Optimization of a solar chimney design to enhance natural ...

Optimization of a solar chimney design to enhance natural ventilation in a multi-storeyoffice buildingM. Gontikaki BSc. dr. Dipl.-Ing. M. Trcka prof.dr.ir. J.L.M. Hensen Ir. Pieter-Jan HoesUnit Building Physics and SystemsEindhoven University of TechnologyEindhoven, NetherlandsABSTRACTNatural ventilation of buildings can be achieved with solar-driven, buoyancy-induced airflow through a solarchimney channel. Research on solar chimneys has covered a wide range of topics, yet study of the integration inmulti-storey buildings has been performed in few numerical studies, where steady-state conditions wereassumed. In practice, if the solar chimney is to be used in an actual building, dynamic performance simulationswould be required for the specific building design and climate. This study explores the applicability of a solarchimney in a prototype multi-storey office building in the Netherlands. Sensitivity analysis and optimization ofthe design will be performed via dynamic performance simulations in ESP-r. The robustness of the optimizeddesign will be tested at the final stage, against e.g. windows’ opening by users. This is an ongoing project;calibration of the solar chimney model and preliminary sensitivity analysis results are presented here.INTRODUCTIONThe exploitation of sustainable energy sources tocover the functional demands of buildings (forheating, ventilation, cooling etc) can contribute tosignificant energy savings and thus to alleviation ofthe current environmental, economical and socialproblems related to conventional energy practices.Passive (natural) ventilation of buildings is asuccessful means to save energy otherwise consumedfor mechanical ventilation and/or cooling. Solarchimneys (SC) are passive elements that make use ofthe solar energy to induce buoyancy-driven airflowand naturally ventilate the building.A SC differs to a conventional chimney in that atleast one wall is made transparent; solar radiationenters the chimney through the glazed part and heatsup the walls. The temperature of the air inside the SCchannel rises due to heat transfer from the walls andthe resulting buoyancy drives the airflow through thechannel. The SC pulls air from the interior of thebuilding, which is replaced by fresh air throughopenings or other paths, and natural ventilation isaccomplished. Performance of the SC is primarilydescribed by the induced ventilation flow rates; incase heat harvesting is also of interest, airtemperature in the channel is the other importantperformance indicator.The geometry of the SC channel is described byits height, length and cavity width. The elements ofthe SC are presented in Fig. 1; the terms indicated inFig. 1 will be used in the following sections to referto the solar chimney’s parts and geometrical features.Integration of a solar chimney in a building ispossible in many ways (Fig. 2), e.g. as part of thesouth-facing façade (or the façade where maximumsolar availability applies), on the roof (also known as‘roof solar chimney’), in the place of a conventionalchimney or as extension of a double façade (usuallyfor multi-storey buildings).The present study explores the passiveventilation potential of a SC integrated in a multistoreyoffice building in the Netherlands. It formspart of a broader project under the name ‘Earth, Wind& Fire’, concerning the exploitation of solar,geothermal and wind energy in a prototype building.This is an ongoing research and results are not yetavailable. The following sections present anextensive literature review, the applied methodologyand envisaged results.Figure 1.Cross-section and top view of a SC.Figure 2. Integration possibilities of SC in buildings.

