Wiem Ben Romdhane

Bilel Elayeb
email: bilel.elayeb@riadi.rnu.tn

Ibrahim Bounhas
email: bounhas.ibrahim@yahoo.fr

Fabrice Evrard
email: fabrice.evrard@enseeiht.fr

Narjès Bellamine
email: narjes.bellamine@ensi.rnu.tn

Ben Saoud

A Possibilistic Query Translation Approach for Cross-Language Information Retrieval

Keywords: Cross-Language Information Retrieval (CLIR), Query Translation, Possibilistic Approach

In this paper, we explore several statistical methods to find solutions to the problem of query translation ambiguity. Indeed, we propose and compare a new possibilistic approach for query translation derived from a probabilistic one, by applying a classical probability-possibility transformation of probability distributions, which introduces a certain tolerance in the selection of word translations. Finally, the best words are selected based on a similarity measure. The experiments are performed on CLEF-2003 French-English CLIR collection, which allowed us to test the effectiveness of the possibilistic approach.

Introduction

With the huge expansion of documents in several languages on the Web and the increasing desire of non-native speakers of the English language to be able to retrieve documents in their own languages, the need for Cross-Language Information Retrieval (CLIR) System has become increasingly important in recent years. In fact, in the CLIR task, either the documents or the queries are translated. However, the majority of approaches focus on query translation, because document translation is computationally expensive. There are three main approaches to CLIR: Dictionarybased methods, parallel or comparable corpora-based methods, and machine translation methods.

The Dictionary-based methods [16][14] are the general approaches for CLIR when no commercial MT system with a recognized reputation is available. Several information retrieval systems (IRS) have used the so-called "bag-of-words" architectures, in which documents and queries are decayed into a set of words (or phrases) during an indexing procedure. Therefore, queries can be simply translated by replacing every query term with its corresponding translations existing in a bilingual term list or a bilingual dictionary. Nevertheless, dictionary-based methods suffer from several difficulties such as: i) no translation of non-existing specific words in the used dictionary; ii) the addition of irrelevant information caused by the intrinsically ambiguities of the dictionary; iii) the decreasing of the effectiveness due to the disappointment to translate multiword expressions. To reduce ambiguity, one may adopt a corpus-based approach.

In corpus-based methods [START_REF] Vitaly | Accurate Query Translation For Japanese-English Cross-Language Information Retrieval[END_REF], a set of multilingual terms extracted from parallel or comparable corpora is exploited. Approaches based statistical/probabilistic method on parallel text written in multiple languages with the intention of selecting the correct word translation provides a good performance, but they suffer from many drawbacks. Firstly, the translation association created among the parallel words in the text is generally domain restricted, which means that accuracy decreases outside the domain. Secondly, parallel texts in different pairs of languages, are not always available.

In machine translation (MT) techniques [START_REF] Mavaluru | Ensemble Approach for Cross Language Information Retrieval[END_REF][13], the main aim is to analyze the context of the query before translating its words. In fact, syntactic and semantic ambiguities are the principal problems decreasing MT performance. Besides, MTbased approaches suffer from several others limits decreasing the effectiveness of CLIR. Firstly, MT systems have serious difficulties to appropriately generate the syntactic and semantic analysis of the source text. Secondly, full linguistic analysis is computationally expensive, which decreases search performance.

In fact, query translation approaches need training and matching models which compute the similarities (or the relevance) between words and their translations. Existing models for query translation in CLIR are based on poor, uncertain and imprecise data. While probabilistic models are unable to deal with such type of data, possibility theory applies naturally to this kind of problems [START_REF] Dubois | Possibility Theory: An Approach to computerized Processing of Uncertainty[END_REF]. Thus, we propose a possibilistic approach for query translation derived from a probabilistic one using a probability/possibility transformation [START_REF] Dubois | Unfair coins and necessity measures: Towards a possibilistic interpretation of histograms[END_REF]. This approach begins with a query analysis step, then a lexical analysis step, and finally the selection of the best translation using different similarity measures.

This paper is organized as follows. Section 2 details our approach which is experimented in section 3. In section 4, we conclude our work and give some directions for future research.

2

The Proposed Approach

We propose a new possibilistic approach for query translation in CLIR. The proposed approach is an extension of a probabilistic model proposed by [START_REF] Gao | Improving Query Translation for Cross-Language Information Retrieval using Statistical Models[END_REF] into a possibilistic framework, using an existing probability/possibility transformation method [START_REF] Dubois | Unfair coins and necessity measures: Towards a possibilistic interpretation of histograms[END_REF]. In this approach we used a greedy algorithm to choose the best translation [START_REF] Gao | Improving Query Translation for Cross-Language Information Retrieval using Statistical Models[END_REF]. The calculation of similarity between the terms and the cohesion of a term x with a set X of other terms are two essential steps before selecting the best term translation. In our case, we used the EMMI weighting measure [START_REF] Rijsbergen | Information Retrieval[END_REF] to estimate the probabilistic similarity between terms. Then, we extended it to a possibilistic framework (EMMI-POSS) using an existing probability/possibility transformation [START_REF] Dubois | Unfair coins and necessity measures: Towards a possibilistic interpretation of histograms[END_REF]. We briefly recall in the following this transformation and we detail the three main steps of our query translation process, which are summarized in figure 1.

Fig. 1. Overview of query translation process

Formally the similarity between the terms x and y is given by formula (1). However, the cohesion of a term x with a set X of other words is the maximum similarity of this term with each term of the set, as given by formula (4).

)

) ( ) ( ) , ( ( log ) , ( ) , ( 2 y p x p y x p y x p y x SIM × × = (1) ) ( ) , ( ) ( ) , ( ) , ( y c y x c x c y x c y x p + = (2) = = y x y c y c y p x c x c x p ) ( ) ( ) ( ; ) ( ) ( ) ( (3) )) , ( ( ) , ( y x SIM Max X x Cohesion X y∈ = (4)
Where c(x, y) is the frequency that the term x and the term y co-occur in the same sentences in the collection. c(x) is the number of occurrences of term x in the collection.

Probability/Possibility Transformation

Given the universe of discourse Ω = {ω 1 , ω 2 ,…, ω n } and a probability distribution p on Ω, such that p(ω 1 ) ≥ p(ω 2 ) ≥ …≥ p(ω n ), we can transform p into a possibility distribution using the following formulas (for more detail you can see [START_REF] Dubois | Unfair coins and necessity measures: Towards a possibilistic interpretation of histograms[END_REF][7]):

n i p p i n i j j i i , , 1 , ) ( ) ( ) ( 1 = ∀ + * = + = ω ω ω π (5) 1 ) ( 1 = = n j j p ω
and p(ω n+1 ) = 0 by convention. [START_REF] Dubois | Unfair coins and necessity measures: Towards a possibilistic interpretation of histograms[END_REF] Among several transformation formulas, we have chosen this formula, because it satisfies both the probability/possibility consistency (i.e. Π(A) ≥ P(A)) and the preference preservation principles (i.e. p(ω i ) > p(ω j ) (ω i ) > (ω j ) [START_REF] Dubois | On Possibility/Probability transformation[END_REF]). Indeed, this transformation process has allowed us to increase the possibilistic scores of coexistence of two terms in order to penalize the scores of terms that are weakly cooccurring. In fact, the penalty and the increase of scores are proportional to the power of words to discriminate between the possible combinations of coexistence.

