Experiences on Modelling and Simulation of Sewage and Wastewater Treatment System

EXPERIENCES ON MODELLING AND SIMULATION OF SEWAGE AND WASTEWATER TREATMENT SYSTEM Jukka Ranta*, Kim Pingoud* and Aarne Halme** *H elsinki University of T echnology, Systems Theory Laboratory,02150 Espoo 15, Finland * *Tampere University of T echnology, Control Engin eering Laboratory PL 527, 33101 , TRE 10, Finland '

ABSTRACT Paper presents experiences got in modelli n g and simulation of sewage systems . Sewage sys tem and its operational problems a r e desc r i bed . Feat ures of simulation studies and c ontro l possibilities are rewieved . Modelling aspects of sewer network and wastewater treat ment syst e m are discussed and a deve l oped si mulati on system is presented . As an example some simul ation studies , re l ated t.o a real system , are shown .

INTRODUCTION The sewage system was originally planned to collect and take FMay waste waters produced by commini ties. Later on changes in urban i zed areas and increAsing amounts of wastewat.e r s caused new problems to r eceiving wate r s and it was necessary to bui ld tre atment plants to dec r ease the pollutation load . Nowadays the sewage system can be considered a " p r oduction " p r ocess , where the " rawmllte ri a l ", wastewat e r, is collected by the sewer system and t.reated by the unit processes in the treatment pl=t . The final p r oducts a r e clean water and s l udge , which possibly Clln be ut.ilized econ omically . The e f ficiency of t.he sewage system can be improved by applying proce~s control methods . Until now , however . very conventi onal techni ques h a.s been appli ed i n sewage s y stems . The possibi l ities of aut.omlltion and ins t rumen t ation have been utilized very seldom , although th e p rocess cont r ol evi de n tly me ans de creasi n g main t enance cost.s , s t ab ility of sys t em oper at i on and in c r eas ing r e l i ab i li t y. Wi t.h the i ncreasing disadvantages at wastewate r s mo r e atte ntion has bee n paid t o t.he efficiency of the sewage system . The growing amount of automat ion and inst r umentation studies i n literature fo r examp l e r efl ects that . In s t r umentation studies a r e done just now very a ctively , see e . g . ( 1, 2 , 4, 7 , 8 , 9 , 2 1, 22 , 25 , 35 , 36 , 38) then t he r e is a great nwnb e r o f simul at ion and cont r ol s tudies conc e rn ing treatment plants ( 1, 3 , 5 , 6 , 7 ,1 0 ,1 1 ,1 2 , 2 1 , 26 , 27 , 28 , 29 , 30 , 3 1 , 38 , 39) , and thi r dly mode lling , s i mulation and con tr ol studi es of sewe r s y s t ems (13 ,1 4, 15 , 17 , 18 , 19 , 20 , 24 , 37 , 40 , 42 , 43 , 44 , 45 , 47 , 52) .

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The Aim of this paper is to in t rod\.:.ce experi ences got i n tht' modelling and simulation of sewage systems in Finl=d . The project began in t h e middle of ' 7 L , and it will last till the end of ' 78 . The project is mainly fi nanciat.ed by Acadell\Y of Fin l and . Some results hAve Ill r eady been publ i shed ( 1 , 11,1 2 , 13 ,1 4 , 15 , 24 , 27 , 28 , 29 , 30 , 31 , 37.39) . In this >Japer the second chapter deals with the sewage sys te m and its problems and simUlation aspects of sewllge systems . The fourth chapter gi ves an application example related to a r eal system .

SEWAGE SYSTEM AND ITS OPERATION System Description The tflsk of the sewer network is to collect tht" wastewaters including the sto::om water runoff , sanitary sewage and often also indus t r i a l wastewaters from urban areas and transport them to treatment plants or direct ly t.o the recei ving waters . The sewer systems can be divided into two main groups , combined systems and separate systems . The, combined sewers are designed to carry both the sani tary sewage and t.he st orm water runoff . They are usually designed so , that in addition to the s ani tary flow only a porti on of the storm water runoff can be car r ied in the sys t.em . Excess flow which consists of a mi)..'ture of stormwater runoff , sanitary sewage and such residue as may have been picked up in the conveyance system is directed without t r eatment to the receiving wate r s of' nwrerous outlet points . The separate system includes two different sewer networks , one principally for the sanitary sewage and the other for the stormwater . In the separate system the storm sewers are usually lead directly to the re cei ving waters . In Finland it is typical that the r e are combined s:rstems in the older urban a r eas whe r eas al l new sewer s y stems are built in acco r dance with the separat e system . At present approxi mately 4J % of the sewe r li nes are combined in Finland . The treatment plant usually consist of seve ral units , called unit p r ocesses . Accordi n g to their operation princi ple the unit pro-

