beam, and connected to the fixture of the post installed rebar inside the furnace. Details of the used fixtures were adopted from (EOTA TR 020 2005). The steel of the loading system was insulated using a ceramic wool based material in order to protect the steel from reaching failure instead of pull-out (bond failure). The same thermal boundary conditions were applied on both loaded and unloaded PIR. The influence of the loading system on temperature profiles and resulting load bearing capacity of bonded anchors in the heating phase were investigated by (Al-Mansouri et al. 2019) (Al-Mansouri et al. 2020) and found negligible.

Afterward, the test specimen was exposed to 90 min of heating under ISO 834-1 fire using the gas furnace. The temperature increase rate being higher while using a gas furnace instead of electrical heating, a thermal gradient along the bond was obtained. The heating time was chosen in a way that the maximum temperatures along the bond would be lower than 300°C. This temperature was selected because most mortars typically provide bond strengths lower than 1 MPa beyond this value according to characterization tests in (« EAD 330087-00-0601 » 2018), due to the loss of adhesion and the carbonization of the mortar that only resists in friction beyond this temperature. In order to obtain a post-fire bond failure, this maximum temperature at the steel/mortar interface was considered in the design procedure of the tests to guarantee that the failure occurs during the cooling phase instead of during the heating phase, and to prevent steel failure in the tests. Afterwards, the test specimen was removed from the oven and left to cool down for several cooling times as presented in Table 2. The next step consisted of conducting the post-fire pull-out tests at the different cooling times with tension loading and confined test setup to prevent concrete cone failure, where the loading was displacement controlled. Figure 1 shows the testing apparatus during heating, where the reinforced concrete beam was placed on the gas furnace, and the testing apparatus (confined tension test) after fire exposure in the cooling phase.

Experimentally obtained temperature profiles

The results of experimentally measured temperature profiles at the steel/mortar interface at the end of the heating phase, and at the time of post fire pull-out tests are shown in Figure 4. Regarding the obtained temperature profiles at the end of the heating phase, steep thermal gradients along the PIRs were observed near the heated surface of concrete beams, while thermal gradients were lower in the inner depths of the specimens. Furthermore, it is shown that almost constant temperatures at the time of postfire tests were observed for the different cooling times after exposure to fire conditions. Figure 5 presents an example of the evolution of the temperature of thermocouples along the PIR vs. time for the PIR embedded in beam B5. The temperature plateau was caused by the water vaporization, which is an endothermic transformation and consumes part of the energy brought by heating. The temperature increased again once all the moisture evaporated, and continued to rise during the cooling phase to a certain level before cooling down to lab temperature. At the time of the post-fire pull-out tests, the temperatures along the bond were quasi-homogeneous.

Comparison between test results and predicted results using Pinoteau's Method

To calculate the evolution of the bearing capacity of PIRs subjected to temperature variation, [START_REF] Pinoteau | Prediction of Failure of a Cantilever-Wall Connection Using Post-Installed Rebars under Thermal Loading[END_REF]) proposed a "bond resistance integration method" using thermal calculations and bond resistance variation at different temperatures. Pinoteau's method was validated by performing a fullscale ISO fire on a cantilever-wall connection using PIRs made with organic mortars. Pinoteau's method was used in the calculated bond resistances in Figure 7. Hence, the resistance profiles are estimated during the heating and cooling phases by using the experimental temperature distribution recorded during the tests and using the bond resistance vs. temperature relationship available only during the heating phase for this mortar assuming both hypotheses: an irreversible and reversible bond strength degradation during the cooling phase (Residual bond strength characterization tests having not been performed at this time). At the section points where no experimental values of temperature were available, temperatures were extrapolated through the depth by a temperature vs. depth curve. The bond stress vs. temperature relationship was obtained from tests according to (« EAD 330087-00-0601 » 2018). Figure 7 shows a comparison between post-fire tests and the outcome of Pinoteau's method for the epoxy-based mortar used in this study. The dashed lines correspond to the calculated resistances during the heating phase up to 90 min, while the continuous lines refer to the calculated resistances during the cooling phase. It is interesting to note that the bond resistances continue to decrease in the first stage of the cooling phase due to the continuous heat diffusion to the cooler parts towards the unexposed surface. It is shown that experimental post-fire pull-out resistances are higher than the calculated resistances. Therefore, for this mortar type and test configuration, Pinoteau's method underestimates the bearing capacity of PIRs during the cooling phase, which justifies the need to characterize more precisely the bond resistance vs. temperature relationship of PIRs during the cooling phase.

In order to benefit from the recovery of the bond in a post-fire design model, more work is needed to study the reversible degradation of organic mortars at high temperatures.

Conclusion

This paper aimed to provide results and preliminary information on the evolution of the load bearing capacity of PIRs made with organic mortars during the cooling phase after exposure to ISO 834-1 standard fire conditions, by conducting post-fire pull-out tests. These tests were conducted on PIRs installed in reinforced concrete beams using an epoxy based mortar. Tests were conducted at different cooling times. The experimental results showed that post-fire pull-out resistance increases with cooling time (23% and more than 50% of the resistance at ambient temperature were respectively obtained at the lowest and highest cooling time). This conclusion can be associated to a probable strength recovery of the epoxy based mortar during the cooling phase.

The comparison between test results and calculated results using Pinoteau's method showed that the latter underestimates the bearing capacity of PIRs during the cooling phase for this mortar type embedded with 155 mm ± 3 mm embedment depth. The variation of temperature profiles during the cooling phase has been shown to have a significant influence on the post-fire resistance of PIRs.

The results of this paper establish the need for additional investigations and research to develop a more rational characterization of the bond resistance vs. temperature relationship of PIRs during the cooling phase as basis for a safe and reliable post-fire design concept.

Figure 1 :

 1 Figure 1: Testing apparatus in the heating phase (Left) and the cooling phase (Right)

Figure 2 :

 2 Figure 2: View of the gas furnace and the loading system during the heating phase

Figure 3 :

 3 Figure 3: Post-fire pull-out normalized resistances at different cooling times

Figure 4 :

 4 Figure 4: Temperatures of thermocouples vs embedment depth

Figure 6 :

 6 Figure 6: Mechanical behavior of PIRs at different cooling times

Figure 7 :

 7 Figure 7: Calculated and Experimental normalized post-fire pull-out resistances of 16 mm PIR with 155 mm ± 3 mm embeddment depth

Table 1 :

 1 Composition of concrete used for casting of beams

Table 2 :

 2 Post fire tests configuration

Acknowledgements

The experimental research presented in this paper was conducted at the fire-resistance laboratory at CSTB (Centre Scientifique et Technique du Bâtiment). The authors would like to acknowledge Mr.

Stéphane Charuel, Mr. Paulo Pangia Ngani, Mr. Francis Diafuanana Luntala, Mr Léo Gontier, Mr Miguel Cruz, Anthony Malara and Mr. Florian Demoulin at CSTB for their contribution to this work.