Example:

Let Ω = {ω 1 , ω 2 , ω 3 , ω 4 } and a probability distribution p on Ω such that: p(ω 1 )=0.2 ; p(ω 2 )=0.5 ; p(ω 3 )=0.3 ; p(ω 4 )=0. So, we have: p(ω 2 ) > p(ω 3 ) > p(ω 1 ) > p(ω 4 ). By applying the transformation formula, we have:

(ω 2 )=(1*0.5)+(0.3+0,2)=1; (ω 1 ) = (3*0.2) + 0 = 0.6; (ω 3 ) = (2*0.3) + 0.2 = 0.8; (ω 4 ) = (4*0) + 0 = 0.

Query Analysis

It is the first step in this approach, in which stop words are deleted from the source queries using a list of words considered as non-significant for source queries. Then, we extract the set of possible translations from a French-English dictionary generated using the free online dictionary Reverso1 .

Lexical Analysis

The step of lemmatization aims to find the canonical form of a word, so that different grammatical forms or variations are considered as instances of the same word. We applied the process of lemmatization on the test collection and queries before their translations. This reduction mechanism gives better results for the following matching phase.

Selection of Best Translation

It is the main step in our approach. Indeed, selecting the best translation among several ones existing in the bilingual dictionary is summarized as follows. The suitable translations of source query terms co-occur in the target language documents contrary to incorrect translations one. Consequently, we select for each set of the source query terms the best translation term, which frequently co-occurs with other translation terms in the target language. However, it is computationally very costly to identify such an optimal set. For that reason, we take advantage from an approximate Greedy algorithm as used in [START_REF] Gao | Improving Query Translation for Cross-Language Information Retrieval using Statistical Models[END_REF].We briefly summarize in the following the main principle of this algorithm. Firstly, and using the bilingual dictionary, we select a set T i of translation terms for each of the n source query terms {f 1 ,…,f n }. Secondly, we compute the cohesion of every term in each set T i with the other sets of translation terms. The best translation in each T i has the maximum degree of cohesion. Finally, the target query {e 1 ,…,e n } is composed of the best terms from every translation set.

Cohesion is based on the similarity between the terms. We transform the weighting measure EMMI to a possibilistic one (EMMI-POSS), which is successfully used to estimate similarity among terms. However, the measure EMMI-POSS does not take into account the distance between words. In fact, we observe that the local context is more important for the selection of translation. If two words appear in the same document, but in two remote locations, it is unlikely to be strongly dependent. Therefore, a distance factor was added by [START_REF] Gao | Improving Query Translation for Cross-Language Information Retrieval using Statistical Models[END_REF] in computing word similarity.

Illustrative Example

Let us consider the following French source query Q: {L'Union Européenne et les Pays Baltes}. Indeed, we have a set of possible translations for each term in the query Q from the used dictionary. The term "union" has two possible translations (union, unity), the term "Européenne" has the unique translation (european), the term "pays" has two possible translations (country, land) and the term "Baltes" has the unique translation (Baltic). In fact, Given the source query Q, we generate the set of possible translations combinations from a bilingual dictionary. In this example, there are 4 possible translation combinations (cf. table 1). The best translation is which has the greater possibilistic score. Table 2 and give detail of calculus. Probability values in table 2 and 3 are very low comparing to the possibility ones. So, they have a poor discriminative effect in the selection of the suitable translation. Consequently, we risk having very close probabilistic similarity scores, in which ambiguity translation cannot be correctly resolved. Moreover, the selected English translation of the given French source query {union, européenne, pays, balte} is the target Enlish query {unity, european, country, baltic}. We remark here that the suitable translation of the name phrase (NP) "union européenne" is not "European unity" but "European union". Consequently, we mainly need to identify the NP in the source query and translate them before translating one-word terms.

Experimental Evaluation

Our experiments are performed through our possibilistic information Retrieval System [START_REF] Elayeb | Towards a Possibilistic Information Retrieval System Using Semantic Query Expansion[END_REF], and implemented using the platform Terrier2 . It provides many existing matching models such as OKAPI and a new possibilistic matching model proposed by [START_REF] Elayeb | Towards an Intelligent Possibilistic Web Information Retrieval using Multiagent System[END_REF]. We propose and compare here our results using these two matching model in order to study the generic character of our approach.

Experiments are achieved using a subset of the collection CLEF-2003. This part includes articles published during 1995 in the newspaper "Glasgow Herald". This collection consists of 56472 documents and 54 queries, forming 154 MB. We only take into account the part <title> of the test queries, because it contains several isolate words, which are suitable to experiment our approach. However, we plan to consider other part of queries such as <description> and <narrative>, in which the context is relevant in the translation process. To evaluate our possibilistic approach, we compare our results to some existing probabilistic similarity measures such as T-score (TS) [START_REF] Church | Lexical Acquisition: Exploiting On-Line Resources to Build a Lexicon[END_REF], Log Likelihood Ratio (LLR) score, [START_REF] Dunning | Accurate Methods for the Statistics of Surprise and Coincidence[END_REF], Dice Factor (DF) [START_REF] Smadja | Translating collocations for bilingual lexicons: a statistical approach[END_REF] and Mutual Information (MI) [START_REF] Daille | Approche mixte pour l'extraction de terminologie : statistique lexicale et filtres linguistiques[END_REF].

Table 4 contains statistics on two elements u and v which are in this case, the components of an expression. O 11 is the number of co-occurrences of u with v. O 12 is the number of occurrences of u with an element other than v, etc.

N = R 1 + R 2 = C 1 + C 2 . ( 11
)
We also calculate the expected frequency of collocation as follows:

E 11 =(R 1 *C 1 )/N (12)
The LLR,MI, TS and DF score are calculated as follows:

) ) r , C , L(O * ) r , C , L(O r) , C , L(O * r) , C , L(O log( -2 v) LLR(u,
The proposed approach is assessed using the mean average precision (MAP) as a performance measure. The formula of computing the MAP is the following:

= = = N j Q i i j j doc P Q N MAP 1 1 ) ( 1 1 (18)
Where: Q j : The number of relevant documents for query j; N: The number of queries; P(doc i ): The precision at the i th relevant document.

Moreover, we compare the possibilistic approach (EMMI-POSS) both to monolingual IR task and to others probabilistic similarity measures, using OKAPI and Possibilistic matching models (Figure 2 and 3, respectively). In fact, we used the precision (Y-axe) over 11 points of recall in the X-axe (0.0, 0.1, ..., 1.0) to draw all recallprecision curves.

Using OKAPI (figure 2) or the possibilistic (figure 3) matching model, results in both figures show that the possibilistic query translation approach has the closest recall-precision curve to the Monolingual task, which confirm its effectiveness comparing to other probabilistic approaches. Indeed, the discriminative character of the possibilistic approach improves its ability to solve the problem of query translation ambiguity and consequently enhance its efficiency.

On the other hand, the mean average precision of EMMI-POSS (0.23) is very close to that obtained for the Monolingual (0.24) and that obtained for TS (0.21). The LLR metric has the worst result (0.15). These results are also confirmed using the possibilistic matching model. Indeed, results in figure 3 prove that the mean average precision of EMMI-POSS (0.165) is very close to that obtained for the Monolingual (0.17). The LLR metric stays also the worst one with 0.104. In fact our approach for CLIR has some drawbacks such us: (i) the limited coverage of dictionary and; (ii) The complexity of the algorithm allowing to choose the suitable translation among the set of the translations proposed by the dictionary. To overcome these limitations, we exploited the cohesion between a given query term and its possible translations in the training corpus and a particular similarity score measure to select the suitable translation of each query term. However, the results were mainly influenced by the specific properties of the used document collection.