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J. Ra nt a , K. Pingo ud a nd A.

cesses can be di video into rTJE'C'hani c81, chemi cal and bi ologi cal processes. TypicAl mechanic'.ll processes arc ego "!:l
H a l ~e

loadings of pollutants to the receiving waters , and dis functioning of the treatment plants. Depending on the sewer system there a r e es st'nt.iall y three types of untreated dischanges to the recei ving waters caused by the storm runoff: 1 ) combined sewer overflows ; 2) st.orm drainage i n separate systems and 3) overflows from infiltrate d sanitary sewers . Previously it 'was thought that the urban stor m runoff was quite clean . When there have appeared serious pollution problems with the untreated overflows from the old combined sewer systems the traditional answer in Fi n land has been to r econst ruct the combined systems to separate systems gradually . It was thought that the sewe r separation would solve the pollutional problems , because during storms the polluted sanitary sewage would then not be discharged untreated to the receiving waters . The treatment plants could then also function in more uni form conditions . However, recent studies have shown , that the urban runoff itself may be heavily polluted especially during the early phases of the runoff , when it gathers up pollutants from the surface. Howeve r the sewer separation would then st ill not. prevent storm water pollution and besides this t he total sewer separation is usually a very expensive and disrupti ve soluti on to th" problem in old urb an a r eClS· During wet. periods owerflows can also happen from the separated san itary sewers because infiltration of stormwaters to the sewers is common . Therefore often the best approach to the problem is to improve utilization of the old combined sewer system . The management alternati ves , when solving the operational problems of a sewer s y stem , can be di v'; ded in three main g r oups: source controls , collection system controls and improved treatment of the wastwater . The aim of the source controls is to altern ate and diminish the flow rates into the sewer system and to limi i.. the pollutional contamin
Expe ri e nces on mod e lling a nd simulation influent flow h as the diurnal rhythm which significant both qualitatively 'md quanti tati vely, as Fig. 2 presents. Ar.d as it is seen the waste concentrlltion and flow amount peaks occur simultaneously, which remarkably in creases waste load variations. ~s

Conventionally the planning procedure is realized acco rding to the assumption of stadc loading. Naturally under variable loading circumstances these assumptions cannot yield correct. operations. An illust.rat.ive example of t.his is that many treatment processes , planned by the sllme principles mClY operate very di ffe rent ly . The treatment efficiency varies accordin g to the diurnal rhytm. Eg . the percentage BOD re moval usually varies between 60 -9 5 % during a day in the activated sludge plant. This is indeed an important. fact from the point of view of recei ving wate rs . Rapid loading peaks, caused eg o by rain, go " through" "the plant usually almo llst without. tuning and cause in receiving waters a lo ading " shock ", which corresponds to several weeks' normal loading. That's why it is very essential to t.ry to minimize the rain as well a load variation effects . In principle there are following four differe nt ways to solve those problems : by controlling t.he internal pumpings of the plant, e . g . the sludge recycle and was ttne; rate of the activated sludge process , by the equali zation arrangel:Jent in the plant, by coordinating the operation of the sewer s ystem Rnd t.rerltment plant , by developing new process technology and lcy irnprovinl'- pl:mning methods , The mR.in Ri m of the recycle and wast in g rate control in the activated sludge process is to keep the operating point IlS optimum as possible . Some criteria which may realize t.his goal are e€",. : keeping the sludge loading rate constant and so maximize the growth poten';ial of bacterial mass; minimizing the process state deviations from steady state optimum . Besides this there are some other facts to be point ed out , ego keeping the bacterial mass well settleable. The last - men tioned fact arouses an interesting question about the sludge age distribution and its significance for the treatment effi.ciency . Ranta et . al (39) have presented some preli minary r esults of the sludge age dist.ribution cont rol. In li terat ure there are a great numb er of act i vated sludge process control studies . Among these the following works can be mentioned (3,5,6,7,10,11,22,27,28,39) . There are also some experiences (2 1, 36 , 38) from practical realizations of advanced control strategies for the a(,ti vated s ludge process. From the previos studies a fundamental result can be concluded: although the diurnal rhytm of the effl'uent flow can be remarkably smoothened, the average treatment efficiency increases only slight ly. This reflects the fact that the biological process is too " slow " to adapt

to the rapid hydraulic variations of the fluent flow.