Sklab Ramdane

Zennir Youcef
email: youcef.zennir@univ-skikda.dz

Pomorski Denis
email: denis.pormorski@univ-lille.fr

NEW APPROACH FOR EARLIER HEAT DETECTION IN INDUSTRIAL FIELD

Keywords: Piston Cylinder Unit (PCU), root mean square (RMS), Distributed Control System. I. PCU FAILURES:

A Piston pump is a type of positive displacement pump in which the high-pressure seal alternates with the piston. Piston pumps are used to move liquids. The pumps can operate over a wide range of pressures and high-pressure operation can be achieved without a strong effect on the flow rate. This type of pump works through a piston and an oscillating mechanism that causes pressure differences. Each movement of the piston releases an equal volume of fluid, which is equivalent to the volume occupied by the piston during its stroke. Piston pumps are often used in scenarios that require high pressure, such as water injection systems in BMS wells. It is known that the amount of energy produced by friction within the PCU should be low and stable, therefore in case of failure, more friction appears and is converted into thermal energy.

The key point here is to detect this temperature change at the earliest moment (in the transition phase) typical of abnormal friction, rather than waiting for the temperature reach a high value. We are faced with two types of overheating dynamics. A very slow one that can last several days, and another fast dynamic that can occur in a few minutes. A new calculation algorithm has been designed and implemented in the DCS that can detect both overheating dynamics. The result has been an early anticipation of typical PCU failures due to overheating with a saving in repair costs of over 50%.

I.1 UNDERSTANDING THE ISSUE:

The water injection pumps in the BMS oil field are very critical in terms of production. Their purpose is to inject water at very high pressure into the reservoir to maintain its pressure and oil production at the desired level. The PCU can be considered as the main part of the horizontal piston water injection pumps. It is built in two parts, one static (Cylinder) and the other moving (Piston). While the pump is running, the plunger slides continuously inside the cylinder liner. Therefore, the PCU will be a place of high friction that can create scratches on the surface of the cylinder liner, due to heat accumulation and induced vibrations. To overcome this drawback, there is continuous lubrication of the contact surfaces along with freshwater cooling of the cylinder. Therefore, both the lubricating oil and the cooling water must be maintained when the pump is in operation to avoid damage. However, many undetected faults, such as clogging or leakage, can occur in both the lube oil and cooling water systems.

In addition, internal parts such as the packing or ring can be damaged, resulting in overheating of the PCUs. According to our estimates, this type of failure more than 70% of the time the pump is damaged. The solution to prevent these problems is to monitor the temperature of each cylinder and stop the pump when it reaches a high value. This remote monitoring system was installed at BMS in August 2018. However, this solution is still unsatisfactory because the pump is triggered only after the PCUs have been running at high temperatures for a certain time, resulting in a pump shutdown with broken PCU internals and high spare parts consumption.

To improve the reliability of this monitoring system, a new approach based on online temperature data processing is applied. The principle is to continuously compare the sensors with each other and at the same time recognize a suspicious sudden change in temperature. This solution is intended to provide an early indication (alarm) of the suspected malfunction Therefore, the pump can be stopped in advance before it operates in severe conditions, regardless of the fundamental causes of the malfunction. After the shutdown, a thorough mechanical overhaul of the PCU can be carried out, which will certainly result in lighter and more economical maintenance work. Before going further in explaining the proposed improvement and for a better understanding, we will explain the details of the current monitoring and control system.

II. THE EXISTING MONOTORING SYSTEM:

At BMS Each pump has got three PCU units Fig. 1, on the top of each cylinder, a temperature sensor (PT100) is inserted and connected to local PLC through temperature transmitter (TT) with 4-20mA loop signal. The PLC perform the raw signal processing and communicate the temperature data to a remote supervision system (DCS) in the control room through Modbus Communication Protocol. The sampling frequency is 1 Hz, meaning that we have for each sensor a recorded value every one second.

When the temperature reaches a value of TAH= 55 ⁰C the DCS will set an alarm message of Temperature Alarm High to operators in the control room. Then, if the temperature continues to increase and hit the value of TAHH= 60 ⁰C (Temperature Alarm High-High), stop command signal is sent automatically from DCS system to electrical substation to power-off both main motor and auxiliaries. This logic of control (interlock) is shown in the diagram of Fig. 2.

Despite the above safeguard interlock, it seems that this solution is very limited for the following reasons. The first is that the set values for the alarm and trigger are too high, the damage is still very significant at the time of the trigger. However, instead of damaging the crankshaft, which can be disastrous, only the PCU is lost. The pump must be stopped much earlier. On the other hand, it is not possible to lower the alarm and trip values without having them overlapping with an ambient temperature that can easily reach 55⁰C during the summer. If we do so, it will lead to many spurious stops ,therefore, if we want to stop the pump properly in advance, we must be able to detect any hidden information in the temperature trends of the cylinder. In doing so, we must consider the extent of the ambient temperature and the slow dynamics of the heating/cooling process.

III. DATA ANALYSIS:

III.1 HEALTHY TRENDS ANALYSIS:

On the other hand, before the incident occurs, we can notice that there is abnormal trivial behavior when we compare the temperatures on the three cylinders. But it is not easy for the operator to keep his eyes on these values all the time trying to deduce any malfunctioning from small changes. The lack of quantitative indicators makes any attempt to recognize malfunction patterns very difficult and continuous monitoring by the system impossible as well.

On the typical trend of three temperature sensors for the healthy running pump. In FIG. 3a &FIG.3.b the daily average values for each healthy PCU have been plotted with an average sampling rate of 6 minutes. The data was collected during both winter and summer 2020 for water injection pumps 1 and 2, respectively. When the PCU is healthy all three sensors have a close value within a small-time span calculated by equation 1 where T1, T2 and T3 are respectively the temperature at the 1st, 2nd, and 3rd PCU.

III.2 THE DISPARITY:

ΔTS is the Disparity and can be caused by many factors, the main one being the transfer of heat from the cylinder to the probe, due to the position of the probe away from the cylinder. On the other hand, the integrity of the wiring can be altered even if the compensation cable is used, introducing a change in the probe resistance due to the high level of vibration. Other sources that may be at the origin of this difference are the quality of the cooling, the accuracy of the calibration and the environmental interferences. Together they make it impossible to obtain the same temperature in all three PCUs. Besides, this disparity can be significant during the start-up transient phase (heating) because when the pump reaches a permanent steady state all values are close together. The low friction at that time creates a very small heat transfer that is almost similar in all three PCUs. This heat transfer is not sufficient to make the measured temperature on the cylinder surface considerably different from the ambient temperature, particularly during summer, 16.800 measuring points were collected from the five pumps during an "assumed" good run-time equivalent to 14 days and used as reference data for the healthy running condition. Statistical analysis of this population has given 1.91⁰C as the mean value of the disparity, with ± 1.02 ⁰C standard deviation, minimum at 0.01 ⁰C and maximum at 9.19 ⁰C. It has been also observed that 99.4% of the disparity values are below 5 ⁰C (16701 out of 16800 points). The disparity was calculated using the equation 1.