Conclusion

In this paper, we presented a possibilistic query translation approach based on the cohesion between the translations of words. This approach is based on probability/possibility transformation improving discrimination in the selection of suitable translation. Besides, this transformation did not increase the complexity such as in [1][2]. We have tested and compared several similarity scores to improve query translation based dictionaries in CLIR. The idea of applying possibility theory to query translation is identical to the use of probabilities in the Bayesian probability model. In fact, it is necessary to evaluate many parameters, a task that cannot be compatible with poor data. The problem of accurately estimating probability distributions for probabilistic query translation is important for the accurate calculation of the probability distribution of translations. However, due to the use of the product to combine probability values (which are frequently small), the probability estimation error may have a significant effect on the final estimation. This contrasts with the possibility distributions which are less sensitive to imprecise estimation for several reasons. Indeed, a possibility distribution can be considered representative of a family of probability distributions corresponding to imprecise probabilities, which are more reasonable in the case of insufficient data (such as the case when some words do not exist in the bilingual dictionary). Furthermore, we no longer need to assume a particular form of probability distribution in this possibilistic reconciliation process.

  List of possible combinations C of translations of each query English corpus CLEF-2003 Computing Similarity SIM(x,y) Computing Cohesion(x, X) Computing Score(x) Selection of the best Score(x) English Query p(x), p(x, y) p(x), p(x, y) Translation Bilingual dictionary π(x), π(x, y) French Query Couples of combinations extracted from C Computing c(x) Computing c(x, y) Computing probabilities distributions List of translations of each term of source query Computing possibilities distributions by probability/possibility transformation

Fig. 2 .Fig. 3 .

 23 Fig. 2. Recall-Precision curves of Monolingual vs. All similarity measures (OKAPI)

Table 1 .

 1 Translation combinations for {L'Union Européenne et les Pays Baltes}

	Translation Combinations

Table 2 .

 2 Possibilistic similarity scores for the different pairs of words (x, y)

	Pairs of words (x, y)	C(x, y)	P(x, y)	(x, y)	SIM(x, y)
	union-european	1317	0.2642	9.3428	34.0590
	union -country	209	0.0442	4.9091	12.9894
	union -baltic	6	0.0583	5.5669	43.4782
	european -country	535	0.0894	6.6168	20.0428
	european -baltic	5	0.0485	5.1314	39.2299
	country -baltic	8	0.0872	6.5532	51.9453
	union -european	1317	0.2642	9.3428	34.0590
	union -land	1	0.0077	1.5429	2.2342
	union -baltic	6	0.0583	5.5669	43.4782
	european-land	51	0.0134	2.3534	4.7296
	european -baltic	5	0.0485	5.1314	39.2299
	land -baltic	1	0.0097	1.8719	12.3381
	unity -european	15	0.0380	4.5408	25.4750
	unity -country	10	0.0282	3.8353	20.3097
	unity -baltic	0	0.0	0.0	0.0
	european -country	535	0.0894	6.6168	20.0428
	european -baltic	5	0.0485	5.1314	39.2299
	country -baltic	8	0.0872	6.5532	51.9453
	unity -european	15	0.0380	4.5408	25.4750
	unity -land	1	0.0024	0.5520	1.6403
	unity-baltic	0	0.0	0.0	0.0
	european-land	51	0.0134	2.3534	4.7296
	european -baltic	5	0.0485	5.1314	39.2299
	land -baltic	1	0.0097	1.8719	12.3381

Table 3 .

 3 The final possibilistic score of each possible translation

	Possible translations of word x	C(x)	P(x)	(x)	Score (x)
	union	9894	0.0148	0.8499	14.0363
	unity	455	0.0006	0.1058	50.9500
	european	11121	0.0165	0.8784	119.0682
	country	13469	0.0204	0.9228	103.8907
	land	5592	0.0083	0.6653	24.6762
	baltic	108	0.0001	0.0291	186.5989

Table 4 .

 4 The contingency table

		t 1 = v	t 1 v
	t 2 = u	O 11	O 12
	t 2 u	O 21	O 22
	We have also:
	R 1 = O 11 + O 12	(7)
	R 2 = O 21 + O 22	(8)
	C 1 = O 11 + O 21	(9)
	C 2 = O 12 + O 22	(10)

http://www.reverso.net/text_translation.aspx?lang=FR

http://terrier.org/


G De Valicourt
email: guilhem.de_valicourt@alcatel-lucent.com

S Chandrasekhar

J H Sinsky

C-M Chang

Y K Chen

M A Mestre

Y Pointurier

S Bigo

J.-M Fedeli

H Duan

Monolithic Integrated Reflective Polarization Diversity SOIbased Slot-Blocker for Fast Reconfigurable 128 Gb/s and 256 Gb/s Optical Networks

We demonstrate a novel fully integrated, silicon-on-insulator, 16-channel polarization diversity fast reflective slot-blocker, which contains more than 65 integrated functional elements with nanosecond switching time. We assess its suitability for metropolitan networks with reconfigurable connections.

Introduction

Today's packet Ethernet metropolitan networks are either very static and highly over-provisioned or require many optoelectronic conversions and electronic switching hardware. Elastic optical network (EON) [START_REF] Yoshida | Proc. OFC'14[END_REF] as well as optical packet switching (OPS) [START_REF] Chiaroni | [END_REF] has been proposed for next-generation of ultrafast, energy-and resource-efficient data transport systems with fast reconfigurable connections. In both proposals, one common implementation is based on wavelength-blocker (WB) technology with broadcast & select approach. The WB or slot-blocker (SB: fast WB) is one of the main building blocks, however, its cost remains high when implemented with discrete components. Photonic integrated circuits (PICs) are expected to provide large cost savings and silicon photonics is a promising option providing large-scale integration of photonic components with high-volume manufacturing compatibility. Integration of silicon-based variable optical attenuator (VOA) combined with silica arrayed waveguide grating (AWG) [START_REF] Nishi | Proc. ECOC, paper We[END_REF] or III-V on silicon semiconductor optical amplifier (SOA) with siliconon-insulator (SOI)-based AWG [START_REF] Valicourt | [END_REF][START_REF] Raz | Proc. OFC'13, PDP5C[END_REF] was proposed in order to build 1xN switching fabrics (with N+1 ports). However, a low-port-count package is desirable to overcome cost barriers in PIC module packaging. In addition, SOI-based integration of the AWGs and VOAs is more promising for the cointegration of the photonics and electronics on the same circuit in the future. Recently, we reported a first SOI-based monolithically integrated slotblocker in a 2-port package [START_REF] Valicourt | Proc. ECOC'14[END_REF] . However, only single polarization (SP) devices were realized and an extinction ratio (ER) no larger than 10 dB was obtained, thereby limiting the blocking/adding functionalities to 80 Gb/s SP-QPSK optical channels. In this paper, we propose and demonstrate a 16channel monolithic integrated silicon-based reflective dual-polarization slot-blocker (R-DP-SB) with only a 1-port package. The integrated device performs polarization and wavelength demultiplexing with sub-wavelength switching capability. The reflective-based design shows an ER improvement up to 6 dB compared to our SP device [START_REF] Valicourt | Proc. ECOC'14[END_REF] , compact footprint (1.7 x 3.9 mm 2 ) and fast switching capability (< 10 ns). We demonstrate an add/drop operation at a record 256 Gb/s line rate per channel for monolithic SOI-based SB. The compact silicon photonic circuit integrating one double polarization grating coupler (DPGC), two AWGs (200 GHz channel spacing), 32 highspeed VOAs and 32 large-band Bragg grating mirrors (BGMs) was designed and fabricated. Fig. 1 (a) shows a photograph of the PIC. The size of the full circuit was 1.7 × 3.9 mm 2 , making it the smallest reported 200Gb/s-capable integrated 16channel slot blocker. For the first time, our reflective configuration allows for a 1-port packaging solution. The fabrication process was similar to the one detailed in our recent paper [START_REF] Valicourt | Proc. ECOC'14[END_REF] . At the input/output of component, light is split/combined into two orthogonal polarization components using the DPGC. Each component is aligned with the TE mode of two identical PICs, side-by-side on the same chip. Polarization independent operation can be achieved by synchronously driving the two PICs. The coupling efficiency of the DPGC with a single mode fiber was around 6 dB and the polarization dependent loss (PDL) around 0.5 dB. The total insertion loss is around 22 dB, which can easily be compensated with an Erbium Doped Fiber Amplifier. The experimental set-up is represented in Fig. 1(b). We used a commercial format and rate adaptable coherent transponder to generate and detect PDM-QPSK or PDM-16QAM modulation formats at 128 Gb/s or 256 Gb/s [each at 32 Gbaud that includes 28% overhead for soft-decision (SD)-forward error correction (FEC)], respectively. The transmitter had a tunable laser and the modulation format was spectrally shaped with a root-raised-cosine roll-off factor of 0.4. An optical circulator is used to direct incoming signals towards our single input/outputport integrated R-DP-SB, and outgoing selected channels from the device towards following nodes. A VOA and a noise loading stage were placed before the coherent receiver to adjust the optical signal-to-noise ratio (OSNR) level and the optical power of received signal. Received data was processed in real-time using the commercial coherent receiver.

