Ryma Benrabah

Zaki El Sayah

Pierre-Alexandre Glaude

Philippe Arnoux

Rene Fournet

Baptiste Sirjean
email: baptiste.sirjean@univ-lorraine.fr

Quantification of hydroperoxides in liquid fuels: a systematic comparison of titrations and absorption methods and their coupling to HPLC

Keywords: hydroperoxides, HPLC, autoxidation, surrogate fuel

Hydroperoxides are major products in the autoxidation of fuels and play a central role in oxidation kinetics.

Their presence affects the oxidation rate, even at low concentrations, and, in turn, the thermal stability of fuels. Standard techniques for the quantification of hydroperoxides (ROOH) in fuels involve the reduction of ROOH by I -, yielding iodine (I 2 ), which can be quantified by titration. The ASTM titration method of ROOH is known to be poorly reproducible and have inadequate lower detection limits and limited dynamic ranges. In this work, several analytical methods for the quantification of hydroperoxides in fuels have been systematically compared for known concentrations of ROOH: titrations of iodine with thiosulfate (ASTM D3703) and triphenylphosphine (TPP) solutions with colorimetric and potentiometric methods and quantification of iodine by UV-visible absorption. n-decane was used as a surrogate fuel and tert-butyl hydroperoxide as the ROOH internal standard. Our systematic study shows that the ASTM method based on colorimetric titration using thiosulfate aqueous solution is the least accurate because of the non-miscibility of water and n-decane, which even makes the UV-visible spectroscopy method ineffective. The other titration method proposed in the literature, using TPP dissolved in n-decane as the titrant does not have this miscibility problem. Potentiometric titration is found to be more reproducible and accurate than colorimetric titration. The UV-visible absorption reaches lower detection limits. We show that the combination of the potentiometric titration of iodine with TPP and UV-visible absorption enables ROOH concentrations to be determined with low detection limits and a large dynamic range. The advantages of iodometry and UV-absorption detection methods have been used to develop a new analytical method based on their coupling in HPLC with a post-column reactor.

Introduction

The oxidation stability of fuels is a key factor for their use in the transport sector [START_REF] Pradelle | Gum Formation in Gasoline and Its Blends: A Review[END_REF][START_REF] Bacha | Oxidation Stability of Diesel/Biodiesel Fuels Measured by a PetroOxy Device and Characterization of Oxidation Products[END_REF][START_REF] Chatelain | Wide Range Experimental and Kinetic Modeling Study of Chain Length Impact on n-Alkanes Autoxidation[END_REF]. Throughout their life cycle, fuels are in contact with air and are subject to significant variations in temperature and pressure. For example, jet fuels can be subject to temperatures up to 150°C because of their use as aircraft coolant [START_REF] Hazlett | Thermal Oxidation Stability of Aviation Turbine Fuels[END_REF]. High temperature or pressure conditions favor the liquid phase oxidation of the fuel, also named autoxidation, and this phenomenon is known to change the chemical and physical properties of the fuels (composition, viscosity, freezing point, …) and ultimately leads to the formation of gum and deposits [START_REF] Chatelain | Wide Range Experimental and Kinetic Modeling Study of Chain Length Impact on n-Alkanes Autoxidation[END_REF][START_REF] Alborzi | Comparative Study of the Effect of Fuel Deoxygenation and Polar Species Removal on Jet Fuel Surface Deposition[END_REF][START_REF] Aminane | Experimental study of the kinetics of degradation of ndodecane under thermo-oxidative stress at low temperature and mechanism inferred[END_REF][START_REF] Zabarnick | Studies of the Impact of Fuel Deoxygenation on the Formation of Autoxidative Deposits[END_REF]. The fuel autoxidation therefore negatively affects engine operation in terms of efficiency, pollutants and safety. So, it is crucial for the fuels to be oxidatively stable through time. The determination of the oxidation stability of a given fuel can be quantified by numerous physical and chemical criteria: induction period of the fuel, the quantity of gum deposit, or the conductivity of gums [START_REF] Dewitt | Effect of Aromatics on the Thermal-Oxidative Stability of Synthetic Paraffinic Kerosene[END_REF][START_REF] Bär | Rancimat vs. rapid small scale oxidation test (RSSOT) correlation analysis, based on a comprehensive study of literature[END_REF]. The main measurable chemical quantity that can be linked to the oxidation stability of fuels is the total amount of hydroperoxides [START_REF] Le | An experimental and detailed kinetic modeling of the thermal oxidation stability of n-decane as a jet fuel surrogate component[END_REF][START_REF] Morris | AN IMPROVED METHOD FOR MEASURING HYDROPEROXIDES IN FUEL USING POTENTIOMETRY AND ALTERNATIVES TO CHLOROFLUOROCARBON SOLVENTS[END_REF].

Hydroperoxides (ROOH) are highly reactive species that accelerate the autoxidation of hydrocarbon fuels [START_REF] Le | Development of a Detailed Kinetic Model for the Oxidation of n-Butane in the Liquid Phase[END_REF][START_REF] Denisov | Oxidation and antioxidants in organic chemistry and biology[END_REF]. They are the main autoxidation products of hydrocarbons, up to relatively high extent and are produced by the radical chain mechanism that governs the conversion of the fuel:

RH + O 2  R• + HO 2 • (1) R• + O 2  ROO• (2) RH + ROO•  R• + ROOH ( 3
)
ROOH decomposition is the branching reaction of fuel autoxidation:

ROOH  RO• + •OH (4)
and is the most sensitive reaction playing a role on the hydrocarbon fuel conversion [START_REF] Le | An experimental and detailed kinetic modeling of the thermal oxidation stability of n-decane as a jet fuel surrogate component[END_REF][START_REF] Chatelain | Structure-Reactivity Relationships in Fuel Stability: Experimental and Kinetic Modeling Study of Isoparaffin Autoxidation[END_REF][START_REF] Zabarnick | Chemical kinetic modeling of jet fuel autoxidation and antioxidant chemistry[END_REF].

Hydroperoxides therefore favor the oxidation of the liquid fuels and are at the origin of gums and deposit formation. They are also known to impair the quality of O-rings and hoses used in the fuel systems [START_REF] Watkins | Hydroperoxide formation and reactivity in jet fuels[END_REF] and adversely affects Research and Motor Octane Numbers and Cetane Number [START_REF] Nadkarni | Guide to ASTM test methods for the analysis of petroleum products and lubricants[END_REF].

The quantification of these oxygenated products is therefore of primary importance. An ASTM standard is used to determine the ROOH content in gasoline, diesel and aviation fuels (ASTM D3703).

In this standard test, the total hydroperoxide content is determined by iodometry and colorimetric titration. The first step in this method is the reduction of ROOH with iodide ions from potassium iodide in absolute ethanol, in the presence of acetic acid. This reaction produces a yellowish solution of I 2 according to the following equation:

ROOH (decane) + 2H + (organic) + 2I - (organic) → I 2 (organic) + ROH (organic) + H 2 O (5)
Then, the ASTM D3703 method uses thiosulfates in an aqueous medium as the titrant, that reacts with I 2 , according to:

I 2 (organic) + 2 S 2 O 3 2- (aq) → S 4 O 6 2- (aq) + 2 I - (aq) (6)
The titration endpoint is determined by the color change of the solution. However, this titration in aqueous phase is known to be poorly reproducible and have inadequate lower detection limits and limited dynamic ranges [START_REF] West | Determination of Hydroperoxides in Jet Fuel via Reaction with Triphenylphosphine[END_REF]. Many works have been performed to determine new methods to better quantify hydroperoxides, and these approaches are mainly based on reduction of ROOH with iodide ions or triphenylphosphine.

West et al. [START_REF] West | Determination of Hydroperoxides in Jet Fuel via Reaction with Triphenylphosphine[END_REF] developed a method to quantify hydroperoxides in jet fuels based on the oxidation of triphenylphosphine (TPP) by ROOH:

ROOH + TPP excess = ROH + TPPO [START_REF] Zabarnick | Studies of the Impact of Fuel Deoxygenation on the Formation of Autoxidative Deposits[END_REF] TPP will react with ROOH through equation ( 7) and the TPPO reaction product will be quantified by gas chromatography (GC) with a flame ionization detection (FID). Prior studies that used the measurement of TPPO only measured peroxide concentrations that were rather high (>1 mmol/L), and they excluded measurements in jet fuel matrices [START_REF] Perkel | Application of Triphenylphosphine to the Gas Chromatographic Determination of Peroxides in the Oxidation Products of Organic Compounds[END_REF]. West et al. [START_REF] West | Determination of Hydroperoxides in Jet Fuel via Reaction with Triphenylphosphine[END_REF] showed that their method only requires a little amount of fuel (0.5 mL) diluted in toluene, has an extremely low detection limit (0.002 mmol/L), a large dynamic range, and is accurate and repeatable. Their work also identified the alcohol produced in [START_REF] Zabarnick | Studies of the Impact of Fuel Deoxygenation on the Formation of Autoxidative Deposits[END_REF], allowing the identification of the original hydroperoxide.

Recently, Roohi and Rajabi [START_REF] Roohi | Iodometric Determination of Hydroperoxides in Hydrocarbon Autoxidation Reactions Using Triphenylphosphine Solution as a Titrant: A New Protocol[END_REF] proposed a water-free iodometric method, based on a visual change of the color to find the titration endpoint. Triphenylphosphine (TPP) in n-decane solvent is used as the titrant for the I 2 produced from the reaction of ROOH with iodide ions I -in an acidic organic medium. In the first step, ROOH is reduced with iodide ions (KI in absolute ethanol with acetic acid)

to produce a yellow-reddish solution as presented in equation ( 5).