LITERATURE REVIEWGeneral Literature ReviewDuring the past few decades numerous researchstudies have been performed on the SC concept, thathave deepened our knowledge on the performance,the parameters that affect the performance and theapplicability of the system for natural ventilation andpassive cooling of spaces. The studies can fall underthe broad categories of experimental, analytical andnumerical modeling studies. A general overview ofprevious studies based on the above categorizationwill be presented initially. This section offers ageneral impression of the various research topics andapproaches, and no findings will be reported forbrevity reasons. Instead, the findings of parametricanalysis studies and of the ones regarding integrationin multi-storey buildings will be grouped andpresented in two consecutive separate sections, sincethey are greatly related to the present study.Experimental studies.Field studies concerning the ventilation inducedby SC configurations in a small-scale single-roomhouse were performed in Thailand (Khedari et al.,2000). In a consecutive study Khedari et al. (2003)studied the performance of SC systems in an airconditionedsmall-scale house. Barozzi et al. (1992)tested a 1:12 small-scale model of a building wherethe roof functions as a solar chimney. Hirunlabh et al.(1999) performed a similar study for a 31m 3 volumehouse where a metallic solar wall was placed on thesouthern façade. Laboratory experiments on smallscalemodels were also performed, where temperaturedistribution of the air and the walls’ surfaces, thevelocity profile in the chimney’s channel and themagnitude of the air flow rates were studied, incombination with parametric analysis (Chen et al.2003, Burek and Habeb 2007). The performance of afull-scale 2m high SC that was part of a 12m 3 room,was studied under laboratory conditions by Bouchair(1994), while Arce et al. (2009) studied a 4.5m highmodel, under real meteorological conditions in Spain.Analytical studies.In a number of analytical studies mathematicalmodels were developed for the prediction of the solarchimneys’ performance. Experiments were usuallyperformed, in order to validate the models. Bansal etal. (1993) developed a steady-state mathematicalmodel to calculate the mean air flow rates andtemperatures of a solar chimney connected to aconventional one. Wall temperature was assumeduniform. Awbi and Gan (1992) analytically derivedthe air temperature distribution along the SC channelby making the same assumption. A steady-statemathematical model was also developed byBassiouny and Koura (2008) to predict the airchanges per hour 1 (ACH) induced in a room by a SC.The thermal resistance network approach wasadopted to set up the steady-state heat transferequations in the model of Ong and Chow (2003),which predicts the performance of a solar chimneyunder varying ambient conditions. Mathur et al.(2006) followed a similar approach to calculate theACH induced in a room by a small-sized solarchimney integrated to a normal window. A simplifiedthermal model and a computer program to calculateventilation flow rate through a chimney weredeveloped by Afonso and Oliveira (2000) which alsotakes into account varying climatic conditions, thethermal inertia of the back wall and dependence ofthe convective heat transfer coefficient on the airflow rate.Numerical modeling studies.The buoyancy-driven airflow and heat transfer invertical heated cavities were investigatednumerically, mainly through Computational FluidDynamics (CFD) simulations in an increasingnumber of studies during the past decade. Some ofthe studies focused on the airflow regime and the heattransfer mechanisms in the SC channel, while otherson parametric investigations. The latter will bementioned here briefly, since more details will begiven in the following section. Numericalinvestigations on the airflow within the Trombe wallchannel, which can be considered a type of SC,preceded by many years, with the first one being thatof Borgers and Akbari (1979). Rodrigues et al.(2000) studied the airflow regime and the transitionfrom laminar to turbulent flow in a SC channel usinga finite-volume method. The heat transfermechanisms (by conduction, convection andradiation) in the SC channel were studied in detail,using the numerical method of finite-differencecontrol volumes, by Nouanégué and Bilgen (2009).In certain studies numerical modeling wasemployed to perform parametric analysis on the SCsystem. The effects of solar heat gain and glazingtype (Gan and Riffat, 1998), cavity width (Gan,2006), inclination and low emissivity coating (Harrisand Helwig, 2007) were some of the issuesinvestigated using CFD modeling. Recently Gan(2010) found that the size of the computationaldomain (for CFD simulations) has an impact on theairflow and heat transfer coefficient predictions insolar heated cavities, and made correspondingsuggestions. An extensive parametric analysis for aSC integrated in a prototype residential building wasperformed by Ho Lee and Strand (2009), usingnumerical modeling in the program EnergyPlus. Theauthors developed a SC module for the program and1 Ventilation rate expressed as a factor of the space volume:ACH [-] = (ventilation induced in one hour –[m 3 ])/(spacevolume – [m 3 ])