Device design and experimental set-up

Device characteristics

The passband output spectra of all 16 channels are plotted in Fig. 2(a) when injecting a dualorthogonal-polarized signal. The AWG was designed with 200 GHz spacing from 1523.3 to 1546.2 nm. The excursion of insertion loss across the spectrum is found to be 2.7 dB. Then we excite the R-DP-SB along one specific polarization using a polarization controller. We turn on only the VOA corresponding to one optical path in order to align the polarization with one of the two PICs. The maximum measured PDL of the entire device is around 1.5 dB, which can be compensated by the VOAs at each polarization. Fig. 2(b) reveals a small mismatch between the two AWGs inducing polarization-dependent wavelength shift. We inject a PDM-QSPK signal and detune its frequency respect to the AWG-channel central frequency when passing passively through the device (that we label as "Through"). The pre-FEC bit error rate (BER) is shown in Fig. 2(c) for a fixed signal OSNR of 19.5 dB in 0.1 nm. When the channel frequency is detuned beyond +20-GHz, an error floor is observed at a BER of 4.5x10 -3 due the severe degradation of one polarization [Fig. 2(f-B)], which is not observed when detuned beyond -60-GHz [Fig. 2(f-A)]. However, the overall transfer function exhibits a large flat region in the center with a 3-dB bandwidth of more than 85 GHz allowing device

System performances

Fig. 3(a) show the results of the transmission experiment in terms of BER versus the relative OSNR in 0.1 nm for 128 Gb/s PDM-QPSK and 256 Gb/s PDM-16-QAM signals in back-to-back, through or drop/add operations. Notice that during drop/add operation we measure the added channel after blocking the dropped channel (which residual creates in-band crosstalk). The back-to-back OSNR corresponding to the BER at the FEC threshold for PDM-QPSK is used as a reference and set to 0dB, and all other OSNR measurements are plotted relative to this reference. Insets in Fig. 3(a) show six exemplary constellations. In all cases, both polarizations are well recovered confirming the polarization diversity scheme of our device. All PDM-QPSK measurements show performances well below the 1.5x10 -2 BER limit (SD-FEC threshold). Less than 1-dB OSNR penalty was measured when dropping and adding PDM-QPSK format. In contrast, PDM-16QAM, though providing increased data rate up to 256 Gb/s, is also more sensitive to in-band crosstalk.

Under "Through" operation, less than 0.5dB OSNR penalty was measured. However, when dropping and adding a new channel, an OSNR penalty of around 5 dB is observed at the FEC-limit. To cope with this penalty, optical power management rules have been investigated [START_REF][END_REF] . These rules suggest adjusting the channel power level as a function of the modulation format to maximize performance.

Conclusions

We have demonstrated the first 1-port package fully integrated silicon-photonics-based fast polarization diversity reflective-slot-blocker including 2 AWGs, 32 VOAs, 32 BRMs and one DPGC. We investigated the performance of this DP-R-SB in an optical network testbed with 128 Gb/s PDM-QPSK and 256 Gb/s PDM-16QAM signals and demonstrated its functionality for reconfigurable optical network.

Fig. 1 :

 1 (a) Integrated reflective dual-Pol. slot-blocker photography. (b) Experimental set-up with schematic of the add/drop functionality

Fig. 2 :

 2 Output spectra when injecting (a) two orthogonal polarizations combined (b) one single polarization at a time (superposed). (c) BER penalty for carrier detuning of 128 Gb/s PDM-QPSK signal. (d) Attenuation and (e) modulation response of a VOA depending on the injected current. (f) PDM-QPSK constellations illustrating the impact of the polarizationdependent wavelength shift of the two AWGs. optimal conditions. Then the two p-i-n VOAs corresponding to each channel were forward-biased. Fig. 2(d) shows the attenuation as a function of the injected current for all channels. A static ER up to 15.9 dB across the set of gates was measured for 80 mA bias current (with a minimum of 12.6 dB). Further ER improvements are expected by increasing the VOA section length and the doping level. Then a small signal modulation was applied to the VOA in order to determine the electro-optic (E/O) modulation bandwidth. The E/O modulation response is shown in Fig. 2(e) for several biases current. The -3dB E/O bandwidth is constant over the full-injected current range and measured to be 280 MHz [Inset of Fig 2(e)]. The measurement confirms the 10%-90% rise/fall time is less than 10 ns, in agreement with results reported in 6 made on a similar VOA structure.

  Such power management leads to a trade-off between decreasing the in-band crosstalk for the added channel at node A (PDM-16QAM) meanwhile increasing it for the added channel at node B (PDM-QPSK) [Fig. 3(b)(1)]. We studied the impact of the power management on the BER evolution [Fig. 3 (b)(2)]. By increasing the optical power of the added channel in node A, the BER for PDM-16QAM is improved and former values below the FEC limit are achieved. On the contrary, the BER for the PDM-QPSK is degraded and moves closer to the FEC limit. A sweet spot can be defined when both curves intercept. Under such a scenario, we measured the BER as a function of the relative ONSR and the results are shown in Fig.3(b)(3). Both signals show performances well below the SD-FEC limit. The ONSR penalty for PDM-QPSK is increased to 6.2 dB meanwhile that for the PDM-16QAM is reduced to 3.5 dB.

Fig. 3 :

 3 Experimental results of BER with respect (a) to the relative OSNR in Back-to-Back, through and add/drop configurations, (b(1)) Schematic of optical power management scenario. Experimental results of BER with respect (b(2)) to the In-band crosstalk and (b(3)) to the OSNR in optimal add/drop configuration for PDM-QPSK and PDM-16QAM signals.


We demonstrate burst mode functionality on a continuous commercial receiver piloted by real-time control plane in an end-to-end sub-wavelength switching test-bed. The results show the receiver can maintain its continuous performance with marginal penalty regardless of data burst absence duration.