For the reaction (5) to be complete, the solution must be heated at 68°C for 15 minutes. Then, TPP in n-decane is used for the titration of I 2 , producing an uncolored complex [TPPI] + [I] -as shown in equation [START_REF] Dewitt | Effect of Aromatics on the Thermal-Oxidative Stability of Synthetic Paraffinic Kerosene[END_REF].

I 2(organic) + TPP (decane) → [TPP] + [I] - (organic) (8)
As seen in equations ( 5) and ( 8), the iodine concentration can be determined from the quantity of TPP added and the endpoint of titration is found when the mixture turns transparent. The method proposed by Roohi and Rajabi [START_REF] Roohi | Iodometric Determination of Hydroperoxides in Hydrocarbon Autoxidation Reactions Using Triphenylphosphine Solution as a Titrant: A New Protocol[END_REF] is based on colorimetry but we showed that the titration endpoint can also be found using potentiometry [START_REF] Le | An experimental and detailed kinetic modeling of the thermal oxidation stability of n-decane as a jet fuel surrogate component[END_REF][START_REF] El-Sayah | Comparison of the Effects of Different Biofuels on the Oxidation Stability of a Hydrocarbon Fuel[END_REF]. The authors reported a ROOH determination error of 4% with their method but did not report detection limits. The lowest concentration mentioned is 0.3 wt % of 1-phenyl ethyl hydroperoxide (PEHP) in ethylbenzene ([PEHP] ≈ 6 × 10 -3 mol/L).

Longobardi et al. [START_REF] Longobardi | Analysis of peroxide value in olive oils with an easy and green method[END_REF] recently used a spectrophotometric method combined with iodometry to analyze the peroxide value in olive oils. Their method is based on the addition of HCl-ethanol and a KI solution (reaction 5) and the measurement of the absorbance of triiodide ions (reaction 9) at 350 nm.

I 2 + I -⇌ I 3 - (9)
They establish a calibration curve using tert-butylhydroperoxide from 1 to 10 m eq O 2 /kg (approximatively 4.57 × 10 -4 to 4.57 × 10 -3 mol/L), with a limit of detection of 0.3 m eq O 2 /kg (approximatively 1.37 × 10 -4 mol/L).

Cullis et al. [START_REF] Cullis | The oxidation of decane in the liquid and gaseous phases[END_REF] determined ROOH concentration using a system based on the work of Deedler et al.

[24], using liquid chromatography with a post column reactor, where the iodometric reaction takes place. Normal phase HPLC is used and coupled to the post column reactor fed with the necessary reactants for the reduction of ROOH by I -(reaction 5): sodium iodide in a mixture of iso-propanol, acetic acid and water. The absorbance of I 3 -(reaction 9) is measured at 362 nm. The post column reactor placed after the HPLC was shown to be fast and precise for the quantification of hydroperoxides. It was found to detect concentrations of decane hydroperoxides as low as 0.1 µg/L in n-decane (≈ 5.7 ×10 -10 mol/L). Their study demonstrates that the loss of resolution in chromatograms can be reduced to an acceptable level by a careful design of the post column reaction system.

In this work, we propose a new systematic comparison of different methods of the literature for the quantification of the total hydroperoxide content in an alkane fuel. Iodometric titration methods (ASTM D3703 and TPP) with colorimetric and potentiometric detections of the endpoint are performed. The method based on the UV-vis absorbance of triiodide ions from reactions (5) and ( 9) is also explored for the first time in the literature and compared to iodometric titration approaches.

The main purposes of this study are: (1) to provide experimental data on the reproducibility of the different existent methods, (2) to determine the detection range of each technique, and (3) to develop a method in HPLC, with a post-column reactor and determine its detection and quantification ranges. The surrogate jet fuel used in this work is n-decane [START_REF] Le | An experimental and detailed kinetic modeling of the thermal oxidation stability of n-decane as a jet fuel surrogate component[END_REF] and the hydroperoxide standard is tert-butyl hydroperoxide (TBHP).

I. Experimental methods

Reagents

Potassium iodide (KI), anhydrous, sodium thiosulfate (Na 2 S 2 O 3 ; 0.1 N in aqueous solution), and absolute ethanol were purchased from VWR Chemicals. Butylated hydroxytoluene (BHT) (≥ 99 %), sodium iodide (NaI) (>99%), triphenylphosphine (TPP Reagent plus® 99 %), acetic acid (≥ 99.8 %),

tert-butyl hydroperoxide in n-decane (TBHP / C 10 ; 5-6 mol/L) 2,2,4-trimethylpentane (isooctane; ≥ 99.5 %) were purchased from Sigma Aldrich. n-Decane was purchased from Acros Chemicals. To evaluate the performance of the different analytical methods, TBHP/n-decane solutions were prepared with decreasing concentrations of TBHP obtained by dilutions. The most diluted solutions (10 -6 -10 -9 mol/L) were prepared using the AOC-6000 autosampler of Shimadzu and the dilutions for less diluted concentration (10 -2 -10 -5 mol/L) were done with micropipette.

Preparation of the solution

The first solution used for all of the titrations and the UV-vis spectroscopy was prepared using the protocol from Roohi and Rajabi [START_REF] Le | Development of a Detailed Kinetic Model for the Oxidation of n-Butane in the Liquid Phase[END_REF]: 0.5 g of KI (in excess) and 0.5 mL of acetic acid in 30 mL of absolute ethanol were heated for 5 min in medium agitation (400 rpm) to 68°C. Then, a 1 mL sample of TBHP/n-decane blend of known concentration was added and heated at 68°C, at the same agitation rate, for 15 min to ensure that reaction (5) was complete. The solution was kept warm during the subsequent manipulations.

Colorimetric titration

A usual colorimetric dispositive for titration was used. When TPP is the titrant, a 25 mL burette filled with a 0.08 mol/L solution of 2.1g of TPP and 0.01g of BHT in 100mL of n-decane is used to titrate iodine and the endpoint of titration was determined when the solution became transparent. When Na 2 S 2 O 3 (0.025 mol/L) aqueous solution was the titrant (ASTM D3703), the titration endpoint is also reached when the solution becomes transparent. Each experiment was repeated twice.

Potentiometry

An automated potentiometric titrator (Mettler Toledo G10S Compact Potentiometric Titrator) was used, equipped with a Pt indicator electrode vs. an AgCl / Ag reference electrode was used. For the analysis, the TBHP/I -/C 10 solution was put in the cell stirred at 20% and two titrants were used: TPP (0.08; 8.0 × 10 -3 ; 8.0 × 10 -4 ; 8.0 × 10 -5 mol/L) in n-decane and Na 2 S 2 O 3 (0.025 mol/L) in water. Each experiment was repeated 3 times

UV-visible spectroscopy

An alternative to the titration of iodine is to measure the absorbance of the solution formed in equation ( 5). Indeed, the color is due to the formation of triiodide I 3 -in the presence of I 2 and I -in the same solution (reaction 9). In absolute ethanol, triiodide has one of its maximal absorbances at a wavelength of 362 nm.

The absorbance depends on the dilution factor of the solution [START_REF] Stein | Spectrophotometric Hydroperoxide Determination by the Use of Triphenylphosphine[END_REF]. The Beer-Lambert law is used to link the absorbance of I 2 and its concentration:

A = ε l C (10)
A: absorbance of the solution at 362 nm ɛ: molar extinction coefficient of I 2 (cm -1 L mol -1 ) l: optical length of quartz spectroscopy cell (cm) C: concentration of I 2 (mol L -1 )

A sensitive UV-visible double beam spectrophotometer UV-3600 Shimadzu was used to determine the amount of hydroperoxides in the TBHP/C 10 solutions. The absorbance of triiodide formed by the reduction of peroxides and the reaction of I 2 with excess iodide ions was measured at 362 nm for the sample essay [START_REF] Kireev | Study of molecular iodine, iodate ions, iodide ions, and triiodide ions solutions absorption in the UV and visible light spectral bands[END_REF]. Measurements were done in a 1 mL quartz cell and the cell dimensions were 10x10x40 mm.

High Performance Liquid Chromatography (HPLC)

An HPLC (high-performance liquid chromatography) device combining a separation column in the normal phase (silica) and a post-column reactor (P-cR) was adapted from the work of Cullis et al. [START_REF] Cullis | The oxidation of decane in the liquid and gaseous phases[END_REF].

A HPLC Shimadzu Nexera XR was used at a flow of 1 mL per minute of solvent (isooctane: absolute ethanol / 95:5). 10 µL of the sample TBHP/C 10 was injected using an autosampler through the separative column. This separative column separates oxygenated products thanks to their polarity. At the exit of this column, the fractions were mixed with a 10% acetic acid in absolute ethanol (0.2 mL/min) and a 12.5 g/L solution of NaI in absolute ethanol (0.2 mL/min). The change of iodide salt is due to the ability of KI to obstruct the microfluidic in the HPLC device. This mixture passed through a reactive column packed with 30 µm glass beads, heated at 68°C, with a corresponding residence time of 90 seconds [START_REF] Cullis | The oxidation of decane in the liquid and gaseous phases[END_REF]. This residence time was verified by passing toluene, throughout the system with and without the post column reactor.

II. Results

The colorimetric method, using two different titrants, is compared to the potentiometric method, as well as UV-spectrophotometric measurement and HPLC coupled to a P-cR using a PDA detector is also used.