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About the use of the equalization basins there is until now very little knowledge. Although it is apparent that the equalization basin is a very effective way to smoothen the diurnal rhytm and rain effects and thus to improve the treatment efficiency , the equali zat.ion basins are hardly used at all. Maybe this reflects some drawbacks of the equali zation basins, such as high investment costs and water spoiling effects, which may appear . The inte g rated control of the sewer and treat ment systems is quite important from the point of view of the rain damage preventation . The idea is to utilize the storage capacity of sewer network and so to smoothen rain effects. This ['equi res the coordination of the internal pumping of the sewer system and the continuous information about the treatment plant ' s state. However , this is still an open ques tion, and needs controllability and simulation studies of the inte g r eated sewage sys tem. Besides the treatment efficiency improving and loading equalization the deacrease of the maintenance costs such as energy, chemical and labor costs, can be realized by process control and instrumentation . The control of dissolved oxygen level in the activated sludge process i s one of these points. Be cause of the diurnal rhytm in the wasteload also the oxygen demand varies during a day. Without the oxygen l eve l control an over(or under- ) aeration and so also energy los ses may occur . It is commonly reported (21,38) that the oxygen level control saves 10-20 %in energy costs . Moreover , the overaeration has negative effects on the sludge flocculation and thus also to the settleabilityofsludge. Feat.ures of the simulation of sewage systems The physical phenomen associated with the storm water runoff and its influence on the whole sewage system is very complex in nature . Precipitat.ion falling on urban areas becomes cont aminated as it enters and passes through the human environment . The problem is how the contamination varies with time, what is the influence of the storm runoff on the quali ty of wastewaters in the sewer :1etwork, and what is the influence on the overflows and storm discharges and on the function of the treatment plants . The field studies have shown that sto rmw ate r characteristics are highly variable . The storm path , the collection system configuration and the draina.ge basin itself have adhesive influe nce on the quality of the wastewaters, combined sewer overflows and storm sewer discharges. The capability to analyze v:ori ous component flows and poll uti on loads th rouf!,hout the whole sewage system are the k('Y3 to better design of treatment and control systems . In studying the different management a ltern at.i ves a comprehensive mathe -

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matical mode l of t.he sewage system has the r e fore become a very useful t.ool. ThE' simul ation technique, that is th<:' represe ntat,ion of the physical system identi fi 8ble l;y the model , has been se l ected for modelling because of the comp l exity of th,o studied phenomen and berAilse the simulation tecr,r:ique per rr,irs a rel atively easy int,erpre t a;" i on of t.h e res ult s . A question arises how the simulation technique can be used as a tool in di fferent kinds of plannin r; , design 'emd cont rol problems. The simulation model doesn ' t give direct answe r s to such questions as what the optimal collect ion syste:n configuration is or what for examp l e the optimal sizes and locations of the planned detention basins are . The advantage of the simulation technique is that it allows principally a comprehensive description of the real system and it is very useful in studi!1g different dynamic al operation prob lems and control strategies . A promisin g ap proach to design problems can be the us e of le-ss detailed optimization mode l interact,i vely with th e sewage system si mulat i on mode 1 (53) . The treat.ment plant consist.s of several unit processes , and cboosing the process combin8tion in a given pl ann in g situation is not always clea r, Communi ties us ually set req ui re ments to the operation of the tre atme nt plant , and the plant designer must make his choices under the prevailing technical and economical conditions . The problems of pro cess combination selection are just typical to be solved by the simulation studies . Th i s kind of p r ob lems require the modulari ty of the simulation system so that the user of the system himself can choose different processes and define the interacti ons between various uni t processes. Also economical facts must be taken into account in the design work . In sim ulati on s tudies this is possible by th e cost prog ram, which simp ly executes investme nt and maintenance costs of the given plant structures and makes it possible to compare them economi cally . It must be remarked that cost program in simulation studies is 8lways only veri fYing and gives directly no possibilities for optimal des i gn . There are several " gui de " p ro c€' dures for the t reat.ment proceS'S p lruming t 8sk. Si. m'..ll at ·i on technique i.s suitable for st.ud in g "q llile prl)cedur e plant" in different loading situations and for getting information about the operation limits of the " qui de " plants , for fin ding lacks in design procedures and for searching for better design procedures . The main question of control studies is the plant controllability . By simUlation tech niques we can compare the efficienci es of vf'.ri ous cont rol st rategies and search for new control principles . External disturbances consist mainly of r apid and unexcept ional loading changes , which are caused by impUlsive pumpings in the sewer network and by rain . Simul ati on te chniq ues

make possib l e to study the effects of these dist IJrb ances in the t.reatment plant and also th.-c re vi vRl of t.he treatment plant after dis t.urb8nc~s . Th", controllability studies of sewer system as well as the utilization of t.he storage capacity of the sewer system and studing the sewage system as a wh ole have special importRnce in this connection .