performed single-day dynamic simulations, assumingthree different locations for the building. Numericalinvestigations have also been performed to study theapplication of solar chimneys or similarconfigurations of solar heated cavities (e.g. doublefaçades) in multi-storey buildings (Punyasompun etal. 2009, Ding et al. 2005, Letan et al. 2003, Gan2006). The corresponding findings of these and of theparametric analysis studies are reported in thefollowing two sections.Parametric Analysis FindingsIn parametric analysis, parameters are varied oneby one to determine the sensitivity of the system’sperformance against each. It has been employed inthe vast majority of studies and has played asubstantial role in understanding the mechanismscontrolling the performance of the solar chimney andtheir interactions. The most influential (and thusmostly studied) parameters can fall under thecategory of geometrical (e.g. wall height, gap width),construction (e.g. type of glass, insulation) andclimatic (e.g. solar radiation, wind) parameters. Someindicative results will be presented in this section,regarding the effect of these parameters on thesystem’s performance.Effect of wall height and cavity width.The effect of wall height and cavity width has insome cases been studied and expressed separately,while in others inextricably, in terms of the height-towidthaspect ratio (also referred to as height-to-gapratio). Air flow increases with height, since the backwall’s heat gains increase: in a parametric study onTrombe walls, Gan (1998) found that an increase inwall height by a quarter is equivalent to an increasein heat gains by three quarters. In the study of Ho Leeand Strand (2009) air flow rates increased in all threeassumed locations of the building, by ~73% when thewall height increased from 3.5 to 9.5m (a cavitywidth of 0.3m was considered).With respect to the cavity width, it was foundthat the induced flow rate increases with increasingwidth. In the analytical study of Ong and Chow(2003) it was estimated that a 0.3m wide channelinduced 56% higher flow rate than one of 0.1m.Similarly, according to the model of Bassiouny andKoura (2008) a threefold increase in cavity widthcauses an increase of ACH by 25%. Rodrigues et al.(2000) argued that airflow rates grow with cavitywidth, but the growth ratios decrease as the widthincreases. In some studies an optimum cavity width(or optimum height-to-width ratio) was reported; forthis optimum width the flow rate became maximum,while for wider gaps reverse flow occurred thatreduced the mean flow through the SC (Spencer et al.2000, Chen and Li 2001). This discrepancy betweenstudies is attributed to the different ranges of heightto-widthratios investigated and to the influence ofthe inlet size. The term ‘inlet’ is used here to describethe opening from where the room air is admitted intothe SC channel. In case the inlet size increases alongwith the cavity width, a lower pressure drop in theinlet can counterbalance the reduction in the flow ratecaused by reverse flow, so that no optimum width isfound (Gan 1998, Chen et al. 2003). Gan (2006) laterreported an optimum width of 0.55m for a 6m highSC and supported that the optimum width increaseswith height.Effect of inlet size.The effect of inlet size was also explored insome studies, and was found to have a wicker effecton the performance compared to that of the cavitywidth. Increasing the inlet size by a factor of threeincreased the induced ACH by 11% in the analyticalstudy of Bassiouny and Koura (2008), whileNouanegue and Bilgen (2009) found that volumeairflow rate is a decreasing function of inlet size. Gan(1998) claimed rising airflow rates for cavity widthbeyond 0.3m, as long as the inlet size has the samesize as the width.Effect of inclination angle.Various inclination angles (15 o /30 o /45 o /60 o ) werestudied experimentally by Chen et al. (2003) for aconstant height, cavity width and uniform