Colorimetric titration

TBHP concentrations were measured by the colorimetric method with two titrants: a solution of TPP in n-decane and a solution of sodium thiosulfate in the aqueous phase. Figure 2 Sigma-Aldrich indicates that the concentration of TBHP in n-decane (our stock solution) ranges between 5 and 6 mol/L. It is worth noting that their measure of the TBHP concentration is performed using the thiosulfate and colorimetric method. The theorical data used here are assumed to be the dilution of a 5.5 mol/L stock solution.

A B A

Figure 2 shows that with Na 2 S 2 O 3, the data are scattered with a low correlation coefficient and a deviation in the parity plot (y = 1.13x), while with the TPP titrant, the correlation coefficient is near 1 and the results are close to parity between theoretical and measured values. Using TPP titrant, we observed that the data are well reproducible up 6.0 × 10 -2 mol/L. The detection of the titration endpoint with the colorimetric method quantifies hydroperoxides for concentrations as low as 6.0 × 10 -2 mol/L. For more diluted concentrations, the change of color at the endpoint was no longer visually detectable. The upper limit of detection with this approach was found to be equal to the maximum concentration that we could reach, the one of the stock solution: 5.5 mol/L.

Potentiometric titration

Potentiometry has been used for the determination of the titration endpoint with thiosulfate and TPP titrants. The experimental results are shown in Figure 3. TPP in n-decane was used at different concentrations (0.08 mol/L, 8 × 10 -3 mol/L, 8 × 10 -5 mol/L) since the volume of a droplet in the potentiometer need to stay small compared to the one in the burette. The potentiometric method using Na 2 S 2 O 3 (0.025 mol/L) in water as titrant shows a scattering of the experimental points (Figure 3). The miscibility issues induced by the use of an aqueous titrant led to problems. For this reason, only a limited number of dilution points were explored. These miscibility issues are discussed in more details later in the text. Only a high concentration of peroxides can be measured as the measure fails at ROOH concentration below 1.0 × 10 -2 mol/L. Indeed, the highest concentration leads to a higher immiscibility, which determine the limitation of this method. mol/L can be reached and the highest concentration is 5.5 × 10 -1 mol/L, which is restricted by the detection limit of the potentiometer. The experimental results of the quantification of peroxides in the different samples of TBHP in n-decane agree well (Mean relative deviation (MRD) of 32.7%) with the commercial concentrations. The limit of detection of this method is considerably lower than the colorimetric approach with the same reagents and titrants

The MRD obtained by colorimetric titration with TPP in n-decane as titrant is 14.8%, while the that with sodium thiosulfate in water titrant is 20.7%. As already mentioned, the TPP in n-decane titrant is better suited for the titration of hydroperoxydes in organic solvent because of miscibility issues when aqueous thiosulfate is used in these solvents. Indeed, the main difference in the titration with an aqueous phase titrant and an organic phase titrant lies in the formation of a biphasic medium which brings accuracy issues in the colorimetric (and potentiometric) methods. Figure 5 illustrates the nonmiscibility problems observed when thiosulfate is used as the titrant. Figures 5a and5b clearly show that two phases are involved when water is involved in the titration. The colorimetric determination of the endpoint of titration can even be challenging as illustrated in Figure 5c. Potentiometry cannot be effective on two-phase solutions since the potential of the solution is not homogeneous. In the potentiometric titration, the potential of the indicator electrode in relative to the reference electrode is measured as a function of the titrant volume. In this titration, after adding drops of titrant, the cell potential (in millivolts) is tested and recorded. The volume of titrant added is reduced as the system gets closer to the endpoint of titration. The MRD of TPP with potentiometric titration is 13.0%, which is lower than the detection of endpoint with color change. Note that dilution uncertainties are preponderant in the reported MRD because successive dilutions increase the uncertainty in the reference TBHP concentrations. We demonstrate that potentiometry with TPP in n-decane is accurate, easy to program with an automated titrator and allows a wide range of ROOH quantification.

It can be noted that all the colorimetric titration results show that the TBHP concentration is within the upper limit of the supplier certifications (between 5 and 6 mol/L).

UV-visible spectroscopy

The titrations methods are based on the quantification of I 2 formed in the iodometric reaction ( 5) by its reaction with TPP or thiosulfate. I 2 can also be directly detected by UV-vis absorption and we explored this approach in this section. The absorbances at 362 nm of the diluted solutions of TBHP in n-decane, from higher concentrations to 1 × 10 -7 mol/L, and subjected to the protocol of Roohi and Rajabi [START_REF] Roohi | Iodometric Determination of Hydroperoxides in Hydrocarbon Autoxidation Reactions Using Triphenylphosphine Solution as a Titrant: A New Protocol[END_REF] (reaction ( 5)) were systematically measured and the results are presented in Erreur ! Source du renvoi introuvable.. Figure 6 shows that the absorbance of the mixtures is linear with concentration over 3 orders of magnitude. The linearity is established with a good correlation coefficient of 0.996 with the experimental concentration determined by the potentiometric titration using TPP. This reference concentration was used rather than the vendor one because we demonstrated that potentiometric titration with TPP is more accurate (see discussion section below) than the colorimetric thiosulfate titration used by the vendor. The main uncertainties observed can be explained by the repeated dilutions of TBHP stock solution (5.5-6.5M). Indeed, the errors seem to be corelated with the syringe precision used for the dilution and increase with the different double or triple dilutions.

Using UV-vis absorbance, lower concentrations as low as 1.0 × 10 -6 mol/L of ROOH can be detected compared to potentiometric titration with TPP, and concentrations as low as to 1.0 × 10 -5 mol/L can be quantified rigorously. We also see that a higher concentration of ROOH cannot be measured by this absorption method because the absorbance is above 2 for concentrations above about 5.0 × 10 -3 mol/L. Above 2, absorbance is known to poorly follow linearly Beer-Lambert law with a spectrophotometer.

The absorbance technique seems to be more reproducible than potentiometry since the standard deviation of each point is less than 9% for the lower concentrations and the mean standard deviation of each point for the potentiometric titration is 13% as specified in Table S1. The error of the dilution of the stock solution of TBHP seems to be linear enough to not affect the linearity of absorbance in the Beer-Lambert law.

Spectroscopy UV-vis is a useful and easy tool widely applied in the scientific fields for its easy use and the detection and the quantification limits are mostly limited by the absorbance of the solution and the path length of the cell. However, with the spectroscopy method, a calibration curve is needed based on a standard solution. This is different from the titration methods, which give an absolute content of ROOH. The accuracy of the UV-vis method will therefore depend on the accuracy of the external calibration done with a peroxide or iodine solution. The MRD increase with the concentration so this method is not adapted for high concentration above 5.5 × 10 -3 mol/L.

High Performance Liquid Chromatography

Experiments consisted in 10 µL or 40 µL injections of diluted TBHP solutions in eluent (isooctane: absolute ethanol 95:5) in the HPLC chain described in Figure 1. Chromatograms that measured the signal of I 3 -at 362 nm are presented in Erreur ! Source du renvoi introuvable.. It can be noted that in our HPLC-P-cR method, absolute ethanol was used instead of isopropanol, which is commonly used in this type of experiment, because we observed that it has the property of readily producing hydroperoxides, probably due to its facile autoxidation. A new solution of absolute ethanol was used every day of experiments and the baseline was checked each time. For these results, the baseline check showed an error ± 0.497 mAU. We can determine a peak if its height is at least 10 times higher than this error. Every peak included in this work outlined this error bar.

The results presented in Figure 7 show that the HPLC set-up used can detect I 3 -, produced in the postcolumn reactor (reactions ( 5) and ( 10)) for concentrations as low as 10 -7 mol/L. The presence of peaks at the retention time of 7.5 +/-0.15 min and the difference of retention times is due to the quantity of TBHP injected in the HPLC. This method is reproducible: each experiment was repeated at least 2 times and the deviation is generally 1.45 mAU which is adequate and the detailed mean standard deviation is shown in table S4.

Using the THBP / n-decane solutions of known concentrations, we calibrated the response of the HPLC-P-cR. Figure 8 presents the results obtained for ROOH concentrations ranging between 0.55 and 5.5 × 10 -9 mol/L. In Figure 8, we can observe that the area of the peaks decreases with the dilution factor. However, this decrease is not linear and three concentration zones appear, that establish the detection and the quantification limits of this technique. We observe that the response is linear from 1.0 × 10 -3 to 5.0 × 10 -5 mol/L. Above 1.0 × 10 -3 mol/L, the absorbance is too high and the Beer-Lambert law no longer applies. Below 5.0 × 10 -5 mol/L, the hydroperoxide content in fresh n-decane which is the diluent has to be considered. Indeed, the fresh bottle of n-decane was found to contain 3.59 × 10 -5 mol/L of hydroperoxides, from the natural aging of the liquid, and explains the plateau observed for the lower concentrations. This artifact due to the presence of hydroperoxides in the diluent highlights the importance of the checking for the presence of hydroperoxides in the solvents used in HPLC-P-cR. Commercially available hydroperoxides are scarce and the only molecules available in organic solvents were TBHP in n-decane and cumylhydroperoxide in cumene.

It is expected that dilutions with cumene to study cumylhydroperoxide would suffer from the same problems because cumene is prone to autoxidation. In order to determine the potential lowest limit of detection of our method, a I 2 solution in absolute ethanol mixed with NaI and acetic acid was injected in the device after removing the 2 columns (analytic and P-cR). The lowest detection limit of I 3 -at 362nm in the PDA cell was determined to be 2.5 × 10 -11 mol/L. mol/L).