Software-Based Burst Mode Reception Implementation for

Time-domain Wavelength Interleaved Networks Lida Sadeghioon [START_REF] Sadeghioon | First Experimental Demonstration of Real-Time Orchestration in a Multi-Head Metro Network[END_REF][START_REF] Qiu | Burst-mode receiver technology for short synchronization[END_REF] , Paulette Gavignet [START_REF] Sadeghioon | First Experimental Demonstration of Real-Time Orchestration in a Multi-Head Metro Network[END_REF] , Vincent Alaiwan [START_REF] Qiu | Burst-mode receiver technology for short synchronization[END_REF] , Laurent Bramerie [START_REF] Qiu | Burst-mode receiver technology for short synchronization[END_REF] , Esther Le Rouzic [START_REF] Sadeghioon | First Experimental Demonstration of Real-Time Orchestration in a Multi-Head Metro Network[END_REF] , Jean-Luc Barbey [START_REF] Sadeghioon | First Experimental Demonstration of Real-Time Orchestration in a Multi-Head Metro Network[END_REF] , Thierry Guillossou [START_REF] Sadeghioon | First Experimental Demonstration of Real-Time Orchestration in a Multi-Head Metro Network[END_REF] , Eric Borgne [START_REF] Qiu | Burst-mode receiver technology for short synchronization[END_REF] , Sébastien Lobo

Introduction

Switching sub-wavelength entities inside the big pipes channels appears as a promising solution for the operator that has to build a network with an efficient filling and different services.

Access to the sub-wavelength granularity directly at the optical layer is an alternative to electrical solution to reduce cost and power consumption by saving on electrical transit and electrical-to-optical and optical-to-electrical conversions. Amongst the various Sub-Lambda Photonically Switched Network (SLPSN) solutions, Time-domain Wavelength Interleaved Networking (TWIN) is an interesting solution since it provides optically transparent subwavelength grooming at intermediate/core nodes, while the intelligence and processing power remains at control plane and the edge nodes 1 .

While synchronisation and scheduling are key functions of the TWIN control plane, fast tuneable laser (FTL) at source nodes and the burst mode receiver (BMRx) at the destination node are fundamental in TWIN data plane.

Due to the nature of the bursty traffic, variable durations of data absence at the receiver sides happen in a normal operation condition. This is a challenge for the BMRx functionality since low cut off frequency linked to capacitive coupling of electrical components at the receiver limits the data absence tolerance to a few hundreds of nano seconds.

Different BMRs have been proposed for Passive Optical Network applications which require quick response to incoming burst packets and high tolerance to the long Consecutive Identical Digit at the same time 2,3 . However, these solutions do not address the optical burst absence in particular.

One approach to resolve this issue is to send the stuffing bursts/signal from the source side towards destinations that are not occupied to fill the data absence. This method can cause source blocking in mesh/tree based topologies.

In other proposed solutions, the stuffing signal is injected electronically at the receiver side in the data absence period. This method needs relatively complex electronics sampling tools at the receiver side [START_REF] Neto | 10 Gb/s Continuous Clock and Data Recovery for Burst Mode Transmissions with Externally Modulated Laser[END_REF] . In previous work, we presented the implementation of the fundamental building blocks including synchronisation and scheduling in a real-time controlled plane at source side on TWIN based test-bed 1 .

In this paper we experimentally demonstrate a software-based burst mode receiver with high tolerance to data burst absence in an end-toend TWIN test-bed. Here we combine the key information in the control plane to drive a low cost optical local stuffing section and add the burst mode functionality to a continuous commercial receiver.

Real Time Orchestration

The core module of the control plane is the Central Control Entity (CCE). CCE takes the traffic matrix (considering, Service Level Agreements, and resiliency, etc. for the dimensioned network), the network topology and point-to-point propagation delays to calculate the scheduling (grant) files. Then it sends element control information (EC) including the grant file to all edge nodes, via a separate control channel. Each grant file contains:  Source Information (SI): to which destination (on which wavelength) at what time data burst should be sent and for how long.  Destination Information (DI): from which sources and for how long traffic comes; when the absence of traffic starts, and for how long it continues.

The CCE has global network knowledge and it is dynamically updated in case of changes (such as link updates, cuts, and traffic changes). Consequently SI"s and "DI"s are periodically updated and sent to all the edge nodes in a defined control cycle, that varies according to the size of the network. The Real-Time (RT) engine role at CCE and all edge nodes is to preserve the priority and switch on different cycles accurately.

The destination is notified about the duration of data absence thanks to DI message therefore at the receiver there is no need for a rapid per burst sampling to verify the beginning or presence of the signal for burst mode operation. Each node is prepared per control cycle for the local bust mode reception. This control architecture prevents complicated calculations and lessens the need for computing algorithms and resources at each edge node. In the following we show how this architecture mitigates the hardware limitation and adds burst mode functionality to an off-theshelf continuous receiver. Then at each node the grant files are received via control channel by RT engine and are passed to the FPGA section of each node. The critical role of RT engine is to keep the control message task timing and the grant files execution precisely.

Experimental set-up

FPGA section that is responsible for element function per source and destination sides has to pilot the source (tuneable laser) and destination side (optical local stuffing) of each node according to SI and DI.

The description of the data plane is in the following: the source comprises an Anritsu MT 1810A Pulse Pattern Generator (PPG). It generates data bursts of 4.5 μs data duration in PRBS 2

7 -1 with 205 ns preamble (2048 bits with 64 bits pattern in 32 bits in "1" and "0"), in addition to 38 ns of header (128 bits "1", 128 bits "0", 64 bits "1", 64 bits "0") in front of the burst and 19 ns (32 bits "0", 64 bits "1", 32 bits "0", 64 bits "1") as trailer. The guard time between the bursts is set to 300 ns at emission to compensate any clock inaccuracy and wavelength tuning time of the tuneable laser. As a result, at each 5.14 µs, a burst can be sent according to grant files at each source. The PPG electrical signal is modulated (by MZM in OOK-NRZ format) on the optical signal generated by the Finisar S7500 Modulated Grating Y laser (MG-Y) tuneable laser with a rapid tuning time between different wavelengths (less than 100 ns).

The Core Nodes (CNs) contain two fixed demultiplexers and two optical passive couplers.

The burst mode receiver is composed of an optical coupler that allows combining data signal coming from source side and local stuffing laser into the Finisar XFP EVAL board with the XFP module FTLX1812M3BCL.

Our proposed mechanism is the following: in absence of data burst at the receiver side, the control plane drives the optical stuffing laser which is in our case a continuous laser externally modulated by clock signal at 1 GHz.

Experimental Results

We first evaluate the data absence tolerance of the XFP receiver (without the proposed mechanism). Fig. 2 shows the BER performance of the receiver for PRBS 2 burst signal with data absence (for simplicity we call the data absence gap) from 300 ns up to 1 µs. The performance for the bursts with 300 ns gap is identical to the PRBS 2 15 -1 due to the mixture of long sequence of "1's and "0"s as preamble, header and trailer with 2 7 -1 PRBS as the burst body. Thus this receiver performs with no penalty for bursts generated with 300 ns guard time. As we increase the gap up to 500 ns the penalty increases up to 1.2 dB. Fig. 2 shows that a gap larger than 500 ns is not well tolerated by the receiver, and error floors appear. The effect of low cut-off frequency (several tens KHz) of the receiver deteriorates the quality of the received bursts to an unrecoverable limit for 1 µs gap.

Next, we implement our proposal of software based burst mode reception by providing SI and DI files to both sources and destinations. SI files indicate to S1, S2 when to transmit traffic towards D3 (@1558.17nm), D4 (@1556.56 nm), and DI triggers the local stuffing laser to fill the absence of data burst.