heat flux.The air velocity profile across the cavity width wasfound to be more uniform when the SC was inclined,leading to lower pressure losses at inlet and outlet,and thus to higher airflow rates (45% higher airflowrate was found for the angle of 45 o ). Harris andHelwig (2007) numerically studied the consequencesof inclining the SC along the roof line of buildings(for the latitude of Edinburgh, Scotland). Theyargued that although the heat gains can be favoreddue to tilt, heat transfer between air and glazing ishigher, resulting in higher heat losses that couldreduce the performance. Higher flow rates by 11%were found (for the optimum angle of 67.5 o ), whilethe performance at 45 o angle was almost the same asthat of the vertical SC. It is implicit that the impact ofSC inclination is highly dependent on the latitude ofthe location.Effect of back wall properties.Increasing the thickness of the back wall (i.e itsthermal mass) favors night-time ventilation becausethe time distribution of the induced airflow rateschanges; their magnitude on the other hand is notsignificantly altered (Charvat et al. 2004, Martí-Herrero and Heras-Celemin 2007). Insulation of theback (and side) wall(s) is imperative to preventdevastating heat losses of the SC (as well asoverheating of the adjacent spaces): airflow ratesdecreased by 60% without back wall insulationaccording to the study of Afonso and Oliveira (2000),while Gan (1998) reported that 40% of available heatgains would be lost through a non-insulated back

wall (0.3m thick). In that study the surfacetemperature of the back wall rose by 9 o C wheninsulation was applied. Back wall absorptivity shouldbe as high as possible to maximize solar heat gains.Increasing the absorptivity from 0.25 to 1, led toincreased airflow rates by 42-57% in all threelocations assumed for the building (Ho Lee andStrand 2009). Back wall emissivity should be as lowas possible to restrict radiative heat losses; when alow-e coating was applied at the back wall, airflowrates increased by 10% in the study of Harris andHelwig (2007).Effect of glazing type.The use of double glazing can preventdowndraught (and thus reverse flow) along the coldglass surface during winter, but was also found toincrease the induced airflow rates up to 17% whenapplied to a Trombe wall used for passive ventilationin the summer (Gan, 1998). Harris and Helwig(2007) argued that double glazing improves theperformance of a SC but only marginally, so that it isnot a cost-effective measure (only summer conditionswere considered).Effect of climate: solar intensity and wind.The intensity of solar heat flux is the motiveforce for the operation of the SC and is thus the mostdeterminant factor for its performance. In theexperimental study of Chen et al. (2003) varyingvalues were considered for the uniform heat flux onthe back wall and the airflow rate was found to riseby ~38% for a threefold increase of heat flux (from200W/m 2 to 600W/m 2 ). Mathur et al. (2006) foundthat airflow rate increases linearly with solarradiation and Bansal (1993) estimated that a SC withsurface area of 2.25m 2 , would induce 100m 3 /hr and350m 3 /hr for solar radiation of 100W/m 2 and1000W/m 2 respectively. Based on experimentalinvestigations on a small-scale SC, Burek and Habeb(2007) derived that the mass flow rate is proportional0.572to Q i where Q i (W/m 2 ) the uniform heat fluxsupplied to the back wall. The simulations of Ho Leeand Strand (2009) showed flow rates to vary as muchas 200% between the three assumed locations of thebuilding, as a result of the varying solar availability.Wind is the second most influential climaticparameter, as it can create positive or negativepressures at the outlet of the SC and thus obstruct orenhance the airflow. In the outdoor experiments byArce (2009) at a full-scale SC, the highest airflowrates coincided with the highest recorded windvelocity, while Afonso and Oliveira (2000) alteredtheir model to include wind effects which provedsignificant (error between model predictions andmeasurements was then lower than 10%). In theanalytical study of Mathur et al. (2006) the largeerror of 23% was attributed to wind effects, whichwere neglected in the model. In practice, devices canbe incorporated at the outlet of the SC so that wind ofall directions creates negative pressures.Integration in Multi-Storey BuildingsInvestigating the performance of a SC in a multistoreybuilding holds great interest due to the highpotential benefits involved in actual, large-scaleapplications. This subject has been studied onlynumerically in the past few years, mainly