J M Sprauel'

J M Llnares'

J Bachmann'

P Bourdet

Uncertalntles In CMM Measurements, Control of IS0 Speclflcatlons

Keywords: Coordlnate measurlng machlne, Uncertainty, Statlstlcal

In the scope of quallty control, accurate evaluatlon of measurement uncertalntles Is a real challenge to Improve the use d Coordlnate Measurlng Machlnes (CMM). In our work, a new method, bmsed on a statlstlcal approach of the prowem, was therelbre developed, to deduce Instmtaneous measurement uncertalntles dC redly from the set o f acqulred coordlnates. The covarlance matrbc of the lntrlnslc parameters whlch eharactertze each analyzed surface Is also evaluated, thus allowlng an accurate propagatlon d the measurement uncertalntles to the I S 0 specltlcatbns to be controlled. The experlments carrled out In our study Illustrate thls new statlstlcal approach and demonstrate its relevance.

INTRODUCTION

Coordlnate measurlng machlnes are now Mdely used to qualify Industrlal mrrkpleces. Nevertheless, the mtual CMM s o m r e Is usually restrlcted to the determlnatlon of mean values. Thls Is the case for both the charade+ zatlon of IndMdual surfaces and for the determlnatlon of geometrlc devlatlons. However, In accordance wlth quaC Ity standards, the uncertainty of e m h measurement should also be specmed [I]. Thls becomes Incremslngly Important In lndusthl routlne. For slmple processes, llke calllper or mlcrometer measurements, the evaluatlon of uncertalntles by a wnventlonal method as recommended by the GUM [2] Is stralghtfoward. However, thls procedure becomes extremely tedlous or even ImpossC ble for coordlnate measurements. Actually, the uncertalntles of such measurements are therefore Bnher deduced f r m repeated expensive experlments or estimated through numerlcd slmulatlons [3,4]. The latter methods requlre however to decompose the measurement prmess Into a set of elementary functlons and to ldentlfy a11 the assoclated Independent random variables. In addttlon, the lntrlnslc panmeters of the analyzed surfaces are then assumed to be Independent one of the other, thus leadlng to a wrong determlmtlon of the error bars of the I S 0 specmcdlons to be qualmed.

Moreover, these methods do not account for uncontrolled events and resuthg perturbatlons whlch may occur durlng the acqulsitlon. Another way to evaluate the uncertalntles of CMM measurements Is to use a statlstlcal approach of the problem. In fact, the set of dlgithed coordlmtes forms a statlstlcal sampllng of the true analyzed surface. It contalns therefore some mixed Informatlon about the dlst+ butlon of the materlal around the Ideal geometrlc e l e ment and about the qudlty of the measurement. Thls property hms already been polnted out b y dMerent authors [5,6.T], but has not yet been used to evaluate the uncertalntles of CMM measurements. A new method was therefore developed In our laboratory, to deduce Instantaneous measurement uncertalrtles dredly from the set of acqulred coordlnates [El. The covarlance matrix of the Intrlnslc parmeters whlch characterize each analyzed surface Is also evaluated, thus allowlng an accurate propagatlon of the measurement uncertalntles to the I S 0 specmcatlons to be controlled. The experL ments carrled out In our study wlll Illustrate thls new statlstlcal approach and All demonstrate the relevance of the methods developed In our work.

PRINCIPLE OF THE M€IHOD

Flttlng of elementarysurfacez

The Rrsl step requlred In the treatment of coordlnate measurements Is the descrlptlon of each d l g h e d surface by an Ideal hature. Each geometrlc entlty Is charactertzed by a set of p lrtrlnslc parameters 8; eoordlnates of the centre of the measured surface, coslnes of the normal to a plane or of the dlrectlon vector of an wls, radlus, angle of a cone, etc. The Wlng of the acqulred data comes thus to the optlmkatlon of these parameters 8, In order to obtdn the best layout of the measured coordlnates around the Ideal hature. It Is usually based on the mlnlmhatlon of the dstance dk between N acqulred polnts Mk and the assoclated geometrlc element.

DMerent procedures are used for that purpose llke the classlcal least squares method or the Tchebychev crlte don. In our study, these methods h m been edended to a statlstlcal approach of the problem [El. The dlstrlbutlon of the measured coordlnates around the Ideal feature Is charadartzed therefwe by its probablllty denslty functlon T(drJ. Accordlng to the mwlmum IlkelC hood erlterlon, the best statlstlcal estlmatofs A, of the parameters 8, have to mwlmhe the conditlonal probablC lty t $ of a11 the realhad Independent measurements:

N k=I # = n f ( d k ) I0 be m w l m h e d 3 -= 0 a,
We suppose now that a11 the systematic errors have been corrected In the acqulred data. Therefore, the devlatlons Included In the measured coordlnates just resuit from the conwlutlm badween statlstlcal perturbatlons of the coordlnate measurlng machlne and the dlstrlbutlon of the matter around the Ideal geometrlc e l e ment. Slnce the Instrument depends on a great number of uncontrolled parameters, the Rrst devldlm Is u w a l y assoelated wlth a normal law. The second cunponert Is more dif7lcuit to define. However, for hlgh quality surfaces, measurements carrled out on dmerent Industrlal pleces, have s h o M that the scatterlng of the matter around the Ideal geometrk element can then be re+ sonably approdmated by a Gausslan dlstrlbutlon. Thls Is a Rrst step of our statlstlcal approach, but other dlstrlbw tlons wlll be tested In the near Mure for mugh surhces. Under these assumptlons, the Ilkellhood criterlon slmplC The evaluatlon of the standard devlatlon ascomes thus to the determlnatlon of the Jacoblan matrix J . For that purpose, a generlc algorithm has been developed M l c h allows computlng its components whatever geometrk construdlon has been used to dartve the dlstmce 6.

EXPERIMENTAL APPLICATION

In order to valldate our new statlstlcal approach, dlPferent experlments have been carrled out In our labordory uslng a coordlnate measurlng machlne equlpped A t h a touch trlgger probe system mounted on an lndedng head. All the measurements have been conducted h programmed automatlc mode. The acqulsttlon speed was kept constant and set to haK the m d m m sampllng rate of the coordlnatemeasurlng machlne. Flgure 1 : Machlne checklng gauge system. Such a system, deslgned to test the volumetrk performance of a coordlnate measurlng mattine, permits an+ iyzlng the reference pkotlng arm In a great range of (@) Incllnatlons. Slngle polnt measurements were thus carded out for 24 evenly dlstrlbuted dlredlons. The acqulsltlons were repeated I 4 4 tlmes. Thls allowd. for each lncllnatlon of the system, to compute the covarlance matrix of the dlgitbed coordlnates, uslng classlcal statlstlcal formdae. Slnce the polnts were a m acqulred h the dlrectlon normal to the pkotlng arm, all the components of thls matrix were found of second order, except for the dlrectlon of measurement. The standard devlatlon of the p k o t h g radlus Is thus sulAclent to c h a r d e r h e the acqulsttlons. The resutts are presented In Table 1.

Table 1: Standard devhtlms of measurement In pm.

With a confidence level of 99 % , Fisher tests applied to this data demonstrate that the standard deviation can be considered as constant for all the scanned directions. The whole acquired points could therefore be used to characterize the stochastic noise of our coordinate measuring machine. Figure 2 shows the histogram of the deviations measured in this first experiment. This graph demonstrates that the random perturbations of our machine can be accurately described by a Normal distribution.

Uncertainties of elementaryfeatures

In the second step of our experiments the artifact of Figure 3 was tested to check our new statistical a p proach.