MCDELLING OF' SEWER NETWORK AND TRtAT'l'Rc:ATt,1Z!'l'J' PLANT Modelling of Sever System In developing a comprehersi ve simulat ion model of the sewer syste m which also includes the simulation capability of the urban runoff , there appear a question of the model detail. Big modelling proble ms are for example a feasible description of the urban drainage bas in wi t.hout using many system parameters , whi ch a.r e not e asily available and the whole computation of the water qual ity . Moreover the key part of a sewer system model is in any case th e computation of the flow hydraulics throu/91 the sewer network. During a storm the re appear many different unsteady flow conditions in the spwe r pipes. The flow can be subcritical or supercritical or i t can be changing from one flow condition to the other . There can be an open channel flow in the p i pe or the pipe can be full and the flow pressurized . All th e water quality computations are based on the comput ation of the hydraulics . They must take into account , how the sedimented particles of different s i ze as the p ipe bottoms or on the d r Hinage bash watershed are carri ed by the flow . An important practic a l problem is the easy and flexible use of the model. Th e subsequent runs with different sel,rer s y stem confi gurations should in volve only input data changes . Aft·e r st udyi n g the di ffe r ent practi cal as pects of the sewe r system modelling , it was decided to use as a base model the S~n1t4 (Storm Water t.1 anagement ~10del) of U.S . Envi ronmental Protection Agency (17 , 18 ,1 9 , 20 , 54), in spite of its shortcomin gs in th e pipe flow computations . The model called SH1U is a dynamical simulation model , that can determine th e amount of runoff from a storm , rout e the runoff through a combined or a storm sewer s ystem with by user specified storage facilities , and finally route the water to the treatment plant or to speci al overflow treatment facilities. With the model it is possible to determine the amounts and locations of the local floo ding and combined sewer overflows in the net work as well as the flows and the water quali ty at vari ous l ocations of the wh ole system . The printed output of the mode l contains both tab les anc. graphs of hydrog raphs and pollutographs of BOD, coliform and total suspended solids at user- selected p oints in the s ystem . The model is especially oriented for simulation of short -- durated events like storms .

Experiences on modelling and simulation The model consists of over 10 000 Fortran statements. In SIMU-model (13,14,15,24,25,37),the Finnish modificF.l.tion of thp SWMM h'lve SI-units been used in the whole computati on, and the model has been implemented on the UNIVAC-l108 computer. Several errors found in t.he original model have been correct.ed and the parameters have been changed proper to Finnish circumstances. The model consists of 4 main groups of subroutines called blocks, which are defined as their own segments in the main storage, Fig. 3. The main segment and the biggest segment t.ake together approximately 77 ki lowords of main storage. All the blocks are independently functioning: the results of each of the blocks are st.ored on computer storage devices and are used as part of the input to other clocks. A short description of the different blocks is given. The Executive Block includes the main program and is defined as its own segment. It calls the other blocks wren needed and all interfaCing between the other blocks is maintenanced by this block. The Executive block includes also the subroutines for printing the graphs and one subroutine, which makeit possible to combine and manipulate the files generated by the other blocks. The latter subroutine is very useful, when simulating bigger networks. The Runoff Block simulates the routing of the rainfall over the drainage basin and through the smaller guttprs and pipes of the sewer system into the main sewer pipes. The block also determines the pollution load of the runoff entering the main sewe r network. The user gi ves as an input to the block the rainfall time history and the idealized description of the drainage basin. The dr8inage basin is discret.ized into sub- b8sins of constant land form characteristics. The location and characteristics of the gutters and pipes also have to be des cribed. In addi ti on the user must input street cleaning frequency and catcbasin data as well as the land use and the other features of the different areas of the basin. The Transport Block simulates the flow at storm runoff (computed wi th the Runoff Block) , the sanitary sewage and the to the system in filtrated water, t.hrough main sewer pipes and through the maxi mum of two optimal storage tanks. The flows can be routed to a maximum of 5 outlet points. The information of these points is written into a file, which can be read by the storage block or by the treatment plant model. If flows in the system becolll2 surcharged the flooding is assumed to occur at the closest upsystem manhole. The block also determines the dry weather flow quality and quantity, the infilt r'ation into the system and the water quality of the flows in the whole system. To model the system, this block requires that the system is discretized by the user into pipe segments of constant size slope and type joined by eit.her manholes, control structures as flow dividel's or storage tanks. The user defines the dimensions of the tank. The outlet device of the tank can be