The below histogram shows the distribution of the data collected:

III.3 THE FAULT TRENDS ANALYSIS:

A typical PCU failure is shown in Fig. 5 where the temperature was recorded at the PCU of pump 1 from 23 July at 10:00 to 26 July at 23:55. The pump was stopped on July 26th at 15:25 by the operator after it reached a high temperature at PCU No.3 with the disparity of ΔTS = 16⁰C. The trend of ΔTS can be broken down into three phases of overheating. The first phase begins at 46 hours before the pump stopped and the temperature at PCU No.3 is observed to slowly increase and continue to rise on a slight slope for 16 hours until it reaches ΔTS = 9⁰C. This is the transient phase in which, due to the failure, heat is transferred from the inner side of the PCU to the surface of the PCU by conduction. The second phase is constant and lasts 18 hours with a slight decrease in ΔTS due to the heating of the ambient temperature. The last phase is characterized by the rapid growth of ΔTS =16⁰C probably due to the high level of friction caused by the slow degradation of the internal parts of the PCU, the disparity has almost doubled in less than 9 hours. The pump operated under these conditions for 3 and a half hours until it stopped. We were informed that the lack of cooling water was the origin of this problem. The damaged parts were the stuffing box, the packaging, and the bottom ring. This type of failure represents most of the overheating phenomenon related to the gradual degradation of an internal component of the PCU.

Eq.1

The three PCUs may get overheated simultaneously without showing a significant difference between them preventing us to detect any important disparity (less than 6.5⁰C). However, the dynamic of such overheating is very fast regarding the previous slow drift case. Indeed, the temperature can rise by 10⁰C within few minutes as shown above in Fig. 7 As a part of his duty, the operators are checking periodically the temperature values and their disparity to choose whether to stop or to keep running the pump. The operators used to wait until the PCU's temperature reaches high values or disparity between sensors begin to be signed before stopping the pump. This hesitancy can last for many hours and the operator may wait for the advice of process engineer or mechanical engineer to stop the pump. Also, it has been noticed that the disparity grows slowly at the beginning then it rises quickly without reaching alarm limit. If the operator is busy at that time with managing other parts of the process, he will not be able to notice the abrupt change since there is no alarm. Passing that moment, the action is taken to stop the pump comes too late and the casualties can be very high (ea. loss of crankshaft, bearing…). Hence, the ideal situation is to stop the pump properly in advance just at the beginning of the trouble during early phase 1 as shown in Fig. 5 IV

. NEW APPROACH FOR EARLIER HEAT DETECTION:

It is clear after all that has been seen that we are facing two types of overheating dynamics. The first is very slow and can last several days. The other is a fast dynamic and can occur in a few minutes. Hence, we should be able to detect both of them. We can do it by two ways:

1-Enhanced spatial comparison between sensors to detect slow drift.

2-Time-based comparison for each sensor to detect sudden changes.

The new calculation algorithm implemented in the DCS was first tested with real data through simulation and detects both heat dynamics by first making an improved spatial comparison between the sensors to detect slow drift, and by applying a combined temporal drift of all the sensors to detect sudden changes. Both parameters are standardized at 5⁰C based on statistical analysis. All this means that below 100% we are within the normal situation and above 100% temperature growth is detected as abnormal. A pre-alarm was set at 90% to be more conservative, thus providing decision tools that help the operator to decide beyond the simple observation of the disparity between the values of the sensors' temperatures, it should be possible to obtain a more efficient indicator.

IV.1 ENHANCED SPATIAL COMPARAISON TO DETECT SLOW DRIFT:

We need to improve the simple method of observing the Sensor Disparity ΔTS to distinguish the fault independently of the effect of ambient temperature, measurement uncertainty and other disturbances that introduce a baseline deviation with a magnitude close to 15⁰C during the extreme situation, instead of immediately comparing the differences between the temperatures of the PCU and then selecting which is abnormal, we will use a simple and effective formula that gives a single parameter. Thus, the new parameter noted ΔAs will be calculated by the following equation (eq.2). This formula will calculate the root mean square (RMS) of the differences between the minimum temperature value between all PCUs and the temperatures of the other PCUs. The lowest temperature is considered a reference and is assumed to be the most reliable, meaning that there is no abnormal friction in that PCU. The largest interval between the highest temperature PCUs is ΔAs. Simply the extra heat dissipation made by friction due to the failure is represented by the factor ΔAs .Also, to obtain immunity to measurement uncertainty we consider 5⁰C to be the minimum difference between the healthy and the bad PCU and normalize ΔAs to this value. The normalized square root filters out the lower disparity values, while the higher values are emphasized. Consequently, the trend of ΔAs is smoothed out and will only change if there is a significant disparity. In other words, we reduce both unwanted faults and spurious alarms. This method is suitable for tracking the slow dynamics by comparing the temperature of the PCUs that are supposed to be equal, rather than tracking the moving average by collecting a large amount of data over a long period. Furthermore, this method is independent of the fluctuating baseline made by the heating and cooling cycle of the ambient temperature (e.g. day and night, summer, and winter).

%

Eq. 2

IV.2 TIME-BASED COMPARAISON FOR DETECTING SUDDEN CHANGES:

In addition to the above, another parameter that can be applied is the TEMPERATURE TIME DERIVATIVE ΔTt of each PCU considering that in case of failure in one PCU the others may be working well. Unlike ΔAS, which detects a slow fluctuation, ΔTt reflects the rapid change in trend that seems to have sharp edges. After studying the trends of several cases, we have noticed that the most serious damage will occur when there is a sudden change in 5⁰C within a 30-minute interval. Below 5⁰C it will be difficult to distinguish between measurement noise and actual deviation. This abrupt change of temperature in the unhealthy PCU should be normalized to 5⁰C. In the following equation (Eq.3), dT1, dT2 and dT3 are respectively the temperature at the 1st, 2nd, and 3rd PCU recorded in the previous 30 minutes.

The below figure shows an example of the implemented algorithm in the DCS:

V. Conclusion:

A new calculation algorithm has been designed and implemented in DCS that can detect both overheating dynamics. The result has been an early anticipation of typical PCU failures due to overheating with a saving in repair costs of over 50%.

Through this Implementation we have got two new factors for every pump that were combined as following along with minimum difference value criteria to avoid spurious alarm during cold time:

• Threshold for high alarm for both DAs & DTt.

• Combine logic Alarm (DAs + DTt) = Trip.

• Reset manual. % Eq. 3

• Bypass at start up until steady state is reached for 24 HRS to close a full day-cycle. This algorithm will be further improved with new data from the pump sensors.


PASTEURELLA MULTOCIDA EXPERIMENTAL INFECTION 1): RESISTANCE AND HEMATOLOGICAL RESPONSE

Keywords: Pasteurellosis, resistance, hematology, blood cell counts, rabbit

Pasteurellosis is the first cause of female mortality in rabbit farms. During the RELAPA project (Genomics for the Genetic Resistance of Rabbits to Pasteurellosis), 953 rabbits were inoculated at 6 weeks of age with a pyogenic strain of Pasteurella multocida (Pm) and were monitored during 14 days. Disease response was very variable among animals, with 7% of resistant animals and 11% of highly susceptible rabbits. Blood cell counts were performed at day 14 after inoculation on 574 inoculated and 28 control rabbits. Significant differences in white blood cell, red blood cell, and platelet counts were observed according to the disease resistance score. Susceptible rabbits have a lower red blood cell count, probably due to the hemolytic and hemorrhagic activity of Pm. They also have a higher percentage of monocytes, neutrophils and eosinophils (mainly involved in the innate immune system and inflammatory responses) and, conversely, a lower percentage of lymphocytes (mainly involved in the adaptive immune response) compared to highly resistant and control rabbits. They do not seem able to mount an effective immune response to control the infection.