Figure 3: Artifact used in our experiment For this sample, all the planes were acquired in 20 evenly distributed pints. The cylinders were characterized by three circles defined by 16 pints. The measurements were repeated 151 times to allow the standard deviations of the results to be defined in a classical way. Figure 4 shows the results obtained for the testing of Plane P1 which is a surface of high quality. For this feature, the standard deviations were found to be the same for all the acquired points. The whole 151 x 20 digitized coordinates of the experiment were therefore used to define the histogram of the least squares optimization residues. This result has been compared to the data obtained for single p i n t acquisitions (Figure 5). Figure 6: Distribution of least squares residues of C1 Again, the distribution of the least squares residues is Gaussian. However, in that case, its standard deviation is about two times greater than the value found for single p i n t measurements. This is due to the form defect of the cylindrical surface, which was evaluated to 11 pm. Such result demonstrates now that the acquired coordinates also include statistical information about the distribution of the matter around the perfect ideal feature which is fitted to the measured points. The same type of resutts is obtained too for the t w a other circles.

0,301

It has however to be pointed out that the layout of the matter around the fitted feature cannot ahways be described by a normal distribution because it closely depends on the manufacturing process. In the general case the deviations included in the measured coordinates will then result from the convolution between the Gaussian contribution of the coordinate measuring machine and the process related geometrical surface defects of the analyzed sample. The characterization of the location deviation between cylinder C and plane P2 required finally to acquire this last surface

CONCLUSION

In our rmrk a new statlstlc a p p r o x h has been deveC oped to evaluate Instantaneous uncertalntles of coordC nate measurements. These uncertalntles are dertved from the resldue betwen the perfecl Ideal features Rtted to the acqulred polnts and the related dlgtthed mordnates. The method shows that due to the form defects of the measured surface, the devlatlons o f the resutts obtalned wtth a gken algorithm not only depend on the stochastlc nolse of the CMM but are also llnked to the polnts dlstrbutlon selected on the measured surface. The experlmental results obtalned In our study demonstrata clearly that the uncertalntles dertved from a slngle measurement uslng our statlstlcal method are very close to the v a l w s deflned by repeated tests. The Instartane ous uncerhlnty evaluated through our approach wlll t h s g k e a relevart lndlcator allowlng to check a w e n CMM control process In order to optlmhe Its procedures and experlmental condttlons. At present, the method Is llmited to the verltlcatlon of I S 0 1101 tolerances and geometrlc dB\rlatlOM. The stdlstlcal approach wlll now be extended to the control of envelop requlrements.

Res

  to the c1ass1cal least squares method and the optlmhatlon conditlons become: If the p parameters 8, o f the geometrlc element assoclated to the dlgithed surface were perfectly darned, the standard devlatlon rn could also be estlmated In the same way: However, such estimator would lead to a blased evaIu+ tlon of a because a set of p parameters 8, has already been dertved from the acqdred data. Therefore, the standard devlatlon of the measurement has to be cunputed wlth the followlng expresslon, also called resldue of the least squares optlmhatlon: Thls devlatlon 6 can be propagated to deduce the covariance matrix of the estlmated parameters d,, uslny equatlon (2) and the classlcal dmerentlal expresslons of the uncertalntles [2]. From the dlagonal components of the cowrlance matrix, the error bars of 8, are then easlly calculated, slnce the statlstlcal dlstrlbutlon of these random varlables corresponds to a Flsher-Student law. 2.2 Uncertalntles of I S 0 11 01 speemcatlons The covarlance matrix determlned m each elementary feature can now be used t o propagate the standard devlatlons of the Rtled surfaces to any dertved geometrk element. The uncertalntles of the dlmenslons and geometric devlatlms to be verlRed can thus be evaluated. At present, however, our method restrlds to the cortrol of I S 0 1101 specmcatlons. Accordlng to thls standard. each d h e M l # l and geometrlc error Is then quailfled by a dlstance 6. Thls dlstance 6 1s dertved from d b r e r t geometrlc construdlons and Is llnked to n of the parame tars 8, determlned by the Rttlng o f the elementary fa+ tures. Uslng a dmerentld f m u l d l m of its standard devlatlon as it comes: lntroduclng the Jacoblan matrix J of the dlstance Gand tts transpose J', thls expresslon can also be rewrttten as a matrix product: 4 = JCJ' .where J, =* and CI = Cov(e,.eI) (6) h,

3. 1

 1 Uncertalntlaz of slngle polnt measuremenfzThe uncertdntles obtalned In slngle polnt measurements have been characterbed Rrsl to deRne the random perturbatlons of the coordlnate measurlng machlne. A MCG checklng gauge was used for that purpose wlth a p l w t -Ing arm of 151 mm (Flgure 1).

FrequencyFigure 2 :

 2 Figure 2: Histogram of the stochastic noise of the CMM.This graph demonstrates that the random perturbations of our machine can be accurately described by a Normal distribution.

Figure 4 :

 4 Figure 4: Histogram of the residues of plane PI.

Figure 5 :

 5 Figure5: Comparison between the deviations obtained for single p i n t acquisitions and for testing of Plane PI. Both distributions are practically the same. This means that for surfaces with low form defect, like plane P1, the least squares fithng residues are directly linked to the stochastic noise of the coordinate measuring machine. It demonstrates clearly that the random deviations of the CMM are included in the set of acquired coordinates and can therefore be characterized by our statistical approach. The next experimental part is now dedicated to the control of the location deviation between cylinder C and plane P2. Three circles C1, C2, C3 have therefore been measured on the cylindrical surface to define the axis of this entity. Figure6shows the histogram of the least squares residues obtained forthe first acquired circle C1. 0.35 Frequency 0.301 0.25

Flgure 7 :

 7 Hlstogram of the resldues of plane Pz.Flgure 7 shows the hlstogram obtalned for thls entity. As for plane PI, due to the low form defect o f the surface, the resldues of the least squares Rttlng correspond to the stochastlc nolse of the coordlnate measurlng machlne.

3. 2

 2 Uncertalntles of geomeblc devlatlonsFrom each set of acqulsttlons carded out on clrcles C1, C2, C3 and plane Pz, the geometrk errors of cyllnder C could flnally be denned. Accordlng to I S 0 1101 star+ dard, the locatbn devlatlon of cyllnder C has been d e duced from the dlstances between the centers of clrcles C1, C2, C3 and plane P2. Slnce the experiment was repeated 151 tlmes, the standard devlatlms of these dlstances could also be computed In a cIass1caI way. On the other hand. as a l r e d y polnted out, our new statlstlcal approach allows also to estlmate the covarlance matrix of the Intrlnslc parameters evaluated for each elementary surface. Thls Mormatbn has been propagated to the calculated dlstances, thus deflnlng the standard devlatlons In a second manner. For each set of data, these values are then lust dertved from the 20 polnts acqulred to characterize plane P2 and the 3 x 16 coordlnates whlch denne cylnder C. The resutts are presented In table2. standard devlatlon urn) I c1ass1cal I deduced from I 1 method 1 residue I

Table 2 :

 2 Standard devlatlons of the measured dlstances. The devlatlons deduced from the resldue of the least squares optlmhatlon were of the same order for a11 the set of acqulred surfaces. Only thelr mean values were therefore reported In thls table. The resutts show clearly that the Instantaneous standard devlatlons deflned trough our new statlstlcal gproach are very close to the values calculated by a c1assIcaI method based on repeated measurements. Thls demonstrates clearly the relevance of our method.


Jean Hermetz
email: jean.hermetz@onera.fr

Michael Ridel
email: michael.ridel@onera.fr

Carsten Doll
email: carsten.doll@onera.fr

Carsten Döll

DISTRIBUTED ELECTRIC PROPULSION FOR SMALL BUSINESS AIRCRAFT A CONCEPT-PLANE FOR KEY-TECHNOLOGIES INVESTIGATIONS

Keywords: Distributed propulsion, electrical propulsion, overall aircraft design process OAD Electrical architecture, handling qualities

published or not. The documents may come

Distributed electric propulsion for small business aircraft

a concept-plane for key-technologies investigations.

Introduction

Environmental considerations, in terms of noise as well as pollutant emissions [START_REF] Acare) | Realising Europe's Vision for Aviation: Strategic Research and Innovation Agenda[END_REF] [START_REF]Flightpath 2050: Europe's Vision for Aviation, Report of the High Level Group on Aviation Research[END_REF], in addition to the potential reduction of carbon-based natural resources, lead to investigate the use of electric propulsion for transportation.