The HPLC-P-cR setup quantifies ROOH in solution by determining the concentration of I 3 -using an easy and reproducible method, for a large range of concentrations. In addition, this method has the potential to separate and quantify different ROOH structures in a mixture of oxidized components.

Adsorption chromatography is well suited for oxidized fuels, since it leads to the formation of oxygenated low molecular mass products. Since the analytical column is normal phase, an efficient separation of polar and non-polar fractions can be achieved. Hydroperoxides are very polar molecules so these molecules will be well retained and elute at the end of each analysis.

An overview of the different methods explored in this work for the quantification of hydroperoxides is given in Figure 9, along with their detection and quantification limits. meaning an extension of the lower limit of quantification, require the use of solvent free of hydroperoxides and it should be pointed out that for HPLC, as for UV-vis used in the latter method, an external calibration is required to obtain the iodine response, which was not necessary with the potentiometric titrations. It may be noted that the detection limits presented here are the intrinsic values of the methods and that the upper detection limit could be extended by sample dilution. However, as noted several times in the manuscript, successive dilutions inevitably lead to an increase in measurement uncertainty.

Conclusion

This work compared the reproducibility and detection limits of different techniques of hydroperoxides quantification in fuels. The change of color and potential in iodometric titrations and the UV-Vis absorbance of the solutions were monitored during different methods. A commercial solution of TBHP in n-decane was used as standard and diluted. Potentiometric and colorimetric titrations showed to be reproducible at high concentrations, especially when using TPP as titrant in an organic phase. The use of thiosulfate in an aqueous phase as a titrant is poorly reproducible and explains the limitations of this ASTM standard method. The potentiometric method gives reproducible results until a concentration of 10 -4 mol/L. Below that value, experimental uncertainties take a larger place and biased the results. Spectroscopy using UV-vis absorption at 362 nm is able to quantified hydroperoxides in a reproducible way until 10 -6 mol/L. The results obtained with the new HPLC coupled with a post-reactor column for the iodometric reduction of hydroperoxides are very promising because concentration as low as 10 -11 mol/L can be detected and ROOH were quantified for concentrations as low as 10 -7 mol/L. HPLC is also interesting thanks to the possibility of this device to separate hydroperoxides in an aged fuel and quantify their concentrations in a more complex mixture.

Figure 1

 1 Figure 1 presents a schematic representation of the HPLC device.

Figure 1 :

 1 Figure 1: Representation of the HPLC-P-cR device used in this workA chromatogram such as the one presented in Figure1at 362 nm was obtained, which allows the indirect hydroperoxide quantification (I 3-absorbance at 362 nm) in the sample, after calibration. It

Figure 2 :

 2 Figure 2: Comparison of experimental and theoretical (commercial certifications) TBHP (ROOH) concentrations as a function of dilution. Experimental method: colorimetric titration with different titrants: TPP in n-decane (A) and thiosulfate in water (B).

Figure 3 :

 3 Figure 3: Comparison between experimental and theoretical (vendor certification) TBHP concentrations in n-decane. Potentiometric titration with thiosulfate.

Figure 4

 4 Figure 4 presents the parity plot between theoretical and experimental ROOH concentrations,

Figure 4 :

 4 Figure 4: Comparison between experimental and theoretical (vendor certifications in x error bars) TBHP concentrations and potentiometric titration with TPP in n-decane.

Figure 4

 4 Figure4shows a very good agreement between the theoretical and experimental concentrations for

Figure 5 :

 5 Figure 5: Pictures representing the different states of colorimetric titration of iodine (before the equivalence volume (a, c) and after (b, d) using an aqueous solution of Na 2 S 2 O 3 and using TPP.

Figure 6 :

 6 Figure 6: Absorbance at 362 nm of TBHP in n-decane solutions and the concentrations obtained using potentiometric titration.

Figure 7 :

 7 Figure 7: Chromatograms of different diluted solutions injected in the HPLC-P-cR device measured at 362 nm (10 µL injected at 1 mL/min for 10 min). Chromatogram A: solid blue line: [ROOH] = 5.5 × 10 -3 mol/L; Chromatogram B: orange line: [ROOH] = 5.5 × 10 -4 mol/L, yellow line: [ROOH] = 10 -5 mol/L and brown line: [ROOH] = 5.5 × 10 -7 mol/L.

Figure 8 :

 8 Figure 8: Area of the peaks at 362nm as a function of the theoretical concentration of TBHP (10 µL injected at 1 mL/min for 10min). Left panel: all data over the full range of concentrations explored. Right panel: zoom on the linearity zone (R 2 = 0.9925); triangles are the mean values of the repeated measurements.

Figure 8

 8 Figure 8 also shows that concentrations up to 0.55 mol/L can be detected until the saturation of the

Figure 9 :

 9 Figure 9: Detection limits and quantification range of each techniques| Doted part are detection limits and plain part are quantification rangeFrom Figure9, it appears that the titration methods with TPP in n-decane allow ROOH to be detected

ACKNOWLEDGMENTS

The project leading to this application has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement No 101003318). This work was also financially supported by the BioACe project, grant ANR-18-CE05-002 of the French National Research Agency, and the Grand-Est region. The authors thank Yvonne Anak Derrick Warren and Emilien Girot for their help with the experiments.


David Bétaille
email: david.betaille@univ-eiffel.fr

Cyril Meurie
email: cyril.meurie@univ-eiffel.fr

Yann Cocheril

Vision-and map-based non-line-of-sight satellites hybridized processing

Intelligent transportation systems use GNSS receivers as basic technological components. In urban applications one faces the problem of GNSS multipath and particularly of non-line-of-sight (NLOS) satellites. The development of GNSS receiver technologies for mass market encompasses the capability NLOS satellites processing by innovative techniques, not only based on the Signal to Noise Ratio, but also on vision or city model. This is particularly needed for urban positioning of cars for applications which require high accuracy and integrity, typically driving automation. This article deals with the detection of NLOS satellites among those tracked by an automotive-range receiver. We aim at developing a method jointly based on the analysis of video stream and a 3D map model of the environment. The article provides a literature review, an evaluation of some existing techniques and a preliminary analysis of the implementation of the retained algorithm on a prototype developed in the frame of a European H2020 "Fundamental Elements call" project.

I. INTRODUCTION

Global Navigation Satellites Systems (GNSS) widely contribute to the localization and navigation systems in Intelligent Transport Systems (ITS). However, as GNSS positioning relies on the propagation time measurement of at least 4 satellites simultaneously, their positioning performances are degraded in constraint environments such as urban zones. The impact of the surroundings of the antenna can be, first, unavailability of the service when signals are blocked, but also accuracy decrease in presence of multipath reception. Moreover, the case of Non-Line-Of-Sight (NLOS) signals -i.e. signals received after reflections on the surrounding obstacles with no direct ray -frequently occur in densely built environments and degrade localization accuracy because of the delay observed on the propagation time measurement when a reflection occurs. This delay creates an additional error on the pseudo-range measurement. In order to mitigate multipath impacts onto signal reception and tracking, a number of hardware solutions have been developed for a while by GNSS manufacturers, both at the antenna level and at the receiver level. This is not specifically the purpose of this research. In the meanwhile, many works focus on the development of solutions based on the complementarity of other sensors such as vision. Some of these solutions provide good results but are not yet integrated into embedded systems to be industrialized. This is one of the objectives of the eMAPs project. Another is to take advantage in this LOS/NLOS discrimination problem of local city map models, when available.

The development of GNSS receiver technologies for mass market encompasses the capability of NLOS satellites processing by innovative techniques, not only based on the Signal to Noise Ratio (SNR), but also on vision or city model. This is particularly needed for urban positioning of cars for applications which require high accuracy and high integrity, typically driving automation.

We aim at developing a method jointly based on the analysis of video streams and a 3D map model of the environment, in order to guarantee the detection of NLOS satellites among those tracked by an automotive-range receiver. This article is divided into four main parts. Section 2 gives a literature review. Section 3 is related to the NLOS detection based on vision. The definition of the retained algorithm for the sky/not-sky classification step is described and the validation is carried out on the experimental multi-sensors dataset created in Toulouse. Section 4 is related to the NLOS detection based on map model, including the description of the retained strategy that is applied in comparison to the vision-based strategy. Section 5 describes in deep the navigation results. Then we conclude on the work realized.

II. LITERATURE REVIEW

Literature focusing on techniques for localization performance enhancement in harsh environments is abundant. The most spread rely on multi-sensor-based approaches, for which the goals are to compensate the lack of performance of GNSS by adding other sensors (odometer, Inertial Measurement Unit, etc.). The number of sensors can increase the system complexity. Considering that, even with augmentation systems, multipath remain the main source of errors in localization systems, some studies investigate how to enhance accuracy by mitigating this specific source of errors [START_REF] Lentmaier | Bayesian Time Delay Estimation of GNSS Signals in Dynamic Multipath Environments[END_REF]. Such techniques propose some exclusion procedures to avoid using corrupted data [START_REF] Pervan | Parity space methods for autonomous fault detection and exclusion using GPS carrier phase[END_REF]. They can rely on GNSS observables such as SNR or the elevation angle [START_REF] Wang | High-Sensitivity GPS Data Classification Based on Signal Degradation Conditions[END_REF] that can inform on pseudorange reliability. Another approach consists in exploring the knowledge of the structure of the environment crossed by the vehicle for enhancing accuracy using vision. This part is specifically detailed below.