INTRODUCTION

Pasteurellosis is one of the most common bacterial infection in commercial rabbit farms. Pneumonia, caused mainly by Pasteurella multocida (Pm), are a major cause (37.8%) of female mortality on farms [START_REF] Lopez | Etude descriptive des mortalités des femelles reproductrices en élevage cunicole[END_REF]. Genetic selection for resistance to Pasteurellosis is therefore an important goal. Following the collection and characterization of Pm strains (Helloin et al., 2013), the RELAPA project (Genomics for the Genetic Resistance of Rabbits to Pasteurellosis) aims at identifying genomic regions associated with the resistance to Pasteurellosis. This study presents the results of the blood cells count performed after the experimental inoculation of rabbits with a strain of Pm.

MATERIALS AND METHODS

All experiments were conducted in accordance with the guidelines of the directive 2010/63/EU of the European Parliament and of the Council, in the facilities of the Plate-Forme d'Infectiologie Expérimentale: PFIE, UE-1277, INRA Centre Val de Loire, Nouzilly, France. All experimental procedures were approved by the Loire Valley ethical review board (CEEA VdL, committee number 19, N° APAFiS#3866).

Animals

A total of 1030 rabbits were produced Pôle d'expérimentation cunicole toulousain (PECTOUL) by mating 111 dams of the INRA 1777 maternal line and 65 sires of the 6 maternal lines of the 3 French breeders of rabbits (Eurolap, Hycole, Hypharm). Rabbits were produced in 5 batches. They were weaned at 35 days and transported the day after weaning to the Plateforme d'Infectiologie Expérimentale (PFIE, https://doi.org/10.15454/1.5572352821559333e12). A total of 953 inoculated rabbits and 48 controls were kept for this study; 27 rabbits of the inoculation group and 2 rabbits of the control group were excluded from the study due to early mortality not associated with Pasteurellosis. These animals had diarrhea or Epizootic Rabbit Enteropathy (ERE) symptoms without any Pm detected.

Experimental design and measured traits

The animals were housed in cages of five, in two rooms, with a balanced distribution of sexes and paternal and maternal origins. After one week of adaptation, the rabbits were infected at the age of 42 days (D0), by subcutaneous injection between the shoulder blades of a standardized dose of 8,000 bacteria / 0.1 ml saline of the pyrogenic Pm strain CIRMBP-0884 from a stock kept frozen at -80°C and checked for its concentration at each inoculation batch [START_REF] Helloin | Vers une amélioration de la résistance du lapin à la pasteurellose[END_REF]. The health status of the rabbits was monitored daily for 14 days post-inoculation. Critically ill rabbits were euthanized for welfare reasons. The animals were weighed on days 1, 7 and 14. Their body temperature was measured daily from D-1 to D10. With the exception of animals that died or were euthanized during the study, all the rabbits were euthanized at day 14 day after inoculation (56 days of age) and their bodies were examined for signs of pasteurellosis. . At the post mortem examination, the presence and distribution of abscesses were recorded.

Samples

Spleen, lungs, liver and abscess samples were collected for bacteriological analyzes. At the time of slaughter at D14, blood samples were collected during the bleeding after electroconarcosis on a subset of 602 rabbits (574 inoculated rabbits and 28 controls) of batches 2, 3, 4 and 5. Blood cell counts were carried out with the MS9-5 Hematology Counter® (Melet Schloesing Laboratories, France).

Traits and statistical analyzes

Rabbits were scored on the basis of post-mortem examination results for the extent and severity of the abscesses. Another score was given based on the extent of bacterial dissemination in organs [START_REF] Gunia | Premiers résultats du projet RELAPA : génomique pour la résistance génétique des lapins à la pasteurellose[END_REF]. These abscess and bacteriological scores (from 0 to 4) were then combined to create a resistance score (Figure 1). The hematological parameters studied are described in Table 1. White blood cells or leucocytes include lymphocytes, monocytes, neutrophils, eosinophils and basophils. These cells are involved in the inflammation or in the innate immune system. Lymphocytes are a key component of the adaptive immune system, which is more pathogen-specific. Red blood cells transport oxygen and platelets coagulate blood. The hematocrit is the volume percentage of red blood cells in blood. Hemoglobin is a protein found in red blood that carries oxygen. The average values of the hematological parameters were estimated based on the 602 individuals. The relation between hematological characters and resistance score were studied on 601 individuals: 74 rabbits with a score of 1, 425 with a score of 2, 17 with a score of 3, 57 with a score of 4 and 28 controls. The only individual with a resistance score of 0 was excluded from these analyzes. The relationships between the resistance score on the one hand and the hematological parameters on the other hand were analyzed with a linear model (Proc glm of the SAS software).

RESULTS AND DISCUSSION

The proportion of rabbits according to their resistance score is presented in Figure 1 and the average values of hematological parameters in the control and inoculated groups are presented in Table 1. Figure 2 shows the levels of red blood cells, hematocrit, hemoglobin and platelets. The resistant, highly resistant and control rabbits have a significantly higher red blood cell count compared to the susceptible and intermediate animals. Logically, the hematocrit and the hemoglobin concentration follow the same trend. Platelet counts follow the opposite trend, with the highly resistant animals and controls having a lower level than susceptible animals. This can be explained by the hemolytic and hemorrhagic activities of Pm toxins, also observed at post-mortem examination by the petechiae (infiltrations of blood) observed on the internal organs of susceptible animals. As a result, these animals mobilize more platelets to limit blood loss. Figure 3 shows the number of leucocytes and the proportion of the different subsets of leucocytes. The highly resistant animals and the controls have a lower number of leucocytes than the susceptible and very susceptible animals, the resistant animals (score of 3) being intermediate. The proportions of each type of leukocytes and their numbers (not shown here) are significantly different between rabbit groups based on the resistance score. Susceptible animals have more monocytes, neutrophils, eosinophils (involved in the innate immune system).

Monocytes and neutrophils are involved in phagocytosis eosinophils are involved in defense against parasites and some bacterial infections. Neutrophils are contributing to the formation of abscesses in response to local bacterial proliferation. Susceptible animals have fewer lymphocytes (implicated in the adaptive immune system) and basophils (involved in inflammation). It can be deduced that 14 days after inoculation, the most resistant animals would have mounted an effective immune response (innate and perhaps adaptive), which would not be the case of the susceptible rabbits.

CONCLUSIONS

This first step of the RELAPA project shows significantly different hematological profiles between resistant and susceptible animals. Susceptible rabbits have a lower red blood cell count, probably due to the hemolytic and hemorrhagic activity of Pm. They also have a higher percentage of monocytes, neutrophils and eosinophils (involved in the innate immune system and inflammatory responses) and a lower percentage of lymphocytes (involved in the adaptive immune response) compared to highly resistant and control rabbits. They do not seem able to mount an effective immune response to control the infection. This results show a large variability between rabbits in the response to Pasteurellosis infection, which may have a genetic origin.