Generally based on a pragmatic approach, several manufacturers are investigating the possibility to substitute, on an existing airframe, piston engine(s) for a lithium-polymer or lithium-ion battery powered electric motor with a conventional propeller, connected to an electronic control unit. Performances, such as take-off distance, climb and cruise speed appear to be adequate for very light aircraft having a rather short range and low cruise speed, but a strong challenge appears when trying to extend the range beyond one hour of flight (excluding reserves): due to the energy density of such batteries, their mass increases rapidly leading to redesign the aircraft, larger and heavier, reducing the expected economic viability, for a same payload.

In order to contribute to the growth of this emerging market by investigating some potential solutions coping with the main issues of electric propulsion for aircraft, ONERA decided in 2011 to start an expert-based exploratory study, done in association with CEAtech. This expert-group concluded [START_REF]Rapport de synthèse du Groupe de Travail Études Prospectives[END_REF] that there is a potential for all-electric powered airplanes for civil transportation based on the association of several key-technologies integrated in a new airframe configuration using distributed propulsion, in addition to some changes in operational use. Breakthrough technologies concern: • Distributed propulsion; • Electric Ducted Fan (EDF); • Energy supplying, storage and hybrid capabilities;

• Command and control through the association of multi-motors and control surfaces; • Modular architecture and in-flight reconfiguration capabilities of the overall electric propulsion system; • Improved multidisciplinary design and optimization capabilities.

Several relevant sets of those key-technologies have been used in order to assess their performances and to show their pros and cons in an overall aircraft design approach. These assessments highlighted trends which led the expert-teams to conclude on the feasibility of electric powered aircraft using distributed propulsion. They also showed that the use of Distributed Electric Propulsion (DEP) adds some new interdisciplinary coupling but also opens new degrees of freedom for the design of airplanes which lead to new compromises. Assessments were done using a simplified multidisciplinary approach based on a tool able to model several kinds of Propulsion & Power Systems (PPS) and to introduce them into an OAD (Overall Aircraft Design) approach able to size, at a conceptual design level, an aircraft for a given mission, as illustrated in Fig. 1. Several missions, e.g. payload and range, were considered in order to scan the whole market of civil transport aircraft. In order to illustrate the results of such preliminary analysis, Fig. 3 shows the trends from the OAD approach for a regional aircraft with several possible energetic power chains. It focuses on a "regional" mission which consists of carrying 75 passengers on 1 000 km at a flight level (in cruise) of 5 000 m. Three technology-maturity levels are then considered, as referenced before. On this picture, the red marks correspond to two reference aircrafts, respectively ATR 72 and A320 (this last one assessed on this mission, e.g. with fuel suited for 1 000 km + reserves) [START_REF] Döll | Conceptual Feasibility Study for A Fully Electrically Powered Regional Transport Aircraft[END_REF].

Fig. 3: L0 OAD results for a regional mission Thus, if we consider for example a regional Aircraft using fuel cells as energy sources and distributed electric propulsion, the state-of-theart situation gives an aircraft weighting close to 57 tons and using about 100 GJ energy for doing its mission. Using 2030 assumptions, for the same mission it requires only 50 GJ, close to an ATR 72, and weighs 34 tons. Pushing assumptions at the most promising horizon, this Electric Regional Aircraft appears to be close to present ATR 72. Assessments done in that way have convinced both ONERA and CEATech experts that All-Electric-Aircraft (AEA) will be feasible and potentially affordable in the future. Hence, the key-technologies will have to be investigated in order to increase TRL and then to propose them to aircraft manufacturers.

Concept-planes overview

In 2014, a first pre-design exercise [START_REF] Hermetz | L'avion d'affaire personnel à propulsion électrique, un « Concept Plane » ? Aero-Club de France[END_REF] has been done in order to illustrate the potential of such innovations in a first application-case based on the recent results of the UE funded PPlane project [6] dedicated to Personal Plane. Indeed, the need for a 4 to 6 seats small business aircraft, operated from downtown or close to urban area, able to cover ranges from 400 to 500 km in about two hours at low cruise altitude, up to 3 000 m AMSL (Above Mean Sea Level), has emerged from this project, with some requirements in terms of automation in order to be used by everybody without specific skills and qualification.

On the basis of this Top Level Aircraft Requirements (TLAR), an ONERA's engineer team has designed, at a conceptual level, two concept-planes of AEA which illustrate the compromise resulting from the use of several of the breakthrough technologies mentioned previously (Fig. 4 & Fig. 5).

Main Characteristics

Starting from main operational characteristics (TLAR) compliant with the CS23 regulations, an iterative multidisciplinary design process has been used to determine the main aircraft design characteristics (see Fig. 6):

• The propulsion is performed through 40 EDF located along the wing span in order to increase aerodynamic lift in low speed conditions, giving some STOL (Short Takeoff and Landing aircraft) capabilities. Indeed, distributed propulsion promises dramatic increases in aerodynamic and propulsive efficiency, and potentially noise reduction.

• The propulsive force is also used to mainly control yaw and roll effects allowing stabilizers size reduction and finally, aircraft weight saving. However, it requires combining EDFs properly to ensure control laws (lateral stability). Flight performance analysis shows that the propulsive force must be controlled symmetrically at the same time and also in case of EDF failure on both sides of the wing.

• To be compliant with the CS23 certification rules and more particularly during the climb step in case of engine failure, flight performance analysis has shown that only 32 operational EDF are required.

• No complex Environmental Control System is required due to flight level (altitude < 3000 m).

• In our flight configuration, the on-board energy has been defined as follow:

• Starting from the greatest propulsive force required during the take-off and considering electric motor (97 %) and engine power unit (95 %) efficiencies, an electric power of 400 kW is required;

• For a range of 400 km, the consumed energy has been estimated with the following assumptions: 17 min for climb step (70 km), 78 min (330 km) for cruise and the descent steps and, roughly, 15 min for the safety reserve.

To perform this flight, 400 kWh are necessary for the propulsion which leads, considering the other consumers, to a total energy of 500 kWh.

• The different scenarios evaluated through the multi-disciplinary approach show that the Polymer Exchange Membrane hydrogen Fuel Cell (PEMFC) concept is the more promising solution for the considered TLAR for providing the electric power (both for propulsion and systems), with the help of a battery pack for instantaneous power demands.

Propulsion and Power System Architecture

An aircraft results from compromise between several viewpoints in order to fulfil some requirements, e.g. mission objectives and safety constraints. Conventionally speaking, this compromise concerns aerodynamics, structure, propulsion, performances and handling qualities, acoustic considerations and so on. For an AEA, beyond those considerations, several new coupling aspects appear with also new degrees of freedom in the design space. The required compromise comes from an iterative and multidisciplinary approach which considers all of these aspects. The following explanations regarding the main characteristics of the designed Propulsion and Power System (PPS) architecture are the result of this iterative multidisciplinary approach.

Distributed Propulsion Architecture

The first step is to define the optimal distributed propulsion architecture which would be compliant with the CS23 certification rules but also optimized to participate in the motion control of the airplane during flight.

As explained previously, the propulsive force must be controlled symmetrically at the same time on both sides of the wing. Consequently, starting from these considerations, an advanced propulsive architecture has been identified consisting in 10 clusters of 2*2 EDF as shown on Fig. 8 (one color for each cluster). Each EDF is also controlled individually which allows reconfiguration of the overall electric propulsion system. A CONCEPT-PLANE FOR KEY-TECHNOLOGIES INVESTIGATIONS Hence, a failure of one EDF -basic OEI (One Engine Inoperative) case -leads to the lack of a very small fraction of the thrust (1/40). Furthermore, the failure of one cluster of EDF leads to a lack of a limited fraction of 10 % of the overall thrust, and in that failure-case, the bi-symmetrical allocation of EDF along the span avoids any dissymmetrical thrust, which is critical for safety issues.