A. Review about NLOS detection using vision

This knowledge of the structure of the environment crossed by the vehicle can be extracted from video records or 3D models when available [START_REF] Marais | Land Mobile GNSS, Availability and Multipath Evaluation Tool[END_REF]

[5] [6] [7] [8] [9].
Concerning, the first option, that is called direct, no a priori database or mapping is required. The structure can be obtained by images provided by several cameras installed on the roof of the vehicle. The approach has already been validated with the PREDISSAT tool [START_REF] Marais | Land Mobile GNSS, Availability and Multipath Evaluation Tool[END_REF] and is continuously improved in several research project (CAPLOC, SATLOC, ERSAT-GCC, SMARTIES, LOCSP and FERROMOBILE). In a first step, the state of reception of satellite signals is determined by comparing satellite positions and obstacle positions around the antenna. Satellites positioned in the sky area are directly visible: those behind the mask are NLOS. The information extracted from the image can allow us, for example, to exclude or weight, the satellites that degrade the receiver performances. In this way, the literature proposes different methods based on sky/not-sky classification using image processing. But most of them do not respect the real time constrain for embedded application or do not provide satisfactory results in complex urban environment. Some of which are proposed, tested and improved in the framework of research projects, but are not yet industrialized. This is why the eMAPs project aims to use the potential of the most promising methods by going to the end of the process, i.e. the industrialization of the complete embedded system. In the following, we present the different categories of NLOS detection methods based on image processing, called direct, and detail, for each of them, the most relevant papers of the state-of-the-art regarding the eMAPs project.

As introduced previously, during the last decade, we have seen a strong growth of research works using computer vision for applications related to localization systems. They can be classified into different categories. First of all, we can distinguish methods using perspective images and other solutions based on omnidirectional images allowing a wider field of view. In the framework of the eMAPs project and the eHermes prototype, we focus on the second approach. Secondly, one can classify the proposed approaches into different categories. The first one consists in using methods based on matching algorithms to find, from a database of georeferenced images, the image closest to the requested image [START_REF] Zhang | Image based localization in urban environments. 3D Data Processing Visualization and Transmission[END_REF] [11] [START_REF] Hays | Im2gps: estimating geographic images from single images[END_REF]. The second one consists in using images (mainly omnidirectional) coupled with 3D models to detect the skyline separating the sky from other objects in the environment (vegetation, bridge, building, etc.) [START_REF] Koch | Wide-Area Egomotion Estimation from Known 3D Structure[END_REF] [5] [START_REF] Ramalingam | SKYLINE2GPS: Localization in urban canyons using omni-skylines[END_REF]. The third one consists in using omnidirectional image to detect the skyline and classify the pixels/regions of the acquired image as sky (respectively non-sky) in order to identify, after repositioning in the image, satellite classified LOS (respectively NLOS). This is the last category that we retain for the real-time detection task of the LOS/NLOS satellites of the eMAPs project. The methods of this category, which are likely to be appropriate, can also be classified with a finer level of detail, depending on whether they deal with:

• image segmentation or unsupervised clustering [START_REF] Cohen | Quantification of GNSS signals accuracy: An image segmentation method for estimating the percentage of sky[END_REF] • specific sensors such as infrared cameras [START_REF] Meguro | GPS accuracy improvement by satellite selection using omnidirectional infrared camera[END_REF] [5];

• dedicated on FPGA architecture [30] [31].

To summarize the literature review on LOS/NLOS visionbased and conclude, current state-of-the-art approaches use convolutional neural networks to segment image into sky vs non-sky regions. They offer in certain case better results compared to more classical strategies but require a powerful training process, dedicated hardware and a huge computational time when large scenario coverage is aimed. This is for this reason, that we will not retain these types of approach in the framework of eMAPs project. Other works, most of which are older, but which offer very interesting performances focus on so-called more classical clustering techniques. They are applied on infrared, multispectral, or visible images. We can now reject the methods developed for infrared images because of the type of cameras embedded in the eHermes prototype. The other methods used in the visible domain are mainly methods based on: edge detection (Sobel, Canny), automatic and non-parametric image thresholding (Otsu), supervised (SVM, k-NN, Bayes, Neural Networks...) or unsupervised clustering (Fisher, Kmeans, Fuzzy C-means...). They can also combine more in-depth methods used in pre-processing of the clustering step such as color space changes or segmentation methods based on graph analysis, on superpixels or combining various complementary characteristics such as texture, luminosity, points of interest, etc. The comparison of the performance of the vision-based algorithms proposed in the framework of sky/non-sky detection for the improvement of the localization is often discussed in research papers. It allows us to carry out cross-checks to isolate the most interesting approaches. In our opinion, edge detection methods are not adapted to the high complexity of the urban environment in which the eHermes system will be used. Classification approaches that are coupled with a pre-processing step based for example on superpixels segmentation or combining complementary features are to be avoided due to the low speed/performance gain. Unsupervised or supervised classification techniques seem to be the most suitable and preferred approaches. Several studies have shown that the Fisher algorithm used on a simplified image offers very good results on real dataset acquired with a fisheye camera as well as SVM but with a higher processing time. This one seems to us relevant as well as the Otsu algorithm which has been recognized for several years and by several authors as very interesting in terms of performance and processing time. Considering the real-time detection task of the LOS/NLOS satellites in the eMAPs project, we will therefore focus on these two approaches by giving the advantage to the Otsu algorithm for its computational cost and its easy integration on a FPGA board.

B. Review about NLOS detection using map model

As indicated in introduction, an alternative exists to detect NLOS satellites, which is indirect, making use of a digital map into which an a priori user location is projected. The use of geometric city models in urban canyons has first been addressed simultaneously by [START_REF] Bradbury | Code Multipath Modelling in the Urban Environment Using Large Virtual Reality City Models: Determining the Local Environment[END_REF] and [START_REF] Suh | Evaluation of Satellite-Based Navigation Services in Complex Urban Environments Using a Three-Dimensional GIS[END_REF]. Next, a few research teams have been active: [START_REF] Wang | Multi-Constellation GNSS Performance Evaluation for Urban Canyons Using Large Virtual Reality City Models[END_REF] [35] [START_REF] Peyraud | About Non-Line-Of-Sight Satellite Detection and Exclusion in a 3D Map-Aided Localization Algorithm[END_REF], coupling 3D modelling with road plane or numerical terrain 2D constraints. Sky plot of building boundaries from the perspective of the user is made popular at that time.

Whereas these articles present methods that do not model the additional path delay due to signal reflection, a few others, on the contrary, will actually make this next step forward: [START_REF] Bourdeau | Tight Integration of GNSS and a 3D City Model for Robust Positioning in Urban Canyons[END_REF] [38] [8] [9] [START_REF] Suzuki | Correcting GNSS Multipath Errors Using a 3D Surface Model and Particle Filter[END_REF]. In addition to this LOS/NLOS indirect methodology, shadow matching leverages the possibility of predicting which satellites will be visible from the point of view of the user, and compares this prediction to the actual observation [START_REF] Groves | Shadow Matching: A New GNSS Positioning Technique for Urban Canyons[END_REF] [41] [START_REF] Yozevitch | GNSS accuracy improvement using rapid shadow transitions[END_REF]. One can restrict the user's location domain by considering those satellites present in the ephemeris and for which no measurement is made. Whilst [START_REF] Bétaille | A New Modelling based on Urban Trenches to Improve GNSS Positioning Quality of Service in Cities[END_REF] introduced urban trench modelling of the street (UTM: Urban Trench Model), more recent development [START_REF] Zhu | GNSS propagation channel modelling in constrained environments: Contribution to the improvement of the geolocation service quality[END_REF] got rid of this geometrical approximation, to take advantage of the full polygonal description of the buildings, instead of considering simple parallelepiped streets. This methodology (UMM: Urban Multipath Model) is presented in section 3. Despite several proofs of concept for map aided GNSS location through LOS/NLOS detection, there is still need for large scale experiment and results, unless the methodology cannot be generalized. This is one of the purposes of this research in eMAPs, the other being the comparison with vision-based.

III. NLOS DETECTION BASED ON VISION

Considering our analysis of the state-of-the-art, it seems judicious to use the Otsu algorithm in the sky/non-sky classification task in the framework of the eMAPs project. Indeed, this method is relatively simple to implement, does not require any specific hardware, and has a reduced calculation time. These are all reasons why it is often used in the vision aided GNSS applications. Thus, we recall, the principle and the definition of the algorithm given in details in [START_REF] Otsu | A Threshold Selection Method from Gray-Level Histograms[END_REF] and synthetized in [START_REF] Gakne | Assessing image segmentation algorithms for sky identification in GNSS[END_REF]. Otsu algorithm is a non-parametric and unsupervised method based on an automatic threshold selection currently used in image segmentation. It allows to binarize an image by analysing its histogram and calculating an optimal threshold. This threshold value used to classify the pixels of the image into one of the two possible classes (sky and non-sky in our works) is the one that maximizes the interclass variance.