Fig. 3 shows oscilloscope traces of the signal (bursts combined with local stuffing) at the output of optical coupler that enters the XFP Rx (pink traces). Fig. 3 (a) and (b) subsequently show the signal with one and two data burst absence that are filled by local stuffing laser, at the receiver side. We can see the local stuffing signal is positioned exactly according to the DI file with the defined 300 ns guard time.

To perform the BER measurement, we generate a mask signal (blue traces in Fig. 3) to separate the burst data from the stuffing at the BER test-set. In Fig. 3 the 100 ns/div and 50 ns/div zoom scales illustrate the position of the mask signals right after the burst preamble where the header information starts.

Results show no penalty for 5.14 µs stuffing (data absence). Then we increase the data absence to 10.28 µs (corresponding to 2 stuffing signals). We obtain only a maximum of 0.5 dB penalty comparing to the reference (burst with 300 ns gap). This is due to slight variation of mean received power measurement in presence of optical stuffing burst.

Conclusions

We demonstrate a software-based burst mode reception implementing an end-to-end bit rate transparent control plane on a TWIN test-bed.

A penalty of 0.5 dB has been achieved for two bursts absence proving that a simple commercial XFP receiver used in continuous mode can cope with burst arrival rhythm with long absence, alleviating the constraints of low cut-off frequency of components.

Fig. 1

 1 shows the experimental setup for the above mentioned control plane at 40 MHz with a 9.95328 Gbps (STM64) data plane. The test bed consists of two source nodes: S1, S2 and two destination nodes: D3, D4 (the two destinations are identical; we present the results only for D3). The Control Plane part is as follows: the CCE includes a computer to perform scheduling calculations. The RT engine on the National Instrument (NI) PXI 1082 chassis and NI PXIe 7962R modules with two Xilinx Virtex-5 SXT FPGAs are divided between CCE, and the source-destination nodes. The FPGA section in the CCE side has the master role. It takes the phase information of each node (coming from the signal generator at each node) via EC1 and EC2 and sends the relative starting time to all the

Fig. 1 :

 1 Fig. 1: Experimental set-up

Fig. 2 :

 2 Fig. 2: BER versus average optical input power at RX.

Fig. 3 :

 3 Fig. 3: (a) and (b) One and two data burst absence combined with local stuffing. The mask signal (blue trace) shows the position of the mask versus the burst.

Fig. 4 :

 4 Fig. 4: BER versus average optical input power in Rx.

Acknowledgements

This work was partly funded by the DGCIS in the frame of the CELTIC-Plus project SASER-SaveNet.


Frédéric Conte

Philippe Klein

Michel Berengier

Investigating lateral porosity effect on air pumping noise from connected road cavities with CFD simulations

Keywords: Air pumping, Rolling noise, Porosity I-INCE Classification of Subjects Number(s): 11.7.1

Investigating lateral porosity effect on air pumping noise from connected road cavities with CFD simulations

INTRODUCTION

The interaction between the tyre and the road surface produces several noise generating mechanisms [START_REF] Sandberg | Tyre/road noise reference book[END_REF]. The impacts between the road asperities and the tyre tread cause tyre vibrations which produce the main noise contribution in the low frequency domain. Airflow-related mechanisms, often called air pumping in the literature, are considered to be responsible for the noise in the high frequency domain in usual driving conditions. These mechanisms can be either the volume variation of the cavities of the contact patch due to the tyre rubber deformation or the pressure variations due to air flow induced by the rolling of the tyre (cf. Figure 1).

Road surface characteristics such as texture and porosity may have a strong influence on the rolling noise levels and the relative contributions of the different mechanisms involved. The porosity of the road material (called "vertical" porosity) may induce noise reduction through absorption effect as well as overpressure release in the contact patch. Even on non-absorbing impervious road surfaces, the texture characteristics may substantially modify the voids in the contact patch and create a "lateral" porosity likely to reduce overpressures due to airflow-related mechanisms. As for a porous material, the lateral porosity may be complemented by a permeability characterizing the open lateral porosity or an airflow resistance.

Examples of measurements dealing with the permeability effect on the noise generation can be found in the literature. Ejsmont et al. have highlighted the horizontal porosity effect by showing a noise reduction when the number of longitudinal groove of a tyre tread increases [START_REF] Ejsmont | Influence of the tread pattern on tire/road noise[END_REF]. Koike et al. have shown the vertical porosity effect by measuring the pressure reduction in a tyre groove induced by a drainage asphalt pavement [START_REF] Koike | Generation mechanism of tire/road noise -Part 2: pipe resonance in tread groove of tire[END_REF]. The interconnected voids in the contact area allow air flow. So when the air trapped in the contact patch can flow out easily to the outside, the generated noise is lower. 1 frederic.conte@ifsttar.fr 2 philippe.klein@ifsttar.fr 3 michel.berengier@ifsttar.fr Inter-noise 2014 Figure 1 -Sketch of air pumping processes in tyre tread cavities. Green and blue arrows mean respectively tyre tread deformation and aerodynamic processes.

Air flow existing in the contact area decreases the pressure variations which can be generated by the air pumping mechanisms. In this paper, the study focuses on the effect of the permeability of dense road surfaces in the contact patch on air pumping noise. This effect is hereinafter referred to as "lateral porosity". However the behaviour of the noise generation on such surfaces could be extended to all porous road surfaces. CFD simulations of air pumping phenomenon are carried out for 2D and 3D academic configurations.

APPROACH

Context

Air flow related noise sources involved in tyre/road interaction are difficult to isolate in experiments. Numerical approaches allow the study of complex phenomena such as air flow in a complex geometry. Here Computational Fluid Dynamics (CFD) is used to study unsteady air flow. This work takes place within a general approach introduced in previous studies [START_REF] Conte | CFD modelling of air compression and release in road cavities during tyre road interaction[END_REF][START_REF] Conte | 3D CFD modelling of air pumping noise from road cavities with constant volume[END_REF] and presented in [START_REF] Conte | Modélisation CFD du phénomène acoustique de pompage d'air dans un contact pneumatique/chaussée[END_REF]. This approach consists in modelling aerodynamic mechanisms occurring in the air pumping process likely to induce different possible air flows in the cavities of the contact zone generating pressure variations. Two kinds of mechanisms inducing air flow can be distinguished: the rubber deformation and rigid surface displacements. In this paper only the latter is considered. Surfaces are considered rigid, i.e. without dynamic tyre tread deformation. The only noise generation mechanism is the tyre's rolling creating overpressure in the cavities in front of the contact patch by the boundary layer effect [START_REF] Conte | CFD modelling of air compression and release in road cavities during tyre road interaction[END_REF][START_REF] Conte | 3D CFD modelling of air pumping noise from road cavities with constant volume[END_REF][START_REF] Conte | Modélisation CFD du phénomène acoustique de pompage d'air dans un contact pneumatique/chaussée[END_REF].

Air flow is considered compressible and viscous. A numerical approach is chosen to handle complex configurations and simulations are carried out with a CFD code based on Navier-Stokes equations.

The strategy consists in taking into account academic configurations in order to understand the phenomena involved. The cavities are included only in the road surface and the tyre tread is considered as smooth. In order to easily investigate the effect of the lateral porosity in the contact zone, a simplified geometry of the road texture is defined as a plane surface with connected cavities. First a 2D parametric study is carried out in order to evaluate the influence of the air flow resistance on the aerodynamic noise generated. Then, the noise radiated by a 3D pervious road texture is simulated.