Power Architecture

The next step is to design a safe and optimized advanced power architecture (Fig. 9) relevant with the EDF clustering. Aiming to reduce the common failure points, each EDF cluster is powered by its own fuel cell system (PEMFC and high pressure hydrogen tank), battery stack with its Energy Management System (EMS) and its own electrical wiring interconnection systems (EWIS). To reduce the power architecture weight, a High Voltage Direct Current (HVDC at 135Vdc) distribution is chosen between fuel cell (available output level)/battery stack and EDF. This choice reduces the number of power conversion steps (DC/AC and AC/DC) and the number of wires in the power cables (two phases instead of three phases). As a result, an electrical system based on 10 primary power distributions has been selected, in which each primary distribution is composed of Busbar, Solid State Power Controller (SSPC) modules allowing electrical load control remote and cable protection, cable harnesses and inverter (DC/AC) at EDF level.

To supply the power to the other systems, two secondary distributions (called essential and non-essential) are designed with a 28 Vdc voltage. Each of them is connected to one primary distribution via a SSPC module and a DC-DC converter (135 Vdc to 28 Vdc). The essential secondary distribution is also connected to a dedicated li-ion battery system (autonomy 20 min) allowing to supply the power to the main bus if the two primary distributions are out of order. The two secondary distributions are linked by a Bus Tie Breaker (BTB) to transfer the electrical power between the non-essential and the essential buses.

To evaluate the electric power required by all others consumers, the embedded power of the Cirrus SR22 (2.4 kW) has been used as a reference to which additional power, roughly 1.6 kW, has been added for the new on-board systems (high demanding and redundant Flight Control System). Taking into account the redundancy of the power system, an additional capacity of 8 kW has been taken into account for the hydrogen fuel cells.

Components evaluation

The next step is now to evaluate the main characteristics of each component of our proposed advanced power architecture.

First, each fuel cell unit system is designed to provide a power of 40 kW (to supply 4 EDF, 10 kW each), except two fuel cell systems (44 kW) to supply in addition on-board equipment.

To reduce the PEMFC weight (and volume) and preserve the power capacity at different flight levels (from ground up to 3 000 m), the inlet pressure has been set to 1.8 bars. The increasing of fuel cell pressure allows raising its rated power. This 1.8-bar pressure rate results from the use of two air compressors. In these conditions and with a fuel cell efficiency of 0.6 a power density of 1.8 kW/kg is assumed. Thus, the gross weight of the PEMFC system (i.e. 10 fuel cells with their hydrogen tanks, associated with air compressors) is about 226 kg and its volume reaches 1 m 3 . For an embedded energy of 500 kWh, it needs to store 30 kg of hydrogen (at 700 bars) in 10 carbon fiber composite (CFC) material tanks of about 25.5 kg and 0.051 m 3 each (with a diameter and length of 0.3 m and 1.63 m respectively).

The instantaneous power demands will be assumed by battery packs which are linked in parallel to each fuel cell systems and controlled by its EMS. In our case, the "dynamic" part has been estimated at 10 % of total propulsive energy of our flight configuration either 40 kWh. Considering an energy density of 300 Wh/kg, we obtain a battery packs weight of about 133 kg.

Second, each EDF supply chain is protected by a SSPC module of 10 kW under a HVDC voltage of 135Vdc. Based on the assumption that commercial SSPC modules will be used, a power density of 15 kW/kg has been estimated from data sheets, leading to a SSPC weight of about 27 kg.

From the aircraft geometry defined by CAD, the power harnesses length of the propulsive part is close to 114 m. The environmental flight conditions (altitude) and installation characteristics analysis, give a wire gauge of "8" with an average linear weight of 0.130 kg/m. The corresponding cables weight is about 39 kg including their installation penalties (estimated at 30 % of the cable weight).

The overall weight of (DC/AC) inverters located in front of EDF is about 100 kg with a power density close to 4 kW/kg. Finally, the assumption that a power density of 5 kW/kg was available at EDF level has been done and thus the EDF system weight about 80 kg. The total weight of advanced power architecture about 890 kg has been summarized in Fig. 10.

DEP investigations

In order to start investing some of these technologies, ONERA recently decided to focus effort on the distributed propulsion and its effects on aerodynamics and control, and controllability of such planes using unconventional, distributed and heterogeneous actuators.

Thanks to CARNOT Funding, a project, called AMPERE, has been launched to analyze the behavior of the DEP by combining computational and experimental approaches. For that, a wind-tunnel powered mock-up of one of ONERA's concept-planes has been designed and manufactured. This powered mock-up will be tested soon in ONERA's L2 facility (located at Lille Center) in order to capture DEP behavior for aerodynamic assessment and flight control law definition.

Powered mock-up

Mock-up main characteristics

The L2 facility which will be used in our demonstration is a low speed wind tunnel (19 m/s). Due to its geometrical characteristics, no wall effects occur on a mock-up about 3 m span. Considering L2 facility limitations and the will to power our mock-up using COTS components, especially EDF, a scale of 1:5 has been finally As stated before, the use of COTS components and a lack of available solutions led us to consider 50 mm diameter Electric Ducted Fan (EDF) rather than 40 mm diameter ones, which was suggested by homothetic rule. In line with other considerations regarding geometry, symmetrical arrangement and overall thrust level, only 32 EDF will be used on this mockup.

On this basis, and considering the main objectives for these wind tunnel experiments, the design of the mock-up has been improved through some focused investigations regarding mainly, wing airfoil, EDF performances, EDF integration in term of chord location, setting and depth of burying, control surfaces sizing and finally the local geometry of air intake and exhaust including tail cones of EDF.

In addition, more related to the experimental requirements, a special attention has been paid on electrical architecture, EMC compatibility and thermal environment of components integrated in it.

Some of those considerations will be partly detailed hereafter.

Aerodynamic analysis of the EDF integration

As described before, an aerodynamic analysis has been done in order to fix the location of EDF in order to mainly maximize high lift effects.

Starting from some past investigations [START_REF] Hermetz | L'avion d'affaire personnel à propulsion électrique, un « Concept Plane » ? Aero-Club de France[END_REF][7], RANS 2D and 3D numerical computations have been done using in-house ONERA CFD tool elsA.

The aim of these simulations was to compare multiple configurations (wing airfoil, location and setting, fan diameter, etc.) considering several criteria such as [CL, CD], stall behavior and pitching moment wrt thrust level. For example, the Fig. 11 depicts the pressure field obtained by elsA 2D RANS computation on leading edge EDF location, for a certain level of thrust. The second objective of aerodynamic computations was related to the detailed design of intake and exhaust parts of EDF installation.

To do that, 3D CFD RANS computations have been performed through elsA software, with the use of actuator disk to simulate the real EDF used. An example of result is shown on Fig. 12.

Definition of the electrical propulsion

In parallel with the determination of the scale model, components of the electrical propulsion chain (EDF, Electronic Speed Controller or ESC, power supply, wiring, electronic modules for the management of the 32 ESC and the capture of motor RPM) have been either chosen, defined and/or characterized and finally purchased or set-up and built.

WeMotec MicroFan EDF has been chosen after a first set of experiments on a dedicated test bench, with 6 COTS EDF candidates. Then, a second set of experiments (see Fig. 13) was done later on the 32 EDF (completed by the same number of ad-hoc ESC), in order to model their behavior in of laws such as [thrust, Intensity] = f(RPM), considering voltage and then to be able to drive it through ad-hoc electronic modules. From those experiments and considering mockup installation in the L2 facility, the sizing of the electrical power supply concluded on the use of 32 independent sources supplying each 600 W (as each EDF requires an electrical power around 450 W to reach their maximum speed, close to 60000 rpm).

EDF and ESC experiments confirmed also that thermal management of ESC, which will be confined in the wing body of the mock-up, is of first importance.

Motor controllers can dissipate a lot of heat (roughly 70 degree Celsius) versus their solicitation (efficiency).