The eMAPs dataset (see section V) contains 43683 images acquired in the area of Toulouse with the fisheye camera oriented toward the sky for the NLOS detection task. The sky/not-sky classification procedure based on Otsu algorithm has been tested on the entire dataset and provide visual satisfactory results. Nevertheless, to provide quantitative results, we have calculated four classical metrics used actually in artificial intelligence domain: accuracy, recall, precision and f1-score. These metrics require a ground truth of the sky/notsky classification but which cannot be carried on the whole dataset because of the time involved, a problematic well know of the research community. To solve this problem, we have created a reduced dataset (with a frame rate of 250) containing 175 images evenly distributed along the course. The corresponding reference classification has been handmade created by four experts with the Computer Vision Annotation Tool. Figure 1 illustrates four fisheye images acquired in different environments during the experimentation (line 1), the output classification provided by Otsu algorithm (line 2), the corresponding temporary ground truth image created with CVAT (line 3). the LOS/NLOS satellites detection after repositioning in the current image (line 4). In this line, LOS (respectively NLOS) satellites are marked in green color (respectively in red color). Thus, on this reduced dataset, the sky/not-sky classification results based on Otsu algorithm obtains an accuracy of 93.16 %, a recall of 99.96%, a precision of 89.95% and a f1-score of 93.66%. Figure 2 illustrates the different metrics calculated on each image of the reduced dataset. It permits to shows if the classification results are constant or if some images are more difficult to treat. Globally, the f1-score is upper to 80% whatever the image considered expect for 3 slots regrouping 9 images over 175 images. Indeed, as we can notice in Figure 2, three slots show a decrease of the performance: the first one (images [START_REF] Middel | Sky View Factor footprints for urban climate modeling[END_REF][START_REF] Laungrungthip | Edge-based detection of sky regions in images for solar exposure prediction[END_REF][START_REF] Pavlovic | The Skyline Image Segmentation using Color and Detail Clustering[END_REF] shows a minimum at 44%, the second one (images 86-88) is lower at 32% and the last one (images 93-96) is the worse at 16%. These classification errors are all due vegetation in the images.

IV. NLOS DETECTION BASED ON MAP MODEL

The basic idea is to project the current rover position estimate into a 3D map model and determine, from this point of view, whether or not satellites are LOS or NLOS. The rover position estimate could be:

• either the one based on the GNSS only observations • or the one based on GNSS hybridized with other sensors, e.g. wheel speed, IMU, visual odometry... In test, the ground truth can also be used instead of the rover position, to estimate best feasibility. The 3D map model, in the context of this research, makes use of the French national database, BD Topo ®. This is available everywhere in France, with approximately 3 years age. The building layer is used, i.e. polygons representing buildings and their average height. In order to keep reasonable computational throughput, a selection in the map data should be made. This has been specified in accordance with the itinerary performed for test purpose in section V.

The LOS/NLOS decision based on 3D map model is returned to the GNSS navigation algorithm in order to e.g. reweight the GNSS observations depending on the LOS/NLOS decision. In addition to this decision, the methodology is capable of computing a ranging correction in NLOS case. This correction can be applied by the navigation algorithm. The process is first to detect if any facade exists in every satellite azimuth, with a height enough to occult the corresponding satellite elevation. This initial step identifies LOS/NLOS satellites. The next step is to examine every facade, locally, to detect whether it could make a specular reflection with the occulted satellite previously identified. In this case, the final step is to check that no other facade may occult the reflected ray, whether in between the antenna and the impact point, or whether in between the impact point and the satellite. In case several facades exist with reflected rays, the one with the largest incidence angle is preferred. Facades are regarded as vertical planes, with the height of the polygon they belong to. There are several options finally, but the one suggested by Ni Zhu in her PhD dissertation [START_REF] Zhu | GNSS propagation channel modelling in constrained environments: Contribution to the improvement of the geolocation service quality[END_REF] relies on both functional and stochastic approaches. For those satellites being NLOS: ranging are corrected, using the additional travelled paths estimated with the 3D map model (functional) and ranging are reweighted in the least-squares of Kalman filter GNSS navigation algorithm: their variances are multipied by 10 (stochastic).

A. Experimental setup

An acquisition campaign has been carried out in the city of Toulouse, on 23 April 2021 (Figure 3). There are two sections, initial and final, in urban environment, and an intermediate section, on the south ad east highways of Toulouse. The total duration of the test is 62 minutes: 56 minutes in the city centre and 6 minutes on the highway. 5 minutes (between 17:14 and 17:19) in the very deep centre of the city have been chosen to focus on in the analysis. In addition to the skyward facing camera, the GNSS equipment on-board the vehicle was, in addition to a Ublox F9P multi-constellation receiver, a Novatel SPAN GNSS inertial navigation system, for ground truth purpose, continuously available and reliable (i.e. dm accurate).

B. Global confusion matrix

A confusion matrix has been computed in order to compare both methodologies of LOS/NLOS classification using vision and map. The rover position used for map-based LOS/NLOS decision was, for feasibility purpose, the reference trajectory or ground truth. We prove, in the deep centre of Toulouse, that LOS/NLOS classification disagreement between both methods will not occur for more than 12% of the total number of satellite observations.

In the deep urban centre, one counts 1501 epochs with GPS measurements (5 minutes @ 5 Hz) on 23 April 2021 in Toulouse. This totalizes 11821 measurements, among which the elevation and azimuth of 7270 satellites have their projection in the fisheye field.

The LOS/NLOS confusion matrix for fisheye vision versus map model classifications is given in Table I.

C. Navigation results based on 3D model

The navigation solvers used are a GPS-only ordinary leastsquares (OLS), in which every satellite has the same weight, and a weighted least-squares (WLS), similar as RTKLIB with usual modelling of range errors, in which the variance equals:

σ 2 GP S = 0.3 2 +0.3 2 /sin(el)+2.4 2 +0.3 2 +0.3 2 +0.5 2 (1)
where 2.4m stands for orbit error, 0.3m for receiver noise, 0.3m and 0.5m for iono and tropospheric errors resp. Broadcasted ephemeris are used (tlse113z.21n). An elevation cutoff of 15°is optional.

In case of NLOS satellite, a geometrical correction is applied, and the satellite is downweighted by a factor 10 (i.e. variance*10). LOS/NLOS decision and range correction are based on the ground truth in this computation.

The plane error (HPE: horizontal positioning error) is computed and given in Table II, i.e. the quadratic sum of East and North (E, N) deviations between the GPS solutions and the reference trajectory. The plane error envelop (HPL: horizontal protection level), i.e. the semimajor axis of the plane error ellipse, is computed and given in Table III, with a probability of missed detection PMD of 0.1% and dimension 4 (for E, N, Up and receiver clock term), which is supposed to bound 99.9% of the plane error. Note that, before computing this HPL, a global test is made, in order to select only reliable solutions. This test, a χ2 test based on the sum of weighted residuals, eliminates solutions with a probability of false alarm PFA of 0.1%. The degree of freedom applicable in this test equals the number of used satellites minus 4.

In this table, we focus on results in the city only, and for weighted least-squares. The misleading information (MI) is also indicated, i.e. the rate of HPE being actually over HPL, violating the computed integrity. The improvement for GPS-only with no elevation cutoff is around 0.3m less on the median plane error in Toulouse urban test globally (after removing the highway). One gets 2.33m instead of 2.69m, applying the NLOS downweighting and correction. This is in the city centre. The 68 and 95 percentiles are improved by resp. 1 and 4 meters. Almost the same accuracy seems achievable with a 15°cutoff, which would disqualify the map-based NLOS correction, even based on ground truth. However, removing satellites below 15°elevation increases error on the highway, by 0.6m approx. Hence, keeping all satellites, even low in elevation, with NLOS detection and correction seems rather valuable. Moreover, the combination of this 15°cutoff with NLOS detection and correction gives the best results, with a median plane error still equal to 2.40m but with improved 68 and 95 percentiles. An examination into details of samples of the trajectory in the deep urban centre of Toulouse have also be carried out. This shows that UMM does bring improvement when combined again the elevation cutoff. In the case of 15°e levation mask and UMM, the best accuracy is obtained. This indicates that UMM calculation is applicable and valuable to satellites above this elevation mask.

At first analysis, results are positive in Toulouse, even if not so impressive compared to what we used to obtain in Nantes and, above all, in Paris. Note that formerly, we also experienced slightly less success in applying UMM in Toulouse, except in the urban city centre. Globally, Toulouse streets are very different from Paris Haussmannian streets. (UTM was not that good approximating in Toulouse.) Another challenge is to measure the improvement by UMM on the same version of the navigation algorithm, i.e. every other tuning (in particular stochastic parameters) being unchanged. This was not the case in several of our previous works neither in some other articles one can read about map-aided navigation. It is non sense e.g. comparing an OLS with a map-based WLS. Both should be weighted or not, with modulations due to the use of the 3D city model.

For further works, we aim at investigating again with the same algorithms our former data sets, in 2012, 2014 and 2019, in Nantes, Paris and Toulouse. Some are running the F9P (the latter), some the LEA 6T from Ublox. Again, the impact of the ionosphere should be regarded carefully, in particularly in 2014 where it was maximum and not properly modelled in our previous investigations [START_REF] Rivoal | A benchmark of the GPS+Galileo F9P receiver[END_REF]. Note that range downweighting in NLOS case mechanically increases protection level, leading to less integrity failure. An alternative, in order to keep almost constant envelop, would be to upweight all other ranges in LOS case.

D. Navigation results based on vision

Instead of map-based, one suggests in this last part to move to vision-based (for those satellites projecting in the fisheye field of view). In this case, no range correction is made, but only downweighting in NLOS case. In short (Table V), the introduction of vision-based LOS/NLOS sorting in the solver does not change much to the results already shown. They remain almost unchanged. In the deep centre of Toulouse, we have 4.65m of median error against 7.03m for fisheye sorting (8.36m if we do nothing). Since we know that both sorts match 88% in Toulouse, one can assume that the ranging correction makes a significant difference in the very final navigation results, because downweighting only seems not so efficient.