CFD Model

The CFD model used is similar to the model presented in [START_REF] Conte | 3D CFD modelling of air pumping noise from road cavities with constant volume[END_REF]. A smooth rotating tyre rolling over a series of connected cavities included in a smooth road surface is considered. The static deformation shape of a smooth tyre with a radius of 314 mm is taken into account and the reference frame is chosen at the centre of the wheel. Air flows are only generated by the surface displacement and the boundary layer effect. The air flow due to the wheel displacement is not considered.

The Navier-Stokes equations, the mass conservation law and ideal gas law equations are solved. Since the air flow is turbulent, an URANS (Unsteady Reynolds Average Navier-Stokes) approach is used to solve the average flow and model the turbulent component. The RANS model k-ω sst is chosen for its performance to model the flow close to walls [START_REF] Conte | Modélisation CFD du phénomène acoustique de pompage d'air dans un contact pneumatique/chaussée[END_REF].

The computational domain is a half-disk in 2D and a quarter of a sphere centred in the middle of the contact area in 3D. A symmetry condition is considered in 3D at the tyre symmetry plane normal to the lateral direction. A non-reflective boundary condition is set at the pressure outlet boundary. It is discretized with respect to fluid dynamics and acoustic wave propagation. The road is modelled as a sliding mesh zone. Equations are discretized with 2 nd order accuracy in time and space. Simulations are carried out with the software Ansys Fluent 14.5.

Air flow resistance

The open porosity of the road pavement in the contact patch causes the permeability to air flow. This air flow is curbed but allowed and induces a finite pressure loss. The porosity effect on the flow can be characterized by measuring this pressure loss ΔP for a chosen volumetric flow rate Q.

Air flow resistance R is defined as follows:

= ∆ (1)
The specific air flow resistance R s = RA and the air flow resistivity r = R s /L, with A and L respectively the inlet surface and the length in the flow direction of the sample material, are more often considered. The average flow velocity U is defined as U = Q/A.

The porosity φ considered here for a pervious material is defined by φ = U/v where v is the velocity in the pores of the material. It is the porosity related to the permeability, i.e. the porosity seen by the air flow. It differs from the volume porosity which is the percentage of the volume of pores.

The pressure loss can be determined analytically for laminar flow in academic configurations. The Reynolds number Re representing the ratio of the inertial forces to the viscous forces for given flow conditions is used to characterize the flow regime. It is defined by = / with ρ the fluid density, V the velocity, µ the fluid viscosity and D a characteristic length. For low Reynolds number, the pressure loss can be modelled using the Poiseuille's law.

In this paper, air flow resistivity is calculated analytically and numerically in order to check hypothesis done in analytical models and to evaluate in which velocity range inertial forces cannot be neglected. Numerical simulations of air flow resistance are carried out for static flow conditions.

STUDY OF THE POROSITY EFFECT ON AIR PUMPING NOISE IN 2D

As a first step, the lateral porosity effect is studied for 2D configurations in order to save computational time and to be able to carry out a parametric study. The defined surface consists of a series of interconnected open cavities. The connection between cavities is made with a thin air film. Air flow resistance is varied with the thickness of the air film. CFD simulations of air pumping mechanism are carried out. Finally the corresponding air flow resistivity is evaluated for each thickness value.

Configuration

The shape and size of the cavities are chosen to be similar to cavities of smooth actual roads. The cavities considered have the same triangular shape 2 mm deep and 2 mm wide. They are randomly distributed (cf. Figure 2). The distance between adjacent cavities varies from 2 to 8 mm with an average distance of 5 mm. The parameter chosen to control air flow resistance in the contact patch is the thickness h of the air film connecting the cavities. In 2D, this air film should be at the top of the cavities. However this means that there would not be any contact between the tyre and the road and thus would not be-realistic. Therefore the air film is placed slightly under the contact height at 0.3 mm.

Figure 2 -Sketch of the geometry of the series of connected cavities

The parametric study is performed for a rolling speed of 80 km/h. The thickness of the air film varies from 0 mm (no connections) to 0.5 mm. Six thickness values are considered and listed in Table 1. The corresponding porosity is determined relative to the depth of the cavities so φ = h/2 mm.

Table 1 -Channel thickness and corresponding lateral porosity for the studied configurations h (mm) 0 0.02 0.05 0.1 0.2 0.5 φ (%) 0 1 2.5 5 10 25

Air pumping simulation

Simulations are carried out for the six configurations. The analysis focuses on the calculated pressure inside cavities, air velocity in the connections and sound pressure at several locations. at the front and at the rear of the contact patch where air is respectively pushed and aspirated by the tyre. In the contact patch, this velocity is positive because air is going from the overpressure at the front toward low pressure at the rear. This velocity has a constant average for large channels. The velocity increases at the end of the contact patch for thin channels causing the pressure loss shown in Figure 3 (a). The flow rate is more important for large channels with lower air flow resistance. The corresponding Reynolds number for the largest channel is about 300; thus the flow is laminar in the contact patch for these configurations. It is to be noticed that air flow velocities are more important than acoustic velocities often used to characterize such porous materials. Finally the total sound pressure level at the rear and at the front is plotted as a function of the channel thickness in Figure 7 (a). As seen in Figure 4, the noise decrease is more important at the rear. Indeed, small thickness affects only the noise due the resonances at the rear. Above 0.1 mm the noises from the rear and from the front behave similarly. The noise generated at the front is about 2 dB stronger with a similar spectrum shape (cf. Figure 4). This noise propagating through the channel is radiated at the rear [START_REF] Conte | 3D CFD modelling of air pumping noise from road cavities with constant volume[END_REF].

The noise due to the resonance of the cavities at the rear of the contact patch which is dominant for almost closed cavities is rapidly reduced for a pervious road profile. Thus for 2D configurations, the noise is mainly generated at the leading edge radiating at the rear through the contact patch. This noise is also reduced when the channel thickness increases.

Air flow resistivity evaluation

For air flow with low Reynolds number in a channel, the velocity profile normal to the flow direction has a parabolic shape. The pressure loss due to friction forces can be modelled with the Poiseuille's law. For a flow between two parallel plates, the pressure loss ΔP can be written as follows:

∆ = 12 ℎ ( 2
)
where L is the length of the plates, h the distance between them and V the mean flow velocity. Therefore, for low flow velocities air flow resistivity (defined in section 2.3) due to a channel does not depend on the velocity. For the case of the road profile described in section 3.1, air flow resistivity in the contact patch can be modelled as follows:

= 12 ℎ + (3)
with L p the total length of the connecting channels, L the length of the road profile. φ is the porosity defined by φ= U/v where v is the velocity in the channel. The last term b stands for the contribution of the triangular cavities to the total resistivity of the road profile.

In order to more precisely evaluate the air flow resistivity for the road profile considered in realistic conditions, additional CFD simulations are carried out. Calculations are done for material samples 10 cm long for each channel thickness and several velocities. Air flow is considered static, laminar and incompressible. This last hypothesis is not taken into account for thin channels for which the Inter-noise 2014 compressibility of air is not negligible (cf. Figure 6). 3)). Air flow resistivity is very strong for the thinnest channel and decreases rapidly when the thickness of the channel increases. The model 1 corresponds to the resistivity only due to the channels (b = 0). The difference with respect to the CFD model ranges from 4% to 15% for respectively the smallest and the largest thickness. This difference can be approximated by the function Δr = 1.06φ -2.51 . This should mainly correspond to the contribution of the cavities b. This additional term is introduced in model 2. The air flow resistivity normalized by the value calculated at the 0.01 m/s velocity for an incompressible flow is drawn in Figure 6 (b) as a function of the flow velocity. For incompressible flow and low velocities, air flow resistivity is almost constant for all configurations as described by the Poiseuille's law. At 0.1 m/s, the variation is less than 2 %. Above 0.1 m/s air flow resistance increases more with the velocity. Figure 6 (b) shows an important compressible effect for small channel thicknesses (h < 0.1 mm) and high velocities. Air flow resistivity values corresponding to average and maximum velocity flow conditions during tyre's rolling simulations (cf. Figure 5 (b)) are also plotted. In rolling condition, the compressible effect can be neglected (for the thinnest channel flow is allowed only at the edge of the contact patch). However the velocity effect should be taken into account for the largest channels.