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eit.her a pump, a weir or an orifice. The Storage Block simUlates the changes in t.he hydrographs and pollutographs as the sewage flows through a storage tank ar.J.througha special combined sever overflow or a stormwater t.reat.ment facility. Modelling of treatment plant More detailed studies can be found about the syst.em structure and programming technique in (Re f. 12,27,29,30,31) and about the unit process models in (Ref. 12,27,28,29). The basic structure of the program is given in Fig. 3. As we see, each unit process forms its own subprogram. Besides this we ne~d t~e subprograms gathering main program, WhlCh lS made by the user. The needed plant configuration is simply got by organizing the unit process s ubprograms in the correspon ding orde r as processes are in the plant. The influent flow both quality and quantity, is input by the special read-subprogran. In this connection should be remarked that the linkage bptween the sewer network and the treatment. plant models lS carried out by the read-subprogram. The basic structure of the unit process subprograms is the same. The most important task of the unit. process subprogram is to solve the discret.i zed process model one time step forward. The discretation algorithm is Euler method. For the time being the following process models have been developed: bar rack, primary clarifier, flotation process, activated sludge process with and without simultaneous precipi tat.i on, sludge di gestion and cent ri fuge. Calsium precipit.ation and filtration are just under study. The primary clarifier is in this study a rectangular settling basin. The modelling of the basin leads to the partial differential equation model (33,34). This ki~d of model is, however, not quite suitable for the simulation purposes and that I s why an idealization process is carried out, where the basin is divided into three operat.ional parts: solids separation, water and sludge flow. Conventionally the clari fie r models are base d 0:1 Pflanz overflow-rate theory (23) and they are static models in their nature. In this study the modelling work is based an the axial-dispersion model developed by Takamatsu et. al. (34) by taking into account the mathematical expression for the impulse response of the rectangular basin. The water and sludge flows are described by a tilll2 delay and an ideal stirred tank. These idealizations leads to time -variant differential difference equation model for each quality component. Schemati cally the acti vated sludge process includes RJl aeration baDin and a final clarifier, Influent wastewater is contacted with

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bacte r i al mass - acti vat ed sludge - in th " ae r ati on b a.qin, wh pre th e b act eri al growth an d the break up of org>.mic mCltter tak e place. The oxygen demand of the growth process is fulfilled by powerful at'ration of the ba:3in content , which accomplish es also mixing in the basin, but it is computationally too t.ime consuming for the whole plant simulation studies . In t.his st.udy the aeration bC!sin 1" supposed to be an ideal sti rred reactor. The bacterial growth is described by Monod model (16). I t is assumed t.hat there are one , " total " , organi c subst rate (BOD) and one ac tive , " total ", bacterial mass. This is , of course, an ide81izat.ion, be-cause the bact.erial populat.ion is very heterogenous in the acti vated sludge process . The cel l self- oxi dation, and the interacti on between the cell mass and total suspended solids as well as the interaction between total suspended solids and substrate are modelled. The mathematical description of thp aeration basin is a set of nonlinear time - variant differential equati.ons. The clari fi er is a rectangular sett l j ng b as in. Wh at was previ ous ly s ai d ahout se t t li n 8 b asi ns is adequate also in the act i vgt,ed sludge process.

The sewer system , which was studied with the simulation model , represents a typi cal small combined sewer area or the centre of Helsinki Fig. 4. Some characteristic features of this area are : drainage area of 21 hectares , 420 0 inhabi tants . 87 percent of land surface impervious, 95 percent multistorey ed blocks of flats a r e and 5 pf'rcent par'ks . The sewer network includes many pipes with quite small slopes and a steep one, wh ere the flow often is super - critica1. The network has one overf l ow point, where the e xcess flow under net weather conditions is diverted unt.reated to the sea. Thp rest of the flow continues in en inte r ceptor sewer, which is a part of the combined sewer network of th e whole centre area of Helsinki . The topography of the area is variabl e and the slope of the surface i s quit e steep in some pla('es. The simulated sewer system has at the same time been a test area of t he ci t y of Helsinki . There have been carried out flow quality and quantity monitoring by an automatic sampling device and two magnetic flowmeters (one for the overflow pipe and the other for the interceptor). They were all inst.alled in the flow diversion manhole lowest in the network . The precipitation measurements on the arE have been performed by an electrical r'llin gauge. Duri ng a test project in 1975 also the sewer sediments a.nd accumulation rates of t.he street impurity were analyzed. The measured average diurnal dry - weat.he r- flow from the area is 18 lis and it. was concluded that. approximately 5 lis of the flow was infiltrat.ed water and the rest. 13 lis was sanitary sewage . In this study a typical biological treatment