Moreover, the 32 twisted cables which supply each one EDF will be also integrated close to the ESC in the central part of the wing (between two spars) where volume is limited. This implies to take into account the harness losses and also the thermal contribution in that space. As a consequence, a cooling system has been designed and integrated in the mock-up. It uses compressed air, coming from external L2 facility, which will be diffused locally to each controller by small vinyl tubes (see Fig. 14) and extracted close to ailerons at the inner wing. Considering these constraints, the maximum cable length between a voltage source and a controller has been estimated to 8 m and the output of the voltage source will be of 18 volts to have a good performance of EDF. In order to test the overall electric architecture of the mock-up propulsion system, including electronics for ESC driving and motor monitoring, all components are integrated on a ground test bench (see Fig. 15). This functional and material validation, including verification of electronic compatibility will be done during the summer 2016 before integration of these components in the mock-up.

Mock-up detailed design and manufacturing

All of previous focused studies led to set the external geometry of the mock-up through a CAD model and to freeze the requirements for the detailed design and manufacturing of the mock-up.

Detailed design (assuming internal arrangement of structures) and manufacturing have been subcontracted to a French SME, Aviation Design, who is actually involved in several activities regarding scaled flying demonstrators for proof of concepts or technologies. The detailed CAD model of this mock-up has then been created (see Fig. 16) in close relationship with ONERA engineers, fulfilling the set of ONERA requirements coming from tasks detailed before. The mock-up is mainly in carbon fiber composite materials with some metallic parts either for WT balance binding or electric components thermal dissipation. The manufacturing process uses several molds in Labs materials to be compliant with geometrical tolerances required. Electric propulsion for aircraft is a promising solution for reducing environmental impact of aviation together with a decrease of fossil energy dependency, considering also that passenger will accept in the future to fly differently: lower, slower and probably with more bounds for a given range than today.

Based on recent ONERA's investigation, this propulsive innovation requires to address several key-technologies and ONERA's experts are convinced that Distributed Electric Propulsion, using distributed hybrid energy sources based on coupling fuel cells and batteries, will be the basis for the emergence of All Electric Aircraft, first for small business operations but potentially for more demanding ones.

Therefore, the AMPERE project aims to increase know-how regarding these new technologies and will help aircraft manufacturers / aircraft designers to better understand pros & cons, and also better integrate them in future configurations of aircraft able to fulfil societal needs and reduce environmental impact of aviation.

In that way, ONERA intends to participate in the future of Aviation and is ready to go with research and industrial partners to promote, develop and make effective All Electric Aircraft especially using distributed propulsion.

Fig. 1 :

 1 Fig. 1: OAD approach

Fig. 4 Fig. 5 :

 45 Fig. 4 Three-surface concept-plane with distributed EDF at the wing trailing edge

Fig. 6 :Fig. 7 :

 67 Fig. 6: 3 view drawing of the main configuration Now, considering the high-wing concept-plane with distributed EDF along the wing leading edge, a MTOW (Maximum Take-Off Weigh) of 2 400 kg is assessed. The mass breakdown is as follows:

Fig. 8 :

 8 Fig. 8: Example of advanced propulsive architecture by EDF clusters allocation

Fig. 9 :

 9 Fig. 9: Example of advanced power architecture.

Fig. 10

 10 Fig. 10 Summary of weight of advanced power architecture

Fig. 11 -

 11 Fig. 11 -Example of 2D RANS CFD calculation simulating a turbine location to the leading edge.

Fig. 12

 12 Fig. 12 Example of 3D CFD calculation

Fig. 13 -

 13 Fig. 13 -EDF test bench, adapted from RCBenchmark Dynamometer Series 1580 thrust stand

Fig. 14 -

 14 Fig. 14 -View of cooling system

Fig. 15 -

 15 Fig. 15 -Ground test bench for propulsion architecture validation

Fig. 16 -

 16 Fig. 16 -View of the CAD model

Fig. 17 -

 17 Fig. 17 -Picture of the mock-up

DISTRIBUTED ELECTRIC PROPULSION FOR SMALL BUSINESS AIRCRAFT A CONCEPT-PLANE FOR KEY-TECHNOLOGIES INVESTIGATIONS chosen

  . This scale leads to a 2.9 m span mockup with a length of 2.16 m and a constant chord of 0.4 m on the inner wing, on where EDF are located. Thanks to L2 WT characteristics the local Re is 534000. Other main characteristics of our scale model are listed hereafter.

	Characteristic	Unit	Scale 1	Scale 1/5
	Airfoil surface	m²	25.86	1.034
	Horizontal tail	m²	3.80	0.152
	surface
	Horizontal tail	m	4.26	0.852
	wingspan
	Internal volume	m 3	6.35	0.051 (51 l)
	Fuselage length	m	10.80	2.160

Acknowledgments

The authors would like to thank colleagues from ONERA who have contributed to works briefly summarized in this paper, and especially Olivier Atinault (Applied Aerodynamics Dept.), Philippe Choy, Claude Le Tallec, Thierry Lefebvre and Peter Schmollgruber (System Design and Performance Evaluation Dept.), Bernard Paluch (Aeroelasticity and Structural Dynamics Dept.), Antoine Guigon (Prospective Dept.), Alexandre Janot, Fabrice Demourant (Systems Control and Flight Dynamics Dept.), David Donjat (Aerodynamics and Energetic Modelling Dept.), Olivier Dessornes (Fundamental and Applied Energetic Dept.), Laurent Guibert (Electromagnetic and Radar Dept.). These works have been conducted thanks to the French CARNOT funding.


Ilenia Graziani
email: ilenia.graziani@gmail.com

Bruno Berberian
email: bruno.berberian@onera.fr

Barry Kirwan
email: barry.kirwan@eurocontrol.int

Patrick Le Blaye
email: patrick.le_blaye@onera.fr

Linda Napoletano
email: linda.napoletano@dblue.it

Laurence Rognin
email: laurence.rognin@eurocontrol.int

Sara Silvagni
email: sara.silvagni@dblue.it

Development of the Human Performance Envelope Concept for Cockpit HMI Design

Keywords: Human Performance Envelope (HPE), HMI design, automation, Human Factors, pilots, cockpit Human Performance Envelope (HPE), HMI design, automation, Human Factors, pilots, cockpit

In this paper, we introduce a new approach based on the definition and delimitation of the Human Performance Envelope (HPE) concept for cockpit operations and design. Instead of considering one or two single human factors, the HPE investigates a set of interdependent factors, working alone or in combination, leading to a performance decrement that could affect safety. The HPE approach is needed to improve the HMI design to develop innovative solutions and adaptive automations, which can provide effective recovery measures, if the human performance is compromised.

INTRODUCTION

With the development of more and more complex systems in aviation, and in particular in the cockpit, the flight crew has to cope with an unavoidable increase of cognitive demand. Aviation accidents in fact, inevitably involve the pilot and are usually associated to human errors. Regarding the potential dramatic consequences of poor pilot performance, identifying the different causes of "pilot error" has become a first concern.

During the last decades, the human factors research focused on this issue trying to prevent or recover the degradation of performance that could bring the pilot out of the flight safety limits. However, previous human performance and error research have focused on the effects of a single factor on performance (e.g., Svensson et al.; Loft et al.; [START_REF] Svensson | Information complexity-mental workload and performance in combat aircraft[END_REF], [START_REF] Loft | Modeling and predicting mental workload in en route air traffic control: Critical review and broader implications[END_REF]). In contrast, few is known about both the potential interaction between different factors and the availability of technical resources, e.g., HMI and automation support, enabling pilots to be in a situation where they have sufficient cognitive resources to perform efficiently their tasks.

With this respect, in this paper we present a new approach to progress both on the definition and delimitation of the concept of Human Performance Envelope (HPE) for cockpit operations and the design of solutions to extend this Envelope. To achieve these goals, a three steps approach is introduced. Step 1 consists in the identification of the HPE components affecting the performance and their measures (behavioural and physiological) through literature review.