with CFDsimulations assuming steady-state temperature andair velocity fields. The CFD models were validatedagainst small-scale experimental data.Passive ventilation of a five-storey building wasfound feasible in the study by Letan et al. (2003).Numerical simulations were performed withcommercial CFD software assuming steady-statetemperature and velocity fields and summerconditions. It was found that the induced airflow ratesdecreased with floor height: the lower the floor, thehigher the airflow rate. Acceptable thermal conditionswere found for the first four floors with airtemperatures close to that of the incoming air (atmaximum 25.5 o C), while the fifth floor wasoverheated up to 29.9 o C. The authors argued thatextending the SC by one storey height would improvethe situation, but mechanical ventilation would still berequired for the top floor.Ding et al. (2005) investigated a prototype eightstoreyoffice building with an atrium on the northernside and a double-skin façade on the southern side,which extends to a SC channel above the roof height.Reduced scale experiments and CFD simulationswere employed in this study. The size of the openingsconnecting the atrium to the occupant spaces werefixed, while for the size of the openings between thefloor spaces and the double-skin channel three valueswere tested (1m 2 /2m 2 /4m 2 per floor). Differentheights for the SC were also examined. Here as wellthe airflow rates got lower with floor level. Byincreasing the openings’ size higher airflow ratesresulted at all floors, but the pressure difference at theupper floors got lower, resulting in lower percentageof the overall flow going through these. The authorsrecommended that the SC should be at least twostoreyhigh.Ventilation of a four-storey building (total heightof 12m) via buoyancy-induced flow in a double-skinfaçade channel was studied by Gan (2006) usingCFD analysis. Although not a SC channel wasstudied here, the double-skin façade works in asimilar way, with the difference of more symmetricalheating of the two glass skins. Varying cavity widthsfor the double-façade channel and different exhaustconfigurations from the floors to the channel wereinvestigated. Replacing the outer skin of the façadewith photovoltaic panels (PV) was also examined.For the design where each floor has its own opening

to the double-skin channel (referred to as ‘roomventilation’ in the study), flow rates decreased frombottom to top, due to lower stack heights in the upperlevels: for a cavity width of 0.4m, 34% and 17% ofthe total flow was induced at the bottom and top floorrespectively. These floor-to-floor variations weresignificantly reduced when PV panels wereintegrated at the outer skin of the façade. For thisfour-storey structure a cavity width of 0.6-0.8 isproposed as optimum for the ‘room ventilation’design.Punyasompun et al. (2009) performed smallscale experiments for a three-storey building underthe Bangkok climatic conditions and developed asimplified model that could be used for designing a‘multi-solar chimney building’. They tested twopossible ways of SC integration; one where eachfloor had a separate SC channel (i.e. outlet openingsat every floor), and one where the floors wereconnected to a common SC channel, extending frombottom to top floor (i.e. one outlet opening at the topof the channel). The latter proved to perform betterand induce higher airflow rates in the floors.Concluding RemarksIt is evident that fair background knowledge hasbeen gained so far on the physical mechanisms andthe various parameters affecting the performance ofSC systems. The potential of SC systems to driveairflow and achieve sufficient passive ventilation inbuildings has been explored in several studies andwas found satisfactory. Most of these studieshowever, involved single-room or single-zonebuildings and assumed steady-state conditions, whilemost of the outdoor experimental studies (subjectedto dynamic climatic conditions) were performed forhot and arid climates and specific building types,typical of the location. Recent studies havedemonstrated the additional complexity andchallenges posed by integrating a SC system with amulti-storey building, indicating the need for furtherresearch on various related topics.In practice and for large-scale applications of SCsystems in buildings, it is imperative that the designbe based on performance estimations for dynamicconditions and for the specific building, climate andsurroundings. Numerical modeling in buildingperformance simulation (BPS) tools should beemployed when it comes to practical applications:dynamic