Figure 1 :

 1 Figure 1: Pasteurellosis resistance score.

Figure 2 :

 2 Figure 2: A. Red blood cells count B. Hematocrit C. Hemoglobin and D. Platelets according to the resistance score from 0 (highly susceptible) to 4 (highly resistant)

Figure 3 :

 3 Figure 3: A. White blood cells and B. Percentage of white blood cells type per resistance score from 0 (highly susceptible) to 4 (highly resistant). LYM=Lymphocytes, MON=Monocytes, NEU=Neutrophils, EOS=Eosinophils, BAS=Basophils.

Table 1 :

 1 Means and standard deviation of the hematological parameters for the inoculated rabbits (total and per resistance score) and for the control group

	Hematological parameter	Unit	Inoculated rabbits Total (n=574)	Resistance scores of the inoculated rabbits 1 (n=74) 2 (n=425) 3 (n=17) 4 (n=57)	Control (n=28)
	Red Blood Cells 10 6 /mm 3	5.00 ± 0.71	4.72 ± 0.86	4.97 ± 0.67	5.46 ± 0.31	5.44 ± 0.67	5.46 ± 0.76
	Hematocrit	%	30.61 ± 4.83	28.56 ± 5.44	30.14 ± 4.33	34.06 ± 3.27	35.69 ± 4.29	35.30 ± 5.12
	Hemoglobin	g/dl	10.52 ± 1.41	10.13 ± 1.58	10.32 ± 1.25	11.66 ± 1.14	12.13 ± 1.22	11.89 ± 1.61
	Lymphocytes	%	32.46 ± 12.82	28.11 ± 9.87	29.31 ± 9.03 45.36 ± 13.48 57.97 ± 8.33	61.34 ± 7.20
	Basophils	%	0.36 ± 0.14	0.34 ± 0.13	0.34 ± 0.12	0.42 ± 0.13	0.49 ± 0.16	0.47 ± 0.14
	Neutrophils	%	52.00 ± 12.80	54.79 ± 11.84 54.86 ± 10.17 42.09 ± 12.60 29.84 ± 7.72	26.56 ± 6.29
	Monocytes	%	9.51 ± 2.47	9.93 ± 2.59	9.74 ± 2.47	8.22 ± 1.64	7.66 ± 1.31	7.19 ± 1.60
	Eosinophils	%	3.23 ± 3.10	4.39 ± 4.26	3.36 ± 2.97	1.44 ± 1.19	1.33 ± 0.68	1,48 ± 0,66
	White Blood Cells	10 3 /mm 3	12.66 ± 6.78	12.99 ± 6.79	13.46 ± 6.84	9.68 ± 5.64	6.96 ± 2.16	6.53 ± 2.52
	Platelets	10 3 /mm 3 333.31 ± 199.98	354.22 ± 190.24	347.65 ± 207.00	273.38 ± 132.89	210.58 ± 107.09	201.02 ± 106.33
		A
				B
		C				D

ACKNOWLEDGEMENTS

The authors thank all participants in the RELAPA project, particularly the teams from the PECTOUL experimental unit, the CIRM-BP microbial resources centre and the PFIE infectiology platform.


N Alsaleh

D Pomorski

M Sebbache

C Lenoir

K Haddadi

WR15 Six-port Interferometric Set-up for Millimeter-wave Characterization in Harsh Environments

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WR15 Six-port Interferometric Set-up for Millimeter-wave Characterization in Harsh Environments N. Alsaleh, D. Pomorski, M. Sebbache, C. Lenoir and K. Haddadi

Abstract-Continuous wave (CW) millimeter-wave radars have gained the interest from industry for accurate distance measurement. In particular, six-port radar (SPR) architecture presents advantages such as high resolution combined with lowpower consumption and low-cost implementation. A WR15 waveguide six-port interferometer is designed and realized for accurate phase measurement in the millimeter-wave regime for harsh environment conditions. This latter is combined with dedicated calibration algorithms to provide measurements performance in terms of sensitivity and accuracy. Experimental results are exemplary shown with mean phase error 2.2 degrees at the test frequency 60 GHz.

Keywords-Six-Port, millimeter-waves, free-space, radar, demodulator IQ.

I SUMMARY

The six-port is a passive linear component, first developed in the 1970s for accurate automated measurements of the complex reflection. Since then, a variety of six-port systems have been demonstrated. Each technology presents own advantages and drawbacks in terms of circuit size, power consumption, fabrication facility, system integration, measurement performance and cost. Therefore, the choice of the technology is mainly driven by the requirements of the targeted application [START_REF] Moldovan | A new 94-GHz six-port collision-avoidance radar sensor[END_REF]- [START_REF] Koelpin | The six-port technology: A low-cost concept for precise position measurements[END_REF]. This work presents a fully WR15 metallic waveguide sixport interferometer acting as an IQ demodulator operating in the frequency range 55-75 GHz for near-field sensing applications, i.e. near-field high precision distance measurement. The circuit is fully calibrated with reference waveguide phase shifter followed by an attenuator as shown in figure 1. The source power is set to 0dbm. As a demonstration, the steps consists in (i) in-situ linearization of the six-port detectors, (ii) interferometric measurements using waveguide phase-shifter.

The first step concerns in the linearization of the detectors of the SPR in order to eliminate the distortion of theirs electrical response (figure 2 (a)). The linearization procedure consists to interpolate the measured data using a polynomial function. The calculated phase is presented in Figure 3 as a function of the measured phase. To validate our approach, this step is first performed without linearizing the detectors and then with. The average error on the calculated phase decreases significantly from 6.01 degrees to 2.2 degrees after the detector linearization step.

These procedures can lead to high accuracy measurements and take into account the imperfections of the system. An extended method for total calibration and system modelling will be presented in the extended version of the paper.

  Figure 1 (a) Schematic of the test platform; (b) Photograph of the test platform

Figure 2

 2 Figure 2 (a) Power in the detector 1 as a function of the voltage; (b) Detected voltage as a function of the phase The next step is to calculate the calibration coefficients by fitting the measured voltage curve shown in Figure (2(b)).The calculated phase is presented in Figure3as a function of the measured phase. To validate our approach, this step is first performed without linearizing the detectors and then with. The average error on the calculated phase decreases significantly from 6.01 degrees to 2.2 degrees after the detector linearization step.These procedures can lead to high accuracy measurements and take into account the imperfections of the system. An extended method for total calibration and system modelling will be presented in the extended version of the paper.

Figure 3

 3 Figure 3 The calculated phases as a function of the measured phases with and without the detector linearization.

II


est destinée au dépôt

Effects of thermophysiology on the evolution of Pseudosuchia (Archosauria) : contributions of paleohistology and isotopic geochemistry using phylogenetic comparative methods

Mathieu Faure-Brac

To cite this version:

Mathieu Faure-Brac. Effects of thermophysiology on the evolution of Pseudosuchia (Archosauria) : contributions of paleohistology and isotopic geochemistry using phylogenetic comparative methods. Paleontology. Sorbonne Université, 2021. English. NNT : 2021SORUS233. tel-03486175v2


Nawal Alsaleh
email: nawal.alsaleh@univ-lille.fr

Clément Lenoir
email: clement.lenoir.etu@univ-lille.fr

Denis Pomorski
email: denis.pomorski@univ-lille.fr

Kamel Haddadi
email: kamel.haddadi@univ-lille.fr

Mohamed Sebbache
email: mohamed.sebbache@univ-lille.fr

Nano-Positioning Test platform for Free-Space Six-Port Interferometric Distance Measurements

Keywords: six-port, millimeter-waves, free-space, radar

Continuous wave (CW) millimeter-wave radars have gained the interest from industry for accurate subwavelength distance measurements. In particular, the six-port radar architecture presents advantages such as high resolution combined with low-power consumption and low-cost implementation in the millimeter-wave regime. In this effort, a new test platform based on fully automated piezo-electric nanopositioning stages that simulates moving targets in XYZ directions with centimeter range combined with nanometer resolution is described. The test platform is crucial to yield performance metrics in terms of repeatability, sensitivity and accuracy. Preliminary experimental results considering a WR15 six-port CW radar designed and realized for harsh environment operation are presented to validate the approach proposed.