Step 2 identifies the potential interaction between the HPE components through experimentations. Finally, Step 3 concerns the design and the evaluation of innovative solutions to increase HPE. Particularly, some examples of mitigation and recovery measures are introduced to take back the crew's performance to the centre of the envelope, into the "tolerance zone". In the rest of this paper, we will consider each of these steps in turn.

FROM HPE CONCEPT TO HPE FACTORS HPE definition

The metaphor underpinning the HPE concept suggests that when studying human performance and recovery, we need to consider a full range of factors that can affect performance, and be able to detect when one or more is moving out of 'tolerance'. The performance envelope is defined by the relevant factors and associated scales, which contains a region where performance will be tolerable, and where it starts to become hazardous. This set of related factors affects pilots' performance and play a role in the achievement of the intended goals. If these factors are studied borrowing the envelope metaphor, it can be possible to determine the starting point in which significant performance degradation could affect safety. A wide review of aviation human factors studies and cognitive science literature resulted in the identification of the HPE components affecting the performance and their interdependencies. Starting from precedent studies on air traffic controllers and incident reports analysis [START_REF] Edwards | Human Performance in Air Traffic Control[END_REF]- [START_REF] Edwards | Factor interaction influences on human performance in air traffic control: The need for a multifactorial model[END_REF], a series of nine factors (and their relationships) were identified: Workload, Stress, Situations Awareness, Fatigue, Attention, Vigilance, Teamwork, Communication, and Trust. Depending on the value of each factor, in a specific situation, the resulting HPE could evolve from fully acceptable (e.g., guaranteeing a nominal set of cognitive resources available to operations) to not acceptable (e.g., inducing an error-prone cognitive and physical environment). However, even if a single factor could have a non-acceptable value (e.g., low vigilance), it is possible that the interaction with the others could enable compensations, and consequently overall acceptability of HPE. For each factor, there is a "No Go" limit beyond which there should be a degradation leading to a negative impact on the human performance (Figure 1). For each factor, this "No Go" limit varies according to the situation (e.g., task, environment, context). There is a mutual influence of each factor level on their respective "No Go" limit, i.e. the limit for a given factor could be larger if another factor is far from its own limit (e.g., a high level of workload could be acceptable in a situation where stress is quite low and teamwork quite goodi.e. efficient).

Figure 1. Representation of HPE concept

HPE factors and their measures

The literature review conducted, provided a description of the state-of-the-art of the research on the HP factors (and their relationships) that affect the human performance in the cockpit, by managing the cognitive demand. It also provided shared and consolidated information about the HPE components.

The HPE boundaries can be used as the starting point for determining methods to recover the pilot's performance to the centre of the envelope, and consequently increase this envelope, through innovative HMI design, automatic concepts and flight crew monitoring solutions, procedures and training. For each HPE component (Workload, Stress, Situations Awareness, Fatigue, Attention, Vigilance, Teamwork, Communication, and Trust) we provided one or more definitions, and some recovery measures and mitigation means currently envisaged in the aeronautical domain. A list of measures/techniques for each factor was also extracted from the review. In particular, two kinds of measures were taken into account: task-related measures, linked to subjective assessment and measure of the task execution (i.e., accuracy, duration etc.), and psychophysiological measures, related to neurophysiological variation in the operator (e.g., brain, eye, and cardiac activity, respiration, blood flow, and so on).

The results of the literature review [24] show that:  workload and stress are the most investigated factors in aviation research;  the frontiers between the concepts of fatigue, vigilance, and attention are quite fuzzy; in particular, these factors are difficult to assess in a flight simulator, although NASA, for instance, was conducted considerable research on fatigue in long haul flights;  situation awareness is another relevant topic in aviation and several studies were found. However, the distinction between the various levels of situation awareness, and the attention and vigilance factors was often unclear and these factors seem to overlap in most of the cases;  the impact of communication, teamwork and trust on aviation operators performance is mostly unexplored in the scientific literature although well identified in the operational world.

Workload

Workload refers to the portion of operator information processing capacity or resources that is actually required to meet system demands [START_REF] Eggemeier | Workload assessment in multi-task environments[END_REF]. This hypothetical construct describes the extent of cognitive resources, required to perform a task, that have been actively engaged by the operator [START_REF] Gopher | Workload: An examination of the concept[END_REF]. Workload is not an inherent property of a task, but rather it emerges from the interaction between the requirements of a task, the circumstances under which it is performed, and the skills, behaviours, and perceptions of the operator [START_REF] Hart | Development of NASA-TLX (Taskload Index): Results of empirical and theoretical research[END_REF].

On the flight deck the workload is, on a normal day, predictably cyclical for every flight and fluctuations between low and high workload are common both for crews and ATCO (Air Traffic Controllers) teams.

Variations in traffic-load, adverse weather, degraded equipment, loss of aircraft and other abnormal situations, may cause workload peaks. It is well known and demonstrated that an increase of workload and task difficulty lead to a performance decrement that reflects in a decrease of accuracy and number of completed tasks, while reaction times and number of errors increase.

There are several measures in literature for the assessment of workload, for example subjective measures (e.g., NASA-TLX), primary and secondary task, and observation from experts of strategy changes, as regards task-related the end measures. For psychophysiological measures, we found studies using the electroencephalography (EEG), electrocardiography (heart rate), electrooculography (EOG), eye tracking, and respiratory activity. Other minor measurements, also included in this group, are the functional near infrared (fNIRS) spectroscopy, electrodermal activity, and electromyography (EMG). Although literature reports the use of several valid methods and techniques for workload evaluation have been used in literature, some of them are more suitable for simulated conditions rather than real cockpit operations. For example, despite EEG is a reliable form of workload measure, it is still not portable/usable in a real cockpit condition. Other measures such as pupillometry, eye tracking, and respiratory activity can be basically used in simulated conditions, even if new advanced devices are being developed to be more adaptable to the real context.

Stress

According to psychological theories, stress is determined by the balance between the perceived demands from the environment and the individual's resources to meet those demands [START_REF] Frankenhaeuser | A psychobiological framework for research on human stress and coping[END_REF], [START_REF] Lundberg | Methods and applications of stress research[END_REF]. From a physiological point of view, a typical stress response means that autonomic activity increases. Stress can be categorised into two basic forms: acute stress, relatively short in duration and is often experienced as caused by high taskload; chronic stress, prolonged stress that can result from occupational or nonoccupational sources.

Among the main task-related measures used for stress assessment can be mentioned the communication analysis (e.g., using non-standard phraseology), a video camera pointed to the operator (to detect head movement, body position, and facial expressions), and the cognitive observations (e.g., attentional narrowing). Seat foil sensors can be also included in the list for stress assessment. As regards the psychophysiological measurements, particular attention is given to voice analysis, respiratory activity, heart rate variability, and variations in blinking and eye movements. Another interesting measure of stress is the pressure/grip force, measured through specific pressure/grip sensors on seats and tools. Edwards study on ATCOs [START_REF] Edwards | Human Performance in Air Traffic Control[END_REF] confirms that facial expressions, head movements, verbal cues, and behavioural changes (e.g., easily frustrated) are good markers of stress. Physiological changes, identified in heartbeat and sweat with negative feelings such as uncomfort, anxiety, nervosity, and tension, can be markers of stress as well. Voice analysis, grip force, scan pattern, electrochemical sensors and observation from an expert can be detected in real flight conditions.