thermal and airflow simulations for the SCbuildingsystem can be performed and the feasibility,potential benefits as well as possible improvementsof the design can be fully explored.This project studies the feasibility of a SCintegrated in a prototype multi-storey office buildingin the Netherlands. Performance simulations will beperformed in the BPS tool ESP-r and results will beused for sensitivity analysis (SA) and Optimization ofthe design. At present only the SA results areavailable. The calibration procedure and the SAresults are presented in the following sections.AIMThe aim of this part of the project is theinvestigation of the applicability and optimization ofa solar chimney to enhance natural ventilation in amulti-storey office building in the Netherlands.METHODOLOGYTo achieve the aim of the project we envisagedthe research methodology which involves thefollowing stages (Fig. 3):1. Calibrating the model of the solar chimney withthe available data from the small-scalemeasurements set-up.2. Performing Sensitivity Analysis (SA) for a SCdesign and for the following parameters: length,cavity width, inside face short-wave absorptivityand long-wave emissivity, insulation thicknessand thermal mass of the back and side walls,glazing type and glass percentage of the glazedwall. For the selected range of variance of theaforementioned parameters, the Latin Hypercubesampling method is employed and 200 samplesFigure 3. Applied Methodology.

R-squared (R 2 ) is used to judge statistical correlationwhich can take values from 0 to 1, with 1 being theabsolute agreement between measurements andmodel predictions. Since the SC is modeled in ESP-rwith nine thermal zones over the height (see Fig.4[b]), i.e. model’s input and output data refer to ninepoints representing the average conditions in thezones, the available measured data (at four heights)were fitted linearly with curves and ‘measured’values were estimated for the nine model heights, sothat the calculation of the R 2 is possible. The R 2 valueof the linear fitting curves was usually above 0.90,indicating a linear relationship between height and airtemperature in the SC.It is noted that the measured mass flow value,derived from velocity measurements at two points ofthe SC cross-section (at four different heights), isassigned an error of 40%, which is the maximumvariation between points along the length and widthof the SC channel, found in measurements performedspecifically to have an idea of the velocity profiledistribution in the channel. Therefore, a valid rangeof ±40% around the measured mass flow value isestimated, within which the predicted value shouldfall.Calibration Results & DiscussionThe calibration procedure outlined in theprevious section was performed for ten timeslots. It isnoted that the roughness parameter was found to havenegligible effect in the predictions, therefore it wasfixed at 1mm and calibration consisted of adjustingthe local loss factors of the SC components (Ci). Inall cases a loss factor value between 0.6 and 1.0 wasfound to be appropriate (for each timeslot a differentvalue gave the best results) but since this value is afixed input parameter in the model, results arepresented here for a Ci value of 1.0. Agreementbetween model predictions and measurements withrespect to air temperatures for every timeslot ispresented in Table 1, expressed with the value of R 2 ,while agreement of measured and predicted massflow rates is presented in Table 2, where predictedvalues should fall with the valid range. For brevityreasons in Table 2 only the number of the timeslot isincluded; for more data one can refer to Table 1.Given the errors introduced by pre-processing ofthe measured data (e.g. data fitting with curves andassumption for the surface temperatures of the wallsat the upper part of the SC) the model’s performanceis considered satisfactory and the calibrationprocedure successful. In most cases the R 2 value isabove 0.70, whereas lower values are found at timesof low solar radiation intensity values (e.g. timeslotno.5) or for the timeslots of 15/4/10, where asignificant error is traced back to the trendline of thesurface temperatures. Wind speed is also high duringthis day, which could account for the poorperformance of the predictions, since wind isneglected in the model.The above are an indication that the model (where theC i value is fixed) will not be able to represent massflow and air temperatures accurately in some hours ofthe day where extreme conditions, in terms of solarradiation and/or wind speed might come to play arole in the real system. The