The sound pressure levels at the front and rear of the contact zone are plotted against the thickness values (Figure 7 (a)) and corresponding air flow resistivity values (Figure 7 (b)). For low air flow resistivity, the noise which is generated at the front propagates towards the rear through the contact patch and the pressure levels at the front are higher of about 2 dB than those at the rear. They can be modelled by the function log + with b 1 = 2.25 and b 2 = 8.31. For higher resistivity values, noise at the front stabilizes at the same level while the noise due to cavity resonances at the rear increases significantly. In this range it can be modelled by the function log + with a 1 = 6 and a 2 = -13.3.

CASE OF A 3D DENSE ROAD SURFACE

3D simulations of air pumping have been already carried out for closed cavities or a single open groove [START_REF] Conte | 3D CFD modelling of air pumping noise from road cavities with constant volume[END_REF]. The effect of the lateral porosity of the road on the air pumping noise is considered here in the simulation of the air pumping process for a 3D road texture. These aim at evaluating the noise generated by the aerodynamic mechanism considered for a pervious road surface and calculating the air flow resistivity of this surface.

Configuration

The road texture chosen is based on a road surface introduced in previous projects [START_REF]EC project: Integrated Tyre and Road Interaction (ITARI). FP6-SUSTDEV[END_REF][START_REF]DEUFRAKO project: Prediction and Propagation of Rolling Noise (P2RN)[END_REF] which is a low noise dense road surface with a controlled road texture [START_REF] Beckenbauer | Road surface and method for the production thereof[END_REF]. It consists of crossing oblique grooves with a Gaussian shape and a random distribution. This surface is supposed to reduce strongly the noise due to tyre vibrations as well as air pumping. This is a dense road surface but the grooves provide a lateral porosity to the surface and allow the drainage of the contact patch.

For reducing computational cost the rolling process is performed over a short road sample and a regular distribution of the groves is chosen. The road texture is also simplified considering a rectangular shape of the grooves with the same section area. These grooves have a square section with a width h = 1 mm. The distance between each other is d = 7 mm and they have an angle of 45° with the travel direction. The road sample considered has a half width of 10 cm and a length of 30 cm. A sketch of the groove pattern is given in Figure 8

Air pumping simulation

A simulation is carried out for a tyre passing at 80 km/h. Figure 9 (a) presents the pressure evolution calculated at the bottom of the grooves during the contact. The pressure signals calculated at different lateral locations in the contact zone have a similar shape. An overpressure is generated at the leading edge and the pressure drops at the entrance in the contact area. This overpressure is shown in

Air flow resistivity evaluation

As for the configuration of a 2D channel, the pressure loss due to air flow resistance in a pipe can be modelled for low Reynolds number with the Poiseuille's law. The pressure loss ΔP can be written in this case as follows:

∆ = 32 ( 4
)
where L is the length of the pipe, D h the hydraulic diameter and V the mean flow velocity. The 3D road texture considered in the contact patch can be modelled by a material made of several pipes. Then air flow resistivity can be written as follows: The flow conditions in the contact patch for tyre rolling are presented in Figure 11 (b). It is to be noticed that air flow is not uniform in the contact patch due to side effects. At minimum and maximum rolling conditions, resistivity corresponds respectively to 1.6 and 2.3 times the resistivity calculated at 0.01 m/s. The velocity effect is therefore not negligible in the estimation of the air flow resistivity involved in air pumping mechanism. Inter-noise 2014

= 32 ℎ + (5)

CONCLUSIONS

Even on dense road surfaces, the lateral porosity due to the road texture in the contact patch influences aerodynamic noise sources. A CFD model is implemented in order to investigate the effect of the lateral porosity on the air pumping noise. The 2D parametric study of the noise generated by the tyre rolling over a series of connected cavities highlights the effects of the air flow resistivity in the contact patch on the noise radiated from the leading and trailing edges. A simulation is carried out for a 3D dense road surface. Noise is mainly generated at the leading edge and radiated despite the permeability induced by the lateral porosity. The noise level remains rather low in this particular case.

The study of the air flow resistivity in the contact patch for several configurations brings to the light the influence of air flow velocity in the range encountered during the rolling in the contact patch.

  Figur passing phase, th cavities it is als overpres contact l contact. for the c

  Figure 4

Figure 5 -

 5 Figure 5 -Evolution of the relative air flow velocity in the contact zone for connected cavities configurations

2 Figure 6 -

 26 Figure 6 -Air flow resistivity calculated with CFD simulations for several flow velocities Figure 6 (a) shows the air flow resistivity calculated for each configuration and an incompressible flow at the velocity of 0.01 m/s. Results from CFD simulations are compared to the results of the analytical model (equation (3)). Air flow resistivity is very strong for the thinnest channel and decreases rapidly when the thickness of the channel increases. The model 1 corresponds to the resistivity only due to the channels (b = 0). The difference with respect to the CFD model ranges from 4% to 15% for respectively the smallest and the largest thickness. This difference can be approximated by the function Δr = 1.06φ-2.51 . This should mainly correspond to the contribution of the cavities b. This additional term is introduced in model 2.

Figure 7 -

 7 Figure 7 -Sound pressure level (P ref = 1 Pa, add 94 dB for P ref = 20 µPa) calculated at 20 cm at the rear and at the front of the contact zone as a function of the channel thickness (a) and air flow resistivity due to the lateral porosity (b)

  (a) and the geometry of the road sample and the tyre near the contact zone is shown inFigure 8 (b).

Figure 8 -

 8 Figure 8 -Geometry of the 3D road texture

  Figure 1

  Figure 11 -Evolution of the relative air flow velocity in the contact zone for connected cavities configurations

  with= √2 the length of the grooves, L the length of the sample. φ is porosity defined by φ= U/v where v is the velocity in the groove. In this case φ = 2h/d = 28.6%. b is the contribution of the grooves crossing to the total resistivity of the road profile. If this contribution is neglected air flow resistivity r = 2831.4 Pa.s/m 2 .Air flow resistivity is also calculated with a CFD model for several flow velocities. Simulations are performed for a material sample 10 cm long and 10 cm wide. Air flow is considered static, laminar and incompressible. Results are presented in Figure12. The evolution of air flow resistivity is almost linear and can be modelled by the function + with c 1 = 7.73•10 3 and c 2 = 3.21•10 3 . At low velocity the velocity dependency is slightly weaker. At 0.01 m/s, the analytical model without crossing grooves contribution (b = 0) underestimates air flow resistivity of 17%.

Figure 12 -

 12 Figure 12 -Air flow resistivity calculated with CFD simulations for several flow velocities for an incompressible flow. (x) and (o) represent respectively minimum and maximum flow conditions for tyre rolling calculated in section 4.2

ACKNOWLEDGEMENTS

Authors gratefully acknowledge the financial support from the French Environment and Energy Management Agency (ADEME) within the framework of the DEUFRAKO project ODSurf.

This work was performed within the framework of the Labex CeLyA of Université de Lyon, operated by the French National Research Agency (ANR-10-LABX-0060/ ANR-11-IDEX-0007).