Situation awareness

Situation awareness (SA) is the up-to-the minute comprehension of task relevant information that enables appropriate decision making under stress [START_REF] Smith | Situation awareness is adaptive, externally-directed consciousness[END_REF]. SA is a function of several quasi-independent situation types: available situation, perceived situation, expected situation, and inferred situation [START_REF] Boy | Using cognitive function analysis to prevent controlled flight into terrain[END_REF]. Endsley [START_REF] Endsley | Toward a theory of situation awareness in dynamic systems[END_REF] developed a threelevels model of SA: perception of elements, comprehension of current situation, and projection of future status. SA is the perception of the elements in the environment within a volume of time and space, the comprehension of their meaning, and the projection of their status in the future. SA, related to pilots, involves the operators' perception of different environmental elements with respect to time and space, together with a comprehension of their meaning and the projection of their status after some variable has changed with time [START_REF] Borghini | Measuring neurophysiological signals in aircraft pilots and car drivers for the assessment of mental workload, fatigue and drowsiness[END_REF]. When people are required to make critical choices [START_REF] Endsley | Toward a theory of situation awareness in dynamic systems[END_REF], [START_REF] Lundberg | Distributed Situation Awareness for the Civil Cockpit: Theory and operationalisation[END_REF], [START_REF] Parasuraman | Situation awareness, mental workload, and trust in automation: viable, empirically supported cognitive engineering constructs[END_REF], sometimes at a fast pace, the majority of errors occurring is a direct result of failures in SA. While variety of techniques have been proposed to measure situational awareness for example self-rating and inferential techniques (SAGAT or SART 1 ), EEG, EOG, heart rate variability, scan pattern, and expert observation, none of these have been explored fully in terms of their reliability and validity. The multivariate nature of SA significantly complicates its quantification and measurement.

Attention and vigilance

Attention is the ability to attend to information in the environment [START_REF] Eysenck | Principles of cognitive psychology[END_REF]. It is a multidimensional construct that includes focused attention, divided attention and sustained attention/vigilance. Sustained attention or vigilance is the ability to maintain the focus of attention to a task and to remain alert to stimuli over prolonged periods of time, in order to detect and response to infrequent critical events [START_REF] Davies | The psychology of vigilance[END_REF], [START_REF] Parasuraman | The attentive brain[END_REF].

Vigilance, attention and situation awareness are closely linked, and difficult to consider in isolation. Whereas vigilance and attention might be measured with physiological indicators (e.g., eye tracking, EEG, EOG, ECG), situation awareness (as an understanding of the situation) might be more tricky to measure especially in a real cockpit. The three factors seem to be at different levels, with attention and vigilance closely related to SA level 1perception.

Fatigue

Fatigue is a multidimensional state that includes physical, mental and sleepiness components [START_REF] Åhsberg | Perceived quality of fatigue during different occupational tasks development of a questionnaire[END_REF]. It is a gradual and cumulative process associated with an aversion for effort, sensation of weariness, reduced motivation, efficiency, vigilance and alertness, and impairments in task performance [START_REF] Grandjean | [END_REF]. Due to the similar neurophysiological characterization, it is difficult to discriminate between mental fatigue and drowsiness, and they may be considered as transitional states on a continuum. Mental fatigue and sleepiness can be regarded as a consequence of sustained mental activity and lack of resources due to mental task execution, but also as a result of monotonous and boring situations when demand for sustained attention is high but little information is conveyed. No standardized methods for the measure of drowsiness exist, but the more reliable technique seems to be the combination between EEG and EOG.

Teamwork

Teamwork is the organized, collective working methods between an established group of people [START_REF] Bailey | The effects of performance feedback on air traffic control team coordination: A simulation study[END_REF], [START_REF] Erdem | Cognitive and affective dimensions of trust in developing team performance[END_REF], [START_REF] Rasmussen | Teamwork and associated psychological factors: A review[END_REF]. Teamwork is a collective and mutual interaction between humans in the system for performance [START_REF] Edwards | Human Performance in Air Traffic Control[END_REF]. Improving teamwork is the main focus of Cockpit Resource Management (CRM), addressing among other skills 1

SAGAT (Situation Awareness Global Assessment

Technique), SART (Situation Awareness Rating Technique) communication, cooperation and task sharing [START_REF] Flin | Development of the NOTECHS (non-technical skills) system for assessing pilots' CRM skills[END_REF]. Only task-related measures can be applied to this factor such as, TARGET (Targeted Acceptable Responses to Generated Events) and BOS (Behavioural Observation Scale), direct observation/simulation study, and analysis of incident reports.

Communication

Communication may be defined as the transfer of meaningful information from one person to another [START_REF] Hogg | Social Psychology[END_REF] and involves both the production and the reception of messages, although communication is independent from (but related to) the concepts of speech and language [START_REF] Hogg | Social Psychology[END_REF], [START_REF] Huttunen | Effect of cognitive load on speech prosody in aviation: Evidence from military simulator flights[END_REF]. In ATC environment is the exchange of information, including timeliness, accuracy, clarity and receptiveness.

As for teamwork, communication can be measured throughout TARGET, BOS, direct observation/simulation study, and analysis of incident reports. Speech recordings are also a good technique for the assessment of communication.

Trust

Trust is a multidimensional construct [START_REF] Costa | Trust within teams: The relation with performance effectiveness[END_REF]. One taxonomy of trust [START_REF] Kiffin-Petersen | Trust, individualism and job characteristics as predictors of employee preference for teamwork[END_REF] used in literature discriminates between dispositional trust and situational trust. The former refers to an individual's propensity to trust, based on both predispositions to trust, and subsequent environmental influences; the latter is context specific, arising from the perception of an individual's (or machines) trustworthiness.

A second distinction [START_REF] Mishra | Organizational responses to crisis. Trust in Organizations[END_REF], [START_REF] Muir | Trust in automation: part II, experimental studies of trust and human intervention in a process control simulation[END_REF] is made between interpersonal trust and trust in technology. The interpersonal (cognitive and affective) trust the willingness to be vulnerable to another party based on the belief that the latter party is competent, open, concerned and reliable; the trust in technology is described as an intervening variable that mediates between the system and an operator's interaction strategy with the system. Edwards [START_REF] Edwards | Human Performance in Air Traffic Control[END_REF] reports that ATCOs consider trust as important in their work in terms of their relations with colleagues, pilots and management; as well as with regard to their attitude towards technology [START_REF] Bonini | ATC do I trust thee?: referents of trust in air traffic control[END_REF]. There is no standardised method in literature for the measurement of trust. Usually, trust in colleagues is assessed through questionnaires (i.e., self-assessment) and/or direct naturalistic observations, while trust in automation can be inferred using false alarms and reaction times.

Interaction among factors

The literature review revealed several interactions among the nine factors composing the HPE emerged from the literature review. Three thematic areas seem to arise: workload, stress and fatigue is a group of strictly interrelated factors; situation awareness, attention and vigilance are almost overlapped, with attention and vigilance recognised as crucial components of situational awareness. Finally, teamwork, communication and trust can be seen as the set of "social" factors.

Beyond the three thematic areas, it is shown that high levels of workload affect attention, vigilance and situation awareness. It is also proved [START_REF] Berka | EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks[END_REF] that high level of workload affects communication abilities. Stress may affect vigilance, induce monotony, and impair the process of stimuli from environment. Acute stress may also impair decision making, in particular under time pressure conditions, and communication. In addition, fatigue affects attention, vigilance, and situation awareness, and may induce monotony. Endsley [START_REF] Endsley | Toward a theory of situation awareness in dynamic systems[END_REF] showed that situation awareness (SA) and workload are independent constructs, with four possible combinations:  low SA and low workload if the operator does not know what is happening and is not actively trying to find out;  low SA and high workload if the operator is handling too much information or too many tasks, thus he is not able to process and integrate everything;  high SA and low workload, in which the important information is being presented and correctly perceived and integrated (the ideal situation);  high SA and high workload, when the operator is working hard, but successfully handling the situation. SA is also affected by the amount of workload and stress. It was observed that physiological factors, such as sleep loss and high blood pressure, can affect attention and vigilance. Motivation, intrinsic or extrinsic, can affect attention and vigilance too. Teamwork and communication are affected by all the variations of the individual status (workload or stress increase, SA decrease). Finally, a robust positive correlation between interpersonal trust and team working emerged from the analysis of the literature. All the interdependencies emerged are summarised in table 1 where the bold ticks indicate a correlation or interdependency between two factors that is confirmed by independent studies (for instance, the correlation between workload and SA emerged both in Endsley research and in Nählinder studies on workload [START_REF] Nählinder | ACES-Air combat evaluation system[END_REF], [START_REF] Nählinder | Flight Simulator Training: Assessing the Potential Department of Management and Engineering[END_REF]). On the other side, the crosses indicate a relation between factors that emerged from literature review, but with a less stable consensus.