complexity of flowcharacteristics in a naturally ventilated duct and thevarious parameters that affect the flow cannotpossibly be all represented equally well in a model,which is a simplification of the real system.The calibrated model was also validated forwhole-day dynamic conditions and results werefound to be satisfactory. Validation results are notpresented here for brevity reasons. Confidenceacquired in the ESP-r model of the SC throughvalidation allows us to use it for the simulationpredictions required in the next steps.Table 1. Calibration results: air temperatureagreement between measurements and modelpredictionsTable 2. Calibration results: mass flow rateagreement between measurements and modelpredictions.CASE STUDYSome information regarding the prototypebuilding is presented here, since the sensitivityanalysis is performed for a SC design intended towork for the specific building. The case study is

ased on a simplified model of the faculty ofArchitecture at the Eindhoven University ofTechnology (TU/e) campus, in the Netherlands. Thefloor plan of the building is rectangular withdimensions of 43.2*32.4m (floor surface area is~1400m 2 ). The 32.4m dimension, corresponding tothe southern and northern façade determines themaximum possible length of the SC (see nextsection). The total building height is 49.5m (9 floorsof 5.5m height each), and ventilation requirementsare estimated at 32.66 m 3 /s (3.63m 3 /s for each floor).Outdoor air enters the building through a main supplyduct on the northern side (conditioning of the air isassumed up to 18 o C in the supply duct), diverges intothe floors and is consecutively exhausted in the mainexhaust duct on the southern side (exhaust airtemperature is 20 o C). The SC channel is connected tothe exhaust duct at ground level; a fan located at thebottom of the SC will guarantee an airflow of 32.66m 3 /s at all times. The pressure drop through the ductnetwork of the building (excluding the SC channel)was estimated to be aprox. 40Pa. Dampers arelocated at each floor level to balance the system andensure that all floors receive the same airflow rate.The building is assumed to be an office building, thusthe functional hours are from Monday to Friday andfrom 7am to 7pm (3132 hours per year).SENSITIVITY ANALYSISSensitivity analysis is performed for a full-scaleSC of 50m height, intended to be integrated with theprototype office building previously described. Theparameters considered in the SA are presented inTable 3, along with the corresponding ranges andstep changes; discrete values and uniformdistributions were considered for each parameter.Table 3. Parameters and their range of valuesconsidered for SA.properties of the absorbant layer. Three glazing typesare taken into account (single, double and low-e) witha visible light transmission value of 0.87, 0.76 and0.79 respectively. Restrictions were imposed so thatthe cavity width is less than 25% of the length (toavoid shading) and that the cross-section area of theSC results in air velocities not more than 3m/s in theSC shaft. The parameter ‘glass percentage’ isconsidered to account for the reduction of the totalglazed area due structural framing of the glazingwall. The parameters (independent variables) weresampled simultaneously using the Latin HypercubeSampling method and 200 samples were generated(for the matrix generation the freeware tool Simlabwas used). The performance indicators considered forthe SA (dependent variables) are (i) the annualharvested energy in KWh and (ii) the annual fanenergy savings in KWh.The annual harvested energy is calculated as the sumof the air enthalpic gains in the SC for all functionalhours:(1)Where [m 3 /s] the volume flow rate through theSC, [kg/m 3 ] the air density of the incoming air,[KJ/kgK -1 ] the specific heat capacity of air at theinlet temperature, [ o C] the air temperature at theoutlet of the SC and the temperature of theincoming air, assumed to be 20 o C.The annual fan energy savings are calculated as thesum for all functional hours of the quantity:(2)With the building volume flow rate equal to 32.66m 3 /s, =0.65 [-] the fan’s efficiency and thepressure difference induced by the SC equal to:(3)With the term ‘thermal mass’ the thickness of aconcrete layer placed behind the absorbant layer 2 ofthe back and side walls is considered. Absorptivity(short-wave) and emissivity (long-wave) are material2 the term is used here for the surface material of theopaque walls of the SC, which is usually a low thermalmass layer with a dark-coloured outer surface formaximum solar radiation absorption.with [kg/m 3 ] the density of the air at thesupply duct (temperature of supply air is assumed18 o C), [kg/m 3 ] the air density at the SC channeland [Pa] the pressure losses (local dynamicand friction losses) of the SC. In case results anegative quantity the energy savings are set to zerofor that hour, since a negative value would mean thatthe fan would have to consume more power toaccount for the SC’s high losses. It is reminded thatthe fan would need to generate a pressure differenceequal to:(4)