VI. CONCLUSION

This article is based on the research and development activities on the vision subsystem of the GNSS eHermes platform, delivered during the eMAPs H2020 project. The vision-based GNSS is challenged with a 3D model-based LOS/NLOS satellite processing.

The first part of the article summarises an analysis of the current state-of-the-art of the NLOS detection based either on vision or on 3D map. At this stage, Otsu algorithm seems to be promising for the vision-based NLOS detection on the eHermes prototype. The second part is devoted to the description of the NLOS detection based on vision and the evaluation of the performance of the retained Otsu algorithm. The evaluation concludes that Otsu algorithm yields good results: a good classification rate around 96% and a computational time of 27ms/frame on the experimental multisensors dataset created by ENAC during the eMAPs project in Toulouse. The third part is devoted to the NLOS detection based on 3D map model using the French national database, BD Topo ®. The methodology based on the detection of satellite occluding facade and the possible reflecting ones is described. The jointly use of functional and stochastic approaches combined seems to be an interesting and promising way. Finally, a comparison between vision-based and mapbased LOS/NLOS processes has been carried on a focus of 5 minutes in the very deep centre of the Toulouse city. Both techniques agree by 88% with an advantage, in terms of accuracy, using the map and the inferred additional pseudoranges, if NLOS, due to building reflections.

Additional work is on-going in order to finalize the eHermes implementation and also to generalize the processes to other satellites than GPS only. Trying to keep reasonable protection level, not increased PL due to downweight of NLOS ranges, is also targeted in further research about aided urban navigation. ACKNOWLEDGEMENT These research investigations have been carried out in the frame of the eMAPs European H2020 "Fundamental Elements call" project. The authors warmly thank the project leader Benjamin Kawak, 3DAerospace, as well as Paul Thévenon, ENAC and his post-doc Jan Bolting, for developing the eHermes prototype and providing the experimental framework and data in Toulouse.

Algorithm 1 2 k 4 .

 124 Summary of Otsu algorithm 1. Compute the histogram (the number of occurrences for each intensity level) and the probability of each intensity level p i 2. Set the initial values P 0 (0) and P 1 (0) and their initial corresponding means µ I C0 (0) and µ I C1 (0) 3. Set through all possible thresholds from 1 to L : 3.1. Update P 0 , P 1 and µ I C0 and µ I C1 3.2. Compute the inter-class variance α The desired threshold k * corresponds to the maximum of α 2 k

Fig. 1 .

 1 Fig. 1. LOS/NLOS satellites detection by vision

Fig. 2 .

 2 Fig. 2. Sky/not-sky classification results on the reduced eMAPs dataset, compared to the ground truth and using the classical metrics: accuracy, recall, precision and f1-score

Fig. 3 .

 3 Fig. 3. One hour loop in Toulouse

  Table IV, is made onto the 5 minutes subset in the deep city centre of Toulouse.

		TABLE III
	NAVIGATION RESULTS: PROTECTION LEVEL (HPL)
	Each cell displays	City centre	City centre
	median, 68 and 95	16791 epochs	16791 epochs
	percentiles of HPL		map-aided
	WLS no el mask	71.5% global test ok 78.9% global test ok
		7.33m	7.65m
		8.64m	11.00m
		18.14m	31.99m
		18.1% violation	1.6% violation
	WLS el>15°88.1% global test ok 92.2% global test ok
		11.68m	11.96m
		12.18m	12.95m
		21.87m	43.60m
		7.8% violation	1.8% violation
	A particular focus,

TABLE IV NAVIGATION

 IV RESULTS IN THE DEEP CITY CENTRE: HPE AND HPL

	Each cell displays	Deep city centre	Deep city centre
	median, 68 and 95	1501 epochs	1501 epochs
	percentiles		map-aided
	WLS no el mask	9.78m	8.85m
		16.95m	11.20m
		31.51m	20.22m
		27.2% global test ok 76.7% global test ok
		14.03m	25.56m
		15.24m	26.77m
		25.46m	36.75m
		25.7% violation	1.6% violation
	WLS el>15°8.36m	4.65m
		10.70m	7.68m
		22.75m	14.74m
		74.5% global test ok 96.7% global test ok
		17.70m	25.57m
		17.90m	28.07m
		21.68m	48.14m
		14.4% violation	1.2% violation

LOS by vision NLOS by vision LOS by map model

5953 images: 81.9% 401 images: 5.5% NLOS by map model 502 images: 6.9% 414 images: 5.7%


Karim Benzarti
email: karim.benzarti@ifsttar.fr

Sylvain Chataigner
email: sylvain.chataigner@ifsttar.fr

Mazen Wahbeh
email: mwahbeh@altavistasolutions.comrboundouki@altavistasolutions.com

Elena Martin
email: emartind@dragados.comlsopenac@ggravityeng.com

Luis Sopena

Maria Zalbide
email: maria.zalbide@tecnalia.com

Garcia-Sanchez David
email: david.garciasanchez@tecnalia.com

Tecnalia

Veit Birtel
email: veit.birtel@mpa.uni-stuttgart.defrank.lehmann@mpa.uni-stuttgart.de

MPA Frank Lehmann

Gianluca Gemignani
email: gianluca.gemignani@collanticoncorde.it

PREVENTIVE FATIGUE STRENGTHENING OF STEEL STRUCTURES WITH BONDED CFRP -EFFICIENCY DEMONSTRATION ON A REAL BRIDGE

ABSTRACT: One of the goals of sustainable development applied to bridge infrastructure is to provide bridge owners with strengthening solutions that may lead to an increase of existing structures service life. In the case of steel bridges, the assessment of the remaining service life is most often linked to the determination of the structural deterioration caused by corrosion and fatigue. Damage caused by fatigue is very difficult to assess before crack initiation, and is more bound to occur in old structures, for which the phenomenon was not taken into account in design before 1970. In addition, old steel materials present a more brittle behavior. To address these issues, a preventive methodology for fatigue strengthening of steel structures and a strengthening solution based on the use of an adhesively bonded UHM (Ultra High Modulus) CFRP (Carbon Fiber Reinforced Polymer) plate was developed and applied to an existing bridge (Jarama bridge near Madrid in Spain) for validation. Strain measurement was carried out to verify the theoretical expectations of the reinforcement, and different parameters were studied such as the influence of low traffic during reinforcement application. The obtained results proved the efficiency of the system for the studied structure.

Introduction

Steel bridges present frequent fatigue damages that reduce their load-carrying capacity and residual life. The increase of traffic flows and loads over the last decades has emphasized this problem, especially on ageing structures. In Europe, 15% of the 300 000 bridges are made of steel or concrete-steel structures, and approximately 68% of them need structural interventions. In the USA, figures are quite similar.

Having this in mind, in November 2015, the ERA-NET Plus project FASSTBRIDGE was launched aiming at developing a complete methodology including a calculation method to assess the remaining life of steel bridge in terms of fatigue, a design and application method for the strengthening intervention, and a strengthening system relying on the use of adhesively bonded UHM-CFRP plates (Ultra High Modulus Carbon Fiber Reinforced Polymer Composites).

The paper presents the FASSTbridge methodology and strengthening system, which were designed with codes based both on The American Association of State Highway and Transportation Officials (AASHTO) or the European Union's Eurocode, and their implementation in Jarama Bridge (Madrid, Spain).

Description of the Bridge selected for the demonstration (Jarama Bridge)

Jarama Bridge is located in Madrid (Spain) over Jarama river on road M-111. It was designed in 1962 (Design Code 1956) and erected around 1965. It is a 3 span continuous beam with two lateral simply supported spans, with the following distribution: 16.6 m -24.2 m -36.9 m -24.2 m -16.95 m (Figure 1.a). The total length is 118.85 m. The main structure is made of structural steel whereas the top slab is in reinforced concrete with a width of 9,20 m. The whole structure is welded. The cross-section consists of two I-beams connected by transversal cross-bracings to stiffen the bridge in transversal direction (Fig. 1.b). The design code of 1956 did not take into account any fatigue limit state. Adequacy of the structure for the project needed to be checked by carrying-out a fatigue limit state analysis.

Diagnosis of Jarama bridge

Condition of the bridge

A detailed inspection of the structure was carried out to determine its adequacy for the demonstration. As the project is dedicated to preventive intervention, the structure must be in good condition for the retrofit and free from fatigue damages. Steel elements in Jarama Bridge were generally in good condition. Still, there was moisture, moss, corrosion and some other local detectable defects. On the top flange of the main girders, general corrosion was notable. In some cases, corrosion had already progressed into the web plates. In some other cases, efflorescence and pealing problems were noted. The same deficiencies were also present on the bottom flange. Crosses or x-bracing seem in good condition and no visual defect was noted. Nevertheless, bottom lateral bracing members of span 1 show important distortion, corrosion and some other defects probably caused by object impact. One angle in bottom lateral bracing member of span 5 also presented small deformation.

The floor beams were also in good condition. Moisture, efflorescence and corrosion on the top flange were locally noticed. Some areas of peeled coating can be seen in the bottom flange. Larger areas affected by moisture and corrosion are located in floor beams over piers and abutments.

Selection of welds for the intervention

There were two types of butt welds in the main girders: some were welded on-site and other at workshop. During the second bridge-inspection in 2017, four out of the 8 on-site welds were assessed. In addition to visual inspections, ultrasonic tests were carried out, which showed that the selected welds did not fulfil quality standards according to B UNE EN ISO 5817:2014 neither AL2 UNE EN ISO 11666:2011. From the 27 welds of the second type (in-shop-welds) that were analysed, eleven did not fulfil the quality standards (under AL2 UNE EN ISO 11666:2011).