Table 1. Interdependencies between HPE factors

FROM SINGLE FACTORS TO THE MODELING OF THE INTERACTION BETWEEN RELEVANT FACTORS

Usually, a single factor must be severely degraded to cause a significant deficit and, in that case, most modern aviation systems prevent it (for example through HMI tools, strict rest requirements for the pilots, etc.). However, if two or more human factors start to degrade at the same time (e.g. communication problems, fatigue and decreased situation awareness), then a significant combined decrement in performance can be observed, even if the level of the individual factors alone would not cause a significant deterioration. In this sense, we assume that rather than focusing on one single factor, we have to consider a full range of factors that generally affect the performance and their relative interactions. In this work, we propose to reveal these potential interactions using human-in-the-loop simulation. Three HPE factors were chosen as they appeared as the most prominent measures to consider amongst the nine initially identified. Particularly, situation awareness, stress and workload were selected thanks to their respective importance in aviation domain. By manipulating each factor individually, we propose to measure both the effect of each of these three factors on human performance, but also how the interaction of the different factors could impact human performance envelope. Both simple paradigm and complex human-in-the-loop simulations are proposed. We propose to explore in a first step this question in simple paradigm. Particularly, we have designed two experiments using MATB (multiple attribute task battery) from NASA [START_REF] Comstock | The multi-attribute task battery for human operator workload and strategic behavior research[END_REF]. In these two experiments, we plan to manipulate independently the three HPE factors selected, and to measure both the independent effect of each factor on human performance and their interaction effect. Both behavioural (reaction time, time on target, error detection) and physiological measures (ECG, GSR, EEG, oculometric measures) are planned to be collected. Together with the identification of the potential interaction of these three factors regarding human performance envelope, the main objective of these two experiments is also to select adequate sensors for real time simulations. Thanks to the results obtained during these initial experiments, a second series of experiments using real time simulations is planned for 2016 in order to confirm the independent effect of each factor on human performance and their interaction effect in a more complex environment. In these simulations, two scenarios will be played and their characteristics (factor manipulated, performance measure) will be defined in collaboration with pilots.

FROM HPE LITERATURE REVIEW TOWARDS INNOVATIVE SOLUTIONS

The third step of our approach consists to propose innovative solutions including adaptive automation, which can provide effective recovery measures if the human performance is compromised. Particularly, we assume that the delimitation of the HPE boundaries, in terms of cockpit operations and design solutions, can be used as the starting point for determining methods to recover the pilot's performance to the centre of the envelope, and consequently increase this envelope, through innovative HMI design, automation concepts and flight crew monitoring solutions (procedures and training). The importance of the design of HMI relies in enabling pilots to be in a situation where they have sufficient cognitive resources to perform their tasks efficiently and safely.

Recovery measures connected with the introduction of HMI and support tools

The human resources (both physical and cognitive) are limited: to perform efficiently and safely in complex working settings, the human performance needs the support of different tools. Task description, training, working methods, procedures, automation, HMI and supporting tools are introduced in the complex working environment to ensure an efficient support to human activity. Particular attention is given to information display, HMI and automation that need to be designed with and around the final users, on the basis of understanding their needs in the various contexts. The system design, and more specifically the automation design, evolved from an engineer driven approach (based on technical feasibility) to a human user centred approach (based on the user requirements and on the need to reduce accidents/incidents and costs) [START_REF] Bannon | From human factors to human actors: the role of psychology and human-computer interaction studies in system design[END_REF]. Thus, to perform efficiently, designers need to ensure that automation, HMI and support systems are as simple and intuitive as possible, by involving the final users in their design. Keeping this in mind, some examples of recovery measures and mitigation means are proposed from literature for high and low levels of workload (Table 2), as both extremes are potential sources of errors. Mitigation is considered as steps taken to control or prevent a hazard from causing harm and reduce risk to a tolerable or acceptable level, while recovery is composed of the actions put in place in real-time to handle the hazard (i.e., to restore the system to its nominal -pre-failure -state or at least to limit the consequences of the failure).

Workload

Mitigation

CONCLUSIONS

In this work, we proposed a new approach based on the definition and delimitation of the HPE concept starting from a literature review on nine common human factors that can affect the human performance. Recognizing the need for a multi factorial approach to understand the determinants of human performance and eventually to support it, the HPE concept encompasses not only one single factor, but a set of interdependent factors, working alone or in combination. We reviewed the definitions and possible measures for each of the factors and discussed their interdependencies. We also introduced some examples to mitigate and recover the pilot's performance through innovative HMI design, automatic concepts and flight crew monitoring solutions, procedures and training. Particular attention is put on the importance of designing HMI solutions and automation that relies in allowing pilots to be in a situation where their cognitive resources is enough to perform efficiently and safely their tasks. Future works include pilots' workshops in order to elicit applicable factors and measures, and to define scenarios for validation of the concepts. Preliminary experiments will then be conducted in order to reinforce the hypotheses regarding factors interdependencies (e.g., between workload and stress) and their measure, before performing trials involving qualified flight crews in realistic simulations.

Table 2 .

 2 Mitigation and recovery measures for workload

ACKNOWLEDGMENTS

This paper is based on work performed in the Programme Future Sky Safety, which has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 640597. The views and opinions expressed in this paper are those of the authors and are not intended to represent the position or opinions of the Future Sky Safety consortium or any of the individual partner organisations.


Marie-Camille Caumon

Jérôme Sterpenich

Aurélien Randi

Jacques Pironon

Experimental mutual solubilities of CO2 and H2O in pure water and NaCl solutions

Experimental mutual solubilities of CO 2 and H 2 O in pure water and NaCl solutions.

Marie-Camille CAUMON , Jérôme STERPENICH , Aurélien RANDI , Jacques PIRONON GeoRessources laboratory, Vandoeuvre-lès-Nancy, France

OBJECTIVES & METHODS

RESULTS

CONCLUSION

Context

Prevision of the effects of CO 2 injection in saline aquifers:

• Lack of solubility data in saline media at high PT.

• Lack of H 2 O solubility data in the CO 2 -rich phase.

Objectives

Acquisition of solubility data in saline media by in situ Raman techniques at 100 °C, 0-200 bar, 0-2 M NaCl.

Methods

Two Raman probes are connected to a 2L autoclave. Raman spectra are continuously acquired in both vapor and liquid phases while CO 2 is injected.

The IMAGES setup: a PT-controlled autoclave connected to two Raman probes and spectrometer (Kaiser Optical Sys.)

CO 2 solubility vs. salinity

Method performance

• A correlation is found bewteen Raman data and CO 2 solubility in saline water. • Salinity affects the calibration curves in the H 2 Orich phase.

• A correlation is found bewteen Raman data and molar fraction ratios in the CO 2 -rich phase. • This correlation does not depend on salinity.

Comparison with thermodynamic models

•

  Experimental CO 2 solubility in saline water & calculated values (EOS Duan & Sun, 2003) perfectly fit. • Measured H 2 O solubility in CO 2 ranges between the two tested models (Duan & Sun, 2003 & Spycher et al., 2003) and other exp. data. The determination of mutual solubilities of H 2 O and CO 2 is essential for the modelling and understanding of CO 2 geological storage in deep saline aquifer. Here it is demonstrated that the IMAGES experimental device, coupled to a Raman spectrometer, makes possible to produce new solubility data at 100 °C up to 200 bar, in the presence of NaCl. Moreover, it is now possible to measure H 2 O solubility data in the CO 2 -rich phase where data are very sparse. In this last case, previsions may be improved by the optimization of the experimental device.