For the total of 200 samples, simulations wereperformed in ESP-r and the two performanceindicators were derived for each sample. The methodof standardized regression coefficients (SRC) wasused to analyze the results, which is a linearregression method. For every performance indicator(harvested energy and fan savings) the parameters ofthe SA are assigned an SRC value between 0 and 1,which indicate the sensitivity of the model output tothat parameter. The higher the SRC value, the moresensitive the model (i.e. the performance indicator) tothat parameter. A positive value of the SRC meansthat a positive change of the parameter’s value willresult in a positive change of the performanceindicator. A negative SRC value means that for apositive change of the parameter a negative change ofthe performance indicator is expected. Results of theSA are presented in the next section.thickness is low because the backwall of the SC isassumed to be in contact with the wall of the exhaustduct, where the air temperature is 20 o C. The negativevalue of the SRC for the thermal mass indicates thatit is preferable to have the lower thermal masspossible in the walls construction in order tomaximize harvested energy and fan energy savings.From the results of the 200 simulations a scatterplotis produced with the x-axis being the harvestedenergy and the y-axis the fan energy savings; eachdot corresponds to one sample. It can be derived fromFigure 5 that the two performance indicators are notconflicting, i.e. there will be a solution that willmaximise both, as is for example the solutionencircled in the figure. It can also be seen that a largenumber of solutions results in zero fan energysavings (or increased required fan power).SA ResultsFor each performance indicator, the ranking ofthe eight parameters, starting from the mostinfluential, and the SRC values are presented in Table4. It is noted that the R-square values are 0.875 forthe harvested energy model and 0.871 for the fanenergy savings model, reassuring that the linearregression method was a good choice; in case thesevalues were low a non-linear regression analysiswould have been more appropriate.Table 4. Ranking of the SA parameters.Figure 5.Scatter-plot of the 200 simulation results.For the harvested energy the most importantparameters are the length of the SC, the short-waveabsorptivity of the walls, the glazing type (thepositive SRC value here means a double is preferableto a single glazing and that the low-e would be thebest choice out of the three) and the thermal mass.For the fan energy savings only the second mostinfluential parameter is different compared toharvested energy, and that is the gap width, whichranks only 7 th in the harvested energy model.Parameters 5 to 6 are not as important, whereas theones ranking 7 th and 8 th could be discarded from theregression model (the p-value is more than 0.05) 3 . Itshould be noted that the ranking of the insulationCONCLUSIONSThe applicability of a SC for passive ventilationof a prototype multi-storey office building in theNetherlands is explored. Measurement data in asmall-scale SC were used to calibrate and validate theSC model. Modeling and simulations were performedin the building simulation tool ESP-r. A case studyoffice building has been chosen and a sensitivityanalysis (SA) of a SC design intended for thisbuilding was performed. The dimensions of the SC(length and gap width), the short-wave absorptivityof the walls, the glazing type and thermal mass wereidentified as the most influential parameters withrespect to the annual harvested energy in the SC andthe annual fan energy savings. The next step is theoptimization of the SC design and at the final stage arobustness analysis of the optimized design against -among others- active user behavior (e.g. opening ofwindows). At the final stage the integrated model ofthe SC and the office building will be used.3 The p-value is the probability that the true SRC is zero. Ifp-value is higher than 0.05 the variable should be discardedfrom the model.

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