I. INTRODUCTION

Precise positioning using millimeter-wave signals has attracted the interest from the research community [START_REF] Koelpin | The six-port in modern society[END_REF]. In particular, six-port radar technology has been identified as an alternative to the conventional heterodyne architecture [START_REF] Haddadi | A 60 GHz Six-Port Distance Measurement System With Sub-Millimeter Accuracy[END_REF]. Generally speaking, the six-port is a passive structure based on the interferometric principle featuring two input ports and four output ports [START_REF] Vinci | A Six-Port Radar System for Precise Distance Measurements and Vibration Monitoring in Industrial Environments[END_REF]. Six-port combines compactness, low energy consumption together with high measurement performance [START_REF] Moscoso-Mártir | Butler matrix based six-port passive junction[END_REF]. A variety of six-port systems have been exemplary demonstrated in metallic guide, substrate integrated waveguide (SIW), planar and monolithic forms. Each technology presents own advantages and drawbacks [START_REF] Tatu | Multiport technology: the new rise of an old concept[END_REF]- [START_REF] Haddadi | A Fully InP Monolithic Integrated Millimeter-Wave Reflectometer[END_REF]. The authors themselves have contributed to the dissemination of the six-port technology in various applications [START_REF] Haddadi | Ultra wide-band fourport reflectometer using only two quadratic detectors[END_REF]- [START_REF] Haddadi | 60-GHz Near-Field Six-Port Microscope Using a Scanning Slit Probe for Subsurface Sensing[END_REF].

The penetration of six-port technology for industrial applications requires dedicated test set-ups to determine intrinsic performance and limitations. In this effort, we use a metallic waveguide six-port interferometer acting as an IQ demodulator operating at 60 GHz. The metallic waveguide technology provides isolation between nearby signals and presents immunity to environmental variations. In particular, we introduce a new test platform for accurate distance measurements. This latter is built up with nano-positioning stages from SmarAct® and a high performance digital scope for six-port voltages acquisition. In section Ⅱ, the experimental test platform and principle of operation are described. Experimental results are summarized in Section III.

II. EXPRIMENTAL TEST PLATFORM

The block diagram of the proposed distance measurement technique is presented in Fig. 1. The millimeter-wave set-up comprises a frequency synthesizer, waveguide six-port IQ demodulator, low noise amplifier, circulator and horn antenna. The system is completed by a piezo-based nano-positioning stage that holds a metallic target (dimensions = 3 .2 × 4.2 cm 2 ).

The six-port IQ demodulator is fed by the frequency synthesizer. The radar function is achieved using a single horn antenna working as transmitter and receiver. To that end, a circulator is included to deliver the received signal by the antenna to the second input port of the six-port IQ demodulator. A low noise amplifier is used to enhance the signal to noise ratio at the signal reception.

The test platform proposed has been fully automated under Labview® environment to set the measurement parameters (RF power, frequency, distance range and step) and to provide detected voltages under different measurement configurations. (Fig. 1). As a demonstration, experiments are considered for 60 GHz near field distance measurement from contact to stand-off set to 5 mm (2 free-space wavelengths). The target is moved along one linear stage in steps of 500 nm over the full range. The input signal is transmitted to the WR15 horn antenna that radiates the signal towards the target. The metal plate then reflects the signal back to the antenna receiving the signal and transmits it to the second input of the six-port radar. To achieve high measurement accuracy, the linearization (interpolation by a polynomial function) of the six-port detectors to eliminate the distortion of their electrical response is required (Fig. 2). To that end, the detected voltages are measured as a function of the input RF power to apply a linearization algorithm. From Fig. 2, we notice that the linearity is degraded by distortions. Consequently, the linearization procedure consists to interpolate the measured data using a polynomial function. In this study, a 5 th order polynomial is used. As an example, the interpolation model for the power 𝑃 is given by: 𝑃 = -1.1265 × 10 𝑉 + 4.8194 × 10 𝑉 -6.4135 × 10 𝑉 + 6.0750 × 10 𝑉 + 1.1082 × 10 𝑉 + 8.5 × 10

In a second step, guided measurements have been performed to yield intrinsic performance of the six-port IQ demodulator.

To that end, a mechanically variable phase-shifter in WR15 technology has been used to control the phase-shift between the LO and RF signals.

where Δ𝜙 = 𝜙 1 -𝜙 2 is the phase shift between the two input LO and RF signals.

The operating frequency is set to 60 GHz and the relative phase-shift (Δ𝜙) is varied from 0 to 360 0 with step of 10 0 . The I and Q components related to the ratio between the LO and RF signals are given by 𝐼 = 10 cos(Δ𝜙)

𝑄 = 10 sin(Δ𝜙)

Fig. 3 shows the detected voltages 𝑉 and 𝑉 as a function of Δ𝜙. The detected voltages present a sinusoidal shape and are in quadrature, in accordance with (2) to (5). Finally, free-space application is considering by moving the target from a distance separation d between the antenna aperture and the planar metallic target between 0 (contact) to 5 mm (two free-space wavelengths at f = 60 GHz). The four detected voltages as a function of the distance d are given in Fig. 4. Qualitatively, a good measurement sensitivity to the distance is noticed. The shapes of the curves are not sinusoidal as the target is located in the vicinity of the antenna, in the near-field. In addition, free-space multiple reflections between the antenna aperture and the target yield to signal distortion. Consequently, analytical modeling of the free-space propagation is needed to accurately extract the distance to the target. Fig. 4(c) presents V3-V4 as a function of V1-V2 that should exhibit graphically a circle centered on 0 for an ideal configuration. An elliptical behavior related to the system imperfections is noticed.

These results are instructive as they demonstrate a good measurement sensitivity with high signal to noise ratio. The proposed experimental set-up does not induce non-systematic errors and other sources of perturbation brought by the operator when the target is moved manually. An analytical model associated to a free-space calibration procedure will be considered in future works to extract the distance from the detected voltages.

III. CONCLUSION

A fully automated test platform dedicated to short distance measurements has been proposed. This latter is based on piezo-electric nano-positioning stages that simulates moving targets within centimeter range and nanometer resolution. Preliminary experiments considering a monostatic six-port radar realized in metallic WR15 technology are promising. Future works will include full modelling for the resolution of the inverse problem, i.e. determination of the distance from the detected voltages.

Fig. 1 .

 1 Fig. 1. Proposed test platform for mm-wave free-space distance measurement.

Fig. 2 .