plant was designed to the sewer network using the norm81 finnish design guides. The plant includes following unit processes: bar rack, prim;'lfY c l arifier , act,ivated sludge process and sludge centrifuge . Reject waters from sludge centrifuge are fed back to the begi nning of water process. The average flow rate is 18 lis or 65 m3 /h and BOD load 480 kg/day. The normal diurnal rhytm of influent flow is pr·esented by Fig . 2. In the plant dpsi p;n procf'dlJre the measu~-ement flow is 27 lis or 97 m3/h (or 1.5 x average dry-weather floW) . Some data characterizing the plant are pre sent.ed in Table 1 . Simulation studies The simul at ions of the sewe r network are based on the field studies and measurements on the area. In t.he simulation studies the urban watershed of 21 hectares is represented by 21 ideali ze d small waterSheds Fig. 4 . In the computation they are handled as rectangulars with consbwt slopes. The sewer network is r epresented by 71 i deali ze d elements , whi ch consists of pipes (round and egg- shaped) , manholes , rainw ater wel ls , and one diversion (overflow) structure . The sewer system parameters have been fit.ted in acco rdance with the field studies and measurements and the reports f:8Ve been publ ished [ 13, 14, 15 , 24) . The dry - we8t.her- flow COJ~puta;;ions of the model, in c ludin g the di urnal and weak ly vari a tions of both water quality and quantity , were satisfactory when compuined with the measurements. Good agreement was also achieved in the computations when simulating smaller rain s , although some problems occured with the comput.ation o f suspended solids. During bi gger st.orms, when thpre are backwater effect.s and t.h .... flow oft.en bpcomes pressurized in tb e real ",Vstem , the r esults are not equally depend8ble, because of the model short comin gs . The same n aturally applies to the water qualit.y computations, which are based on thp former. The ai m of this paper is to study t he effects of the di fferent flow and water quality vari ations on a normally dimensioned treatment plant rathe r than stUdying the overflow prob lems of the network , The events exami ned were the di urnal dry - weather- flow variations , some real bigger storms and some' synthe tical' small r ains . The treat ment plant operation under the normal di urnal rhy tm is characterized by simUlation ,.tudies in Fig . 5. The percentage BOD and total solids removal are plotted vice the volume of the final cla rifier and the recycle flow rate. During the simulation ·studies all other measurement data have been kept constant . It can be remarked that by correct plant de sign. the percentage treatment effiency depends only slightly on the recycle flow rate strategy. But, however , the proportional control clearly smooths , Fig . 5 , the concentrations of effluent flow . Also the daily effluent BOD and total solids amounts from the plan t de crease considerably . The facts are important

Experiences on modelling and simulation from t h e recei vin@: water point o f vipw . Fig. 5 a l so demonstl'13tes the plBnt f'ensitivity to overload s i tuation~. It is int ~ r' Est ing to note that V = ,60 m corresponds to the 1'10('.FC surement flow 22 , 5 lis ( = 1.25 x average inf luent flow) Bnd VFC' = 550 m3 to the measurement flow 27 lis ( = 1.5 x 8verBge influent flow). The results 131so show that a n8rrow design in the hope of cost savings could not be re as on ab le. One interestin@: resul t is th8t in overload situations the recycle flow r8t" str8tegy hBS a great impor·tance. The right cont r'ol can " continue" the plant operot i on quite considerably . It is also obvious thot 0 great cons t ant recycle flow rate in overload situat.ions t.ends to cause the bacter'ial mass wiishout effect during ni@:ht time . This is seen as t.he fast " b reakdown " at the t.reBt.ment. plant. efficiency . The fi rst type of rains cons i st ed of some small synthet.ical storms , whose dur'ation ware 2 hours and t.he average intensity 1 mm/h. 'rhis kind 0:' rain events are very common . From the quite imperfect rainstatisti"s of Helsinki it ',[85 estimated that. there is a order of 100 2 - hour storms yeat'l-.y , whose ,-,verage intensity is equal or bigger th8n a,e storms studieri. Total rainfall co rr e~;ponds to the daily aver'age during a year in Helsinki city . The results are gathered in Tflble 2, whrrp Q is the overfloviimit , ~ is the mAxirllunr t'1~8F r:l[-,e in th~ pl'rnt, TR iG\~e rise time or. f~ow r8te, eT" 1.S t~e tot"J "011 ej,; remrw,.,l ~,f'f'1 ,'1 ,>cy ( riIH'J~ g;j 'lny) . L'T''' e1'fluenL s"'liej,, """"Hit. f:"m tbp pl.'mt . e b 1\ t.h( · P.0D n~rnov~J. err iCJen,',V (.riunr;f, a d,.,y , L total err~u~nt BUD BOD and L ,]) IS t.otal effluent f.e) t·he receIvIng waters ,overflow + plant ~fflllent). The shape of intensi ty \ or the ITI8Xl mum flow and rise of the influent flow) hBS some effects t.o tre"tment efficiency . t18ybe the most. interesting result is that t.here exist.s an opt.imum overflow limit (respectively to totsl effluent to rec~i vine; wate rs for each r'ainin t ensity . It is also int eresting t.o note that there mi@:ht be an optimum overflow location: upstream in the network , lowst ream In the network or after mechanical tre;.Jtment in the plant .