In order to meet the project budget, accessibility and installation cost must be taken into account. Main span over the river may be the most interesting to stregnthen from a structural point of view, but that would have resulted in budget overspending. It was thus decided to focus on side spans of the bridge.

Span number 2 was selected for the demonstration (Barajas side, see Fig. 1.a). Single beams of span 2 are named "beam 1" and "beam 2". On each beam, four butt welds were worth investigating. Two were discarded because they are too close to the kink of the bottom flange. Therefore, only welds n° 29, 26, 25, 20, 17 and 16 were investigated (Fig 2 .a) and effect of strengthening action was evaluated. In order to get as much information as possible from the demonstration, it was decided to apply different CFRP plate layer arrangements at these selected weld locations: one single layer of 5 plates, 2 layers of 4 plates, and 3 layer of 3 plates.

Theoretical calculations and design of intervention

FEM modeling

To evaluate the strengthening action of CFRP laminates on the butt welds of span 2, a 3D-shell-model was created in FEM-Program (Fig. 2). The two main girders are modelled with shell elements. The deck slab carries out the connection between both girders. For the modelling, the slab induces no loadings into the system and the stiffness in longitudinal direction was set to zero. This allows ensuring a realistic load distribution on both of the girders. The stiffness in transversal direction is achieved in reality by crossbracings. To simplify the model, these latter are idealised by bearings fixed in y-direction.

To represent the welds, the height of the bottom flange was reduced on a small segment with a width of 1-2 cm. It is then possible to get precise results on the stresses with and without strengthening action.

Evaluation of strengthening action

Calculations were conducted, in order to derive the algebraic difference between the minimum and maximum stresses in the welds due to fatigue loading (noted Δσfat). Having this value of Δσfat, an evaluation of the fatigue strength is possible.

Beforehand several scenarios were investigated to estimate an interaction between the welds (possible influence on the neighbouring weld if only one of the welds of the beam is strengthened). From the results of this preliminary investigation, it was decided to strengthen all 6 welds as shown in Fig. 2.b.

For the six welds loaded with tensile stresses, the reduction of Δσfat was estimated. As expected, there is a reduction of Δσfat due to the amount of CFRP laminates and layers. The more laminates next to each other are applied, the higher is the decrease in Δσfat. The same occurs with more layers of laminates. The option "2 layers of 4 plates" per weld provided a reduction of Δσfat of about 8 -15 %, while option "1 layer of 5 plates" gave reduction in the range 4 -7 %, and option "3 layers of 3 plates" led to a reduction in the range 21 -22 %. More details can be found in [START_REF] Chataigner | Fatigue strengthening of steel bridges with adhesively bonded CFRP laminates: case study[END_REF].

Implementation of the strengthening solution in the field

Preparation of UHM-CFRP plates

Ultra-high modulus CFRP plates (460,000 N/mm2, 66,700 ksi) were provided by Epsilon Composite (France). They were cut to the required length and their ends detailed as specified by the designer prior to the preparation of the surfaces for bonding. In addition, when several layers of CFRP reinforcement were considered, the adhesive bonding of the CFRP layers was done at the workshop before being delivered on site (this minimizes the time and the number of operations on site).

Steel surface preparation

In FASSTbridge solution, no primer is needed provided the adhesive application is made shortly after steel surface preparation. A control of the surface preparation quality was done before application of the adhesive. The level of surface preparation by sanding was determined using NF EN ISO 8501-1 (a minimum value of 2.5 is required). Roughness was controlled using NF EN ISO 8503-2. Surface cleanliness was also assessed using NF EN ISO 8502-3.

Adhesive mix and application

A hybrid two component epoxy-polyurethane adhesive (Urepox Extra 2C) was used, with the following specifications: (1) Pot life 30-45 minutes (workability); (2) glass transition temperature Tg > 71ºC after postcuring;

(3) Tensile strength ≥35 MPa, 5,1 ksi. This adhesive was developed specifically for this project by Collanti Concorde (Italy). The only way of achieving the target Tg of 71°C (fixed at the beginning of the project), was to apply a post-curing procedure at high temperature (1 hour at 80ºC) as detailed in [START_REF] Chataigner | Design and evaluation of an externally bonded CFRP reinforcement for the fatigue reinforcement of old steel structures[END_REF]. Implementing this post-curing process on site was quite challenging.

The adhesive mix was applied directly to the surface of the CFRP plate. In general, the target thickness for metal and FRP joints should be 0,5-2,0 mm. To spread the adhesive uniformly, a trowel with a v-notch was used (Fig. 3.a). The application was carried out on CFRP surface, and the impregnated plate was then applied to the steel surface; a roller was used to apply pressure along the reinforcement and remove voids from the adhesive layer (Fig.

Installation in the field and post-curing process

Post-curing (1h at 80°C) of the bonded CFRP system attached to the structure was achieved onsite using ceramic pad units, isolating blankets and a clamping device (Fig. 4). Temperature at the surface of the CFRP plate was monitored continuously during the whole process, in order to control the heating rate and the target post-cure temperature. After removal of the heating system, paint was applied on the whole reinforcement and surrounding steel to protect the area where the coatings had been removed.

Each of the six weld locations was reinforced during night to reduce traffic disruption. For 3 weld locations, traffic was partially deviated during the whole application (one carriageway instead of 2 carriageways). For 2 locations (welds n°26 and 29), traffic was deviated only during the application of the bonded CFRP plates before post-curing. For one location (weld n°16), traffic was not deviated at all. Main results collected by strain gages at the six weld locations are given in Table 1 and in Fig. 6 before and after reinforcement and for both static and dynamic tests. In all cases, a strain decrease between 8 and 30 % was observed after retroffiting, in agreement with theoretical expectations. The highest strain reductions (20 to 30 %) were obtained for locations reinforced with the highest numbers of CFRP plates, showing that the proposed solution works well in the case of the 3 layer configuration (welds 16 and 25). In addition, there was no discrepancy (in terms of strain reduction) for the locations that were reinforced without total traffic disruption (weld n° 16, 26 and 29) compared to those reinforced with total disruption. This suggests that the solution could be applied under low traffic, which would be a major advantage.

Conclusions

The results of FASSTbridge project presented in this article allows proposing a methodology to extend service life of existing steel bridges prone to fatigue loading based on the following stages: Diagnosis, Safety Evaluation, Design of Intervention, Monitoring and Maintenance, in a prefailure scenario. In this line, a fatigue assessment tool was developed for existing structures. Depending on diagnosis, a retrofit design can be proposed if needed, which relies on the use of an adhesively bonded UHM-CFRP plate. FASSTbridge methodology was demonstrated on a real structure (Jarama bridge) near Madrid (Spain). A complete diagnosis of the bridge was carried out, and the remaining service life assessed using the developed methodology. The proposed reinforcement was applied on six locations to check the ease of application and the efficiency of the method through strain monitoring before and after reinforcement during controlled on site load tests. The application was successful and allowed fine-tuning of the solution and proposing improvements for similar operations. More details can be found at www.fasstbridge.eu.

Fig. 1 -

 1 Fig. 1 -Span distribution (a) and general views (b) of Jarama bridge

Fig. 2 -

 2 Fig. 2 -Models of the studied span of Jarama bridge (Span 2) before (a) and after (b) reinforcement at the 6 selected weld locations.

Fig. 3 -

 3 Fig. 3 -CFRP preparation: (a) Application of the adhesive layer and (b) pressure application

Fig. 4 -Fig. 5 -

 45 Fig. 4 -Installation of the heating system used for post-curing operation6. Effectiveness of the proposed solution -Results of load testsIn order to gain knowledge about the condition of the Jarama bridge, a fixed load test was performed. This fixed load condition test allowed, by measuring strains before and after retrofitting, the demonstration of the effectiveness of the intervention. The tests took place during two nights before and after the retrofitting. All the load tests were repeated for both lanes during one-sided traffic blocking of the bridge.Static tests were first performed by placing two 27 tons trucks (Renault Kerax) at three predefined positions of the bridge. Dynamic load tests were also performed by placing a wooden plank, 4 cm in height, at two selected positions, over which a single truck passed at a speed of 20 km/h and 50 km/h. The passage of the truck when hitting with plank, induced a dynamic impact load in the structure. Fig 5.shows examples of positioning of the truck for both static and dynamic load tests.

Fig. 6 .

 6 Fig. 6. Strain measurements during static and dynamic load tests before and after retrofitting

Table 1 -Maximum measured differential strains before and after reinforcement for static and dynamic load tests and for the six studied locations close to the weld toes (80 mm)

 1

	Weld location	Laminates	Static before	Static after	Difference	Dynamic before	Dynamic after	Difference
	16-1	3 x 3 (9)	71 με	56 με	-21 %	60 με	45 με	-25 %
	17-1	1 x 5 (5)	68 με	56 με	-18 %	75 με	62 με	-17 %
	20-1	2 x 4 (8)	84 με	59 με	-30 %	80 με	56 με	-30 %
	25-1	3 x 3 (9)	69 με	51 με	-26 %	65 με	53 με	-18 %
	26-1	1 x 5 (5)	84 με	67 με	-20 %	84 με	77 με	-8 %
	29-1	2 x 4 (8)	77 με	58 με	-25 %	71 με	51 με	-28 %

Acknowledgements

Authors would like to thank Funding Partners of ERA-NET Plus Infravation and the European Commission (grant n°31109806.0008), and are also grateful to Epsilon Composite for their support.