 2 Fig. 2. Input RF power as a function of the measured voltage V1 and polynomial interpolation.

  The theoretical detected output powers P1 (i = 1,..,4) are given by𝑃 = 𝑏 . 𝑏 * = [𝐴 + 𝐴 + 2𝐴 sin(Δ𝜙)](2) 𝑃 = 𝑏 . 𝑏 * = [𝐴 + 𝐴 -2𝐴 sin(Δ𝜙)] (3) 𝑃 = 𝑏 . 𝑏 * = [𝐴 + 𝐴 + 2𝐴 𝐴 cos(Δ𝜙)] (4) 𝑃 = 𝑏 . 𝑏 * = [𝐴 + 𝐴 -2𝐴 𝐴2 cos(Δ𝜙)]

Fig. 3 .

 3 Fig. 3. Detected voltages of the detectors 1 and 3 as function of the relative phase-shift ΔΦ between the RF and LO signals-f =60 GHz.

Fig. 4 .

 4 Fig. 4. Detected voltages of the detectors 1 and 3 as function of the distance separation between the antenna aperture and a metallic target -f =60 GHz.

ACKNOWLEDGMENT The project is supported by the Nano 2022 Plan in the frame of the common lab IEMN / STMicroelectronics and by the European Metrology Programme for Innovation and Research (EMPIR) Project 18SIB09 Traceability for electrical measurements at millimetre-wave and terahertz frequencies for communications and electronics technologies. The EMPIR Programme is co-financed by the Participating States and from the European Union's Horizon 2020 Research and Innovation Programme.


PASTEURELLA MULTOCIDA EXPERIMENTAL INFECTION (2): GENETIC PARAMETERS

Keywords: Pasteurellosis, resistance, hematology, blood cell counts, rabbit

In this study, we experimentally infected 953 crossbred rabbits from 6 sire lines with Pasteurella multocida, and diagnosed their response to Pasteurellosis. We recorded abscess and bacterial dissemination, growth before and after inoculation, and performed blood cell counts 14 days post inoculation. The heritabilities were low to moderate for all traits, except for the eosinophils percentage, which does not seem to be heritable. There were positive genetic correlations between the Resistance score and the red blood cell count, the hematocrit, hemoglobin and lymphocyte percentages. On the opposite, there were negative genetic correlations between the Resistance score and the platelets, the white blood cells, the neutrophil and monocytes percentages. Among the hematological traits, lymphocyte percentage could be a potential selection criterion to breed for Pasteurellosis resistance. Its heritability was relatively high (0.24 ± 0.09) compared to the other traits and its correlation with the Resistance score was also high (0.83). This is the first analyses of the genetic parameters of hematological traits in experimentally infected rabbits.

INTRODUCTION

Pasteurellosis (Pasteurella infection) is one of the most common bacterial infection in rabbits, in commercial farms and laboratory facilities as well. Curative treatments using antibiotics are only partially efficient, with frequent relapses. Breeding rabbits for improved genetic resistance to Pasteurellosis would be a sustainable complementary approach. The objective of the study was to characterize the genetic variability of traits measured in rabbits experimentally infected with Pasteurella multocida. Such traits were related to the extent of bacterial and abscess dissemination, the growth of rabbits after inoculation, and the blood cell counts performed 14 days after inoculation. We also investigated the genetic correlation with the trait under selection in the commercial population.

MATERIALS AND METHODS Animals

The experimental trial is described in details in the companion paper [START_REF] Gunia | Pasteurella multocida experimental infection (1): resistance and hematological response[END_REF]. Briefly, the experimental population includes 1001 crossbred rabbits: 48 controls and 953 inoculated. The 953 rabbits were inoculated with Pasteurella multocida and their response to the infection was studied for 14 days. Blood cell counts were performed on blood samples taken at the time of slaughter at day 14 post inoculation. The experimental crossbred animals were issued from sires of the 6 maternal lines of the 3 French rabbit breeders (Eurolap, Hycole, Hypharm).

World Rabbit Science Association 12th World Rabbit Congress -November 3-5 2021 -Nantes, France, Communication BG-09, 4 pp.

2

In addition, we studied production records in the selection populations. These selection populations include the purebred progenies of the sires used to produce the experimental population. The purebred progenies were raised in the facilities of the 3 breeding companies. Information on 11,971 purebred rabbits of 6 lines born in 2016 and 2017 was available.

Traits

On the experimental crossbred population, the average daily weight gain from birth to weaning (ADG-BW) was measured before inoculation. After inoculation, we measured the following traits (Pasteurellosis resistance traits): Average daily weight gain during the first (ADG-PI1) or the second (ADG-PI2) week post inoculation, Abscess, Bacteria and Resistance scores. These scores (0 to 5) were given according to the extent of lesion and bacterial dissemination in the body. Resistance is a composite score taking into account survival, Abscess and Bacteria scores. The hematological traits were Red Blood Cells (RBC), White Blood Cells (WBC), Platelets (PLT) counts, the Hematocrit (HCT), Hemoglobin (HGB), and the percentages of Lymphocytes (LYM), Basophils (BAS), Neutrophils (NEU), Monocytes (MON), and Eosinophils (EOS). In this paper about Pasteurellosis resistance and hematological traits, we only took into account the traits measured on the inoculated rabbits. Records taken on the control group were not included in the analyses. On the purebred selection population, we considered the two main traits under selection across all the 6 lines, which are the number of kits born alive (NBA) and the weaning weight (WW).

Statistical Analysis

The data were analyzed using Reml method with ASReml 3.0 linear mixed animal model. For more details see the paper of [START_REF] Shrestha | Estimation of Genetic Parameters of Pasteurellosis Resistance in Crossbred Rabbits[END_REF]. Heritabilities were estimated with a linear model using three trait analyses. These three traits analyses always included the two selection traits. Genetic and phenotypic correlations were estimated by including randomly two to four traits together.