C'9

The plant influent flow , overflow , and effluent flow rates as well as concentrations are plotted in case or in Fig . 6 . The peak in the influent total solids concentration is caused by the sedimentation in network pipes . It is clearly seen , in Fi g . 0 , the washout e ffe ct in the treatment plant caused by the hard hydraulic load: the bacterial mass is escaping from the final clarifier and this tends the total solids and also BOD-concentration to incre85e remarkab ly in the plant effluent. By the same time the recycle bacte rial mass concent rati on decreases heavi ly and can occasionally be near the level of aeration effluent . Although the duration of nain is short and its intensity small , the plant revival l asts relatively long time, its is near 24 hours .

473

Second the effect of some bigger storms which normally occur approximately twice a year were st.udied. The li mit of th e pverflow structure wss the same as in the real system that is 100 l/s. The flow r ate of 100 lis seemed to be quite too big for the biol ogical treatment plant. CONCLUSIONS The paper p re sents some simulation aspects and experiences of sewage systems. As the b8ckr()und the operational and manageme nt problems of sewage systems are discussed . This also moti vates t.h e process analysis and simulation studies of the sewage system . Modelling problems of the sewage system are discussed and the deve l oped model and simulation system is shortly reviewed. The simulation studies of a concrete, real sewage system are given as an example of the importance of the sys temat i c st udy of sewe r networks and waste water treatment plants. Because of the growing disadvantages in receiving waters there is a serious need to search new methods for improving the operation of the sewage systems . Process automation and inst rument ati on is an especi ally suitable method for increasing of process effici ency and for stabilation of process operation. How ever , this implies a systematic study at process dynami cs and system operation . Be cause we a.re facing very complex and interact i ve system , simUlation technique seems to be an effective way for controllability and different transient studies. Some si mUlati on res ults are presente d . They are an example about problems, Hh ich can be typically solved by simulation . Int,'res ting results and conclusions can be noticed . But sOlTle facts can be pointed out. The concl usions referin g to treatment plant are quite general flnd they reflect common plant propert1 f'S . CO:lversely the conclusions and remarks concerning the whole sewage system or especi "lly the sewer network are restricted only to the case under study. This is because of t.ha.t t.he drainage basin and sewer network configuration have a decisi ve influence on the transient properties whole "ystem ' s and r,nn pffect.s .

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Expe ri ence s on mod e ll ing and simu l a t ion

475

Feedforward control of an acti vated sludge process , Wat.Res. , 7 , pp 525 - 535 , 1973 4. Brouzes, P.; Control of activated sludge p r ocess: app l ications , }later Rese a rch , 6 , pp 451 - 454 , 1972 . 5. Bryant , J . O.; Wilcox , L. C.; Real- time simulation of the conventiona l acti vated sludge process , Proc . the Joint Autom . Cont. of the American Automatic Council,pp 70 1p9 16, 1972. 6. Busby , J.B .; Andrews, J . F . ; Dynamic mode l ling and control strategies for the acti vated sludge process, Journal WPCF, 47 N:o 5, 1975. 7. Collins, A. S.: Gilliland, B. E . : Control of anaerobic dige s tion process , Journal of the Env . Eng. Div . , Proc . ASCE, 100 , N:o 2 , 1972 . 8. Department of the Int erior ; FederAl Water Quality Administration; Detroit sc'wer monitoring and remote> control , Dt't.r'oit , 1971. 9. Environmental Protection Agen..-y; Feas i bility of computer control of wMteW'3ter treat ment , Water Control Research St'ries , 17090 DOY 12/70, Washington , 1970 . 10. Graef , S . P . ; Andrews, J . F.; Stab ility and cont rol of an a.erob i c di gesti on, J our-lIal WPCF , 46 , N:o 4, 1974. 11. Hiimiiliiinen, R.P.; Halme , A. ; Gyllenbprg , A. ; A control model for activated sludge wast ewate r treatment proce ss , Proc. 6th IFAC World Congress Boston , Mass. USA, 1975. 12 . Kai l a , J . ; Ranta, J . ; Rummukainen, R.; Yletyin e n, P .; Dynamic analysis of sewage systems, SITRA, Rese
13 . Melanen , M.; Pingoud, K. ; Yletyinen, P. ; Simul ation model of sewer network, Gene r a l Part , SITRA Research Report , Otan i " m.i 1976. (in Finnlsh with English Summary)