RESULTS AND DISCUSSION

The heritability of the hematological traits of the infected rabbits are presented in Table 1. The highest heritabilities was observed for the percentages of monocytes and lymphocytes. The heritability of the red blood cell traits (red blood cell count, hematocrit, hemoglobin) was not significantly different from zero. The heritability of the percentage of basophils was also not significantly different from zero and the percentage of eosinophils was not heritable. The platelet count was moderately heritable. The heritability of the disease resistance and production traits are presented in Table 2. They were in the same range as the heritability of the hematological traits. The correlations among hematological traits are presented in Table 3. We observed two groups of traits with positive correlations within the group and negative correlations with the traits of the other group. One group included the red blood cells traits (red blood cells, hematocrit and hemoglobin) and percentage of lymphocytes. The other group included white blood cells, platelets percentage of neutrophils and monocytes. No clear trend was observed for percentage of basophils. The Table 4 shows the genetic correlation between the hematological traits and the Pasteurellosis resistance or production traits. The correlations were moderate to high, however, only a limited number of correlations were significantly different from zero. The correlations were in accordance with the phenotypes observed in the first paper [START_REF] Gunia | Pasteurella multocida experimental infection (1): resistance and hematological response[END_REF]. Resistant rabbits tend to have higher red blood cells, hematocrit, hemoglobin and percentage of lymphocytes. They also had lower white blood cells, platelets, percentage of neutrophils and monocytes. Red blood cells, hematocrit, hemoglobin and percentage of lymphocytes had a positive genetic correlation with Resistance, average daily gain pre and post inoculation, and lower with Abscess and Bacteria. White blood cells, neutrophils, monocytes, and platelets showed the opposite trend. The genetic correlations between the hematological traits and the two selection traits were not significantly different from zero, probably due to a lake of power of our study. They tend to be mostly positive with weaning weight (except for white blood cells, hematocrit, and platelets) and mostly negative with the number of kits born alive (except for neutrophils). Percentages of Lymphocytes and Neutrophils were the two traits with the highest correlations with the other disease resistance traits. They seem to be the strongest indicators of resistance or sensitivity to Pasteurelllosis. Neutrophils are involved in abscess formation. The high response for neutrophils could be explained by the choice of a virulent Pasteurella multocida strain that causes abscesses in rabbits [START_REF] Helloin | Vers une amélioration de la résistance du lapin à la pasteurellose[END_REF]. Lymphocytes are a key component of the adaptive immune response. Due to its higher heritability and genetic correlation with Resistance, the lymphocyte percentage could be an interesting selection criterion to breed rabbits for improved Pasteurellosis resistance. Further studies are needed to analyze the response in the lymphocyte sub-populations. The genetic correlations were stronger between the hematological traits and Abscess or the Average Daily Gain during the 2 nd week post inoculation than with the other traits. This could be explained by the fact that these traits directly reflect the efficiency of the immune response, directly for Abscess and indirectly for ADG2. -0.12 1 Hematological traits: RBC=Red Blood Cells, HCT=Hematocrit, HGB=Hemoglobin, LYM=Lymphocytes, BAS=Basophils, NEU=Neutrophils, MON=Monocytes, WBC=White Blood Cells, PLT=Platelets 2 Pasteurellosis resistance traits: abscess, bacteria and resistance score, ADG1 and ADG2=Average Daily Gain the 1st and 2nd week post inoculation 3 Production traits: ADGBW=Average Daily Gain before weaning, WW=Weaning weight and NBA=Number of kits Born Alive Bold: correlations significantly different from zero.

CONCLUSIONS

There was substantial genetic variation in the response to Pasteurella multocida infection. The heritability of traits related to white blood cells measured post infection were all significantly different from zero, with the exception of the percentage of eosinophils. On the opposite, heritability of the traits related to red blood cells were not significantly different from zero. The lymphocytes and neutrophils percentage were highly genetically correlated with the resistance or sensitivity to Pasteurellosis.

Table 1 :

 1 Heritability of the hematological traits 1 measured on 574 experimentally infected crossbred rabbits

	Trait	Heritability (SE)	Common litter effect (SE)
	RBC	0.04 ± 0.06
	HCT	0.07 ± 0.07
	HGB	0.14 ± 0.08
	LYM	0.24 ± 0.09
	BAS	0.07 ± 0.06
	NEU	0.18 ± 0.08
	MON	0.30 ± 0.06	0.08 ± 0.06
	EOS	0.00 ± 0.00
	WBC	0.17 ± 0.08
	PLT	0.19 ± 0.08
	1 RBC=Red Blood Cells, HCT=Hematocrit, HGB=Hemoglobin, LYM=% Lymphocytes, BAS=% Basophils, NEU=%
	Neutrophils, MON=% Monocytes, EOS= % Eosinophils, WBC=White Blood Cells, PLT=Platelets.

Table 2 :

 2 Heritability of disease resistance traits and production traits 1 Average daily weight gain; BW: from birth to weaning pre-inoculation; PI1: during first week post-inoculation; PI2: during second week post-inoculation: NBA: number of kits born alive: WW: weaning weight. 2 Permanent environment effect for NBA, Common litter effect for Abscess, ADG-BW, and WW.

	Type of traits	Trait	Population	Number of rabbits	Heritability (SE)	Environmental effect (SE) 2
		Abscess		951	0.13 ± 0.07	0.07 ± 0.04
	Pasteurellosis resistance	Bacteria Resistance ADG-PI1 ADG-PI2	Experimental Experimental	951 953 902 852	0.08 ± 0.05 0.16 ± 0.06 0.29 ± 0.07 0.20 ± 0.06
		ADG-BW	Experimental	980	0.11 ± 0.10	0.47 ± 0.05
	Production	NBA	Selection	2,253	0.33 ± 0.06	0.10 ± 0.02
		WW	Selection	11,423	0.05 ± 0.02	0.23 ± 0.02
	1 ADG:

Table 3 :

 3 Genetic (above diagonal) and phenotypic (below diagonal) correlations 1 among hematological traits 2 RBC=Red Blood Cells, HCT=Hematocrit, HGB=Hemoglobin, LYM=% Lymphocytes, BAS=% Basophils, NEU=% Neutrophils, MON=% Monocytes, EOS= % Eosinophils, WBC=White Blood Cells, PLT=Platelets.

		RBC	HCT	HGB	LYM	BAS	NEU	MON	WBC	PLT
	RBC		0.67	0.87	0.50	0.00	-0.02	-0.89	-0.85	-0.39
	HCT	0.98		0.98	0.62	-0.63	-0.44	-0.98	-0.84	-0.80
	HGB	0.88	0.91		0.51	-0.58	-0.38	-0.91	-0.77	-0.58
	LYM	0.18	0.26	0.24		0.57	-0.96	-0.69	-0.61	-0.60
	BAS	0	0.05	0.01	0.43		-0.72	0.39	-0.19	-0.63
	NEU	-0.03	-0.11	-0.08	-0.95	-0.49		0.40	0.54	0.67
	MON	-0.25	-0.3	-0.42	-0.18	0.20	-0.02		0.51	0.38
	WBC	0.05	-0.03	0	-0.67	-0.25	0.64	0.06		0.76
	PLT	0.05	0	-0.06	-0.44	-0.20	0.44	0.17	0.49
	1 Bold: correlations significantly different from zero.

1

Table 4 :

 4 Genetic correlations between hematological traits 1 and Pasteurellosis resistance traits 2 or production traits 3

		ABSCESS BACTERIA	RESISTAN CE	ADG1	ADG2	ADGBW	WW	NBA
	RBC	-0.42	0.21	0.33	0.43	0.74	0.73	0.02	-0.89
	HCT	-0.62	-0.28	0.54	0.50	0.79	0.87	-0.06	-0.49
	HGB	-0.55	-0.32	0.47	0.34	0.72	0.99	0.18	-0.40
	LYM	-0.95	-0.21	0.83	0.44	0.84	0.24	0.14	-0.39
	BAS	-0.43	-0.38	0.27	0.39	0.35	-0.60	0.03	-0.12
	NEU	0.89	0.91	-0.76	-0.71	-0.73	-0.87	0.36	0.42
	MON	0.65	0.57	-0.47	-0.29	-0.54	-0.75	0.26	-0.45
	WBC	0.50	0.59	-0.40	-0.29	-0.84	-0.90	-0.32	-0.07
	PLT	0.61	0.52	-0.43	-0.14	-0.96	-0.25	-0.13

ACKNOWLEDGEMENTS

The authors thank all participants in the RELAPA project, particularly the teams from the PECTOUL experimental unit, the CIRM-BP microbial resources Center and the PFIE infectiology platform (PFIE, https://doi.org/10.15454/1.5572352821559333e12).