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14. Melanen, M. ; Pingoud, K. ; Yletyinen , P.: Simulation model of sewer network Users manual , SITRA Research Report , Otaniemi 19 76 (in Finnish with Eng l ish Summary)

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Rain transients, case one: Flow rate and overflow rate from the network; network effluent concentration, plant effluent concentration REFERENCES

1. Aarinen, R. ; Ti rkk onpn,J .; Halme , A. ; Instrumentation and Control Strategies for Act i v ll.t ed Sludge Plant . Tampe r e Uni ve nod t.y of Technology, Control Engineering Laboratory, Research Report No 2, 1976 (in Finnish) 2. Leiser , C.P. ; Comput er Man agement of a combined sewer system , EPA- 6 70/2 - 74- 022, Ohio 1974 . 3.

Brett , R. W. ; Ke r mode , R. I. ; Burrus, B.C . ;

15. Melanen, M. ; Yletyinen, P.; Pingoud, K.; Ilmavirta, A.; Simulation mode l of sewer net work , Model verification, SITRA Research Report, ()taniemi 1976 . 16. Monod , J. ; La technique des cultures conti nues; theorie et applications. Ann. Inst . Pasteur , 79 , 4 , 1950 . 17 . Metcalf & Eddy Inc.; Un iversity of Florida; Water Resources Engineers Inc . ; Storm wate r management model , I - Final renort , EPA, Hater Pollution Control Research Series , 11024 doc 07/71 , 1971. 18 . Metcalf & Eddy Inc.; University of Florida; Water Resources Engineers Inc . ; Storm water management model, 11 - User ' s manual, EPA , Water Pollution Control Research Spries , 11 024 DOC 08/7 1, 1971 . 19 . Metcalf & Eddy Inc . ; University of Florida; Water Resources Engineers Inc.; Storm Water management model , III - Verification and testing, EPA , Water Pollution Control Re -

476 search Series ,

J. Ranta , K. Pingo uc an d A. Ha l me 1 102 4 Doe 09/7 1, 197 1.

20. Metcalf & Eddy Inc .; University rida ; Water Resources Engineers Inc . ; Wate r man agerrent model , IV - Program EPA , Water Pollution Contro l Research 1 1(12 4 DOC 10/7 1, 1971 .

of FloStorm li s ting , Se r ies ,

2 1. Nage l , C. A.; State of the Technology Semi - Automati c Cor.~rol of acti vated sludge trell,tme n t p l ants , Municipal Environmental Resea r ch LAboratory , EPA- bOO/2-75 - 058 . 1975 . 22 . Ohls80n , G. ; DahlqV±st , K.J .; Ulmgren , L.; Control problems in wastewater treatment p l ants . The Axel Johnson Institute for Indu.s t.:-i al Resear ch , Sweden . No date. 23 . Pflanz , P . ; In Advances in Water Pollution Research , p . 569 , ed . Jenkins , Pergamon Press , London , 1969. 2 4. Pingoud , K. ; Melanen , M. , Yletyinen , P.; Si mul ation modpl of sewer n etwork , Programs, SITRA , ResPClrch Report, OtAnierni 1976. (in Fi nn i sh with English Summary) 2,) . Yletyin e n, P .; MeL,nen . M.; Kaila , J . : Pi ngou d , K. ; Ylii- Soit;inmiiki , E . ; Finnish SWM.l-l Modi f i cation , Its Verification , Usage in Design an d Furth",r Development, EPA- SWMM Users ' Meet i ng , Toronto , Canada , 1976 . 26 . Poduska , R.A.; Andrews, J . F .; Dynamics of n i trifiCAtion in the activated sludge process , ,Journal WPCF , 47, N: 0 11 , 1975.

irol Systems, ColoradO , State Uni versi ty , ~4et.ropoli tan W8t er Inte l ligence Systems Project , Technical Report N:o 8 , PB 212 576 . 36. Wells, C.; Stepner , D.; Automati c con t.rol of rJissolved oxyegen in the Palo Al to regional w'.lstewater t reat.rnent plant , Proc . 65th Annual ~~eet in g of t.h e A. I .Ch.E . , 1972 . Pingoud, K.; t4e lan en , ~4 . ; Yletyinen , P .; 37 . Simulll,tion model ofa sewe r system, SIMS- mee ting - 76 , T8mpere , 1976 , (in Swedi,,". ) 38 . Peters8ck , J . F. ' Smith , R.G . ; Advanced Automatic Cont.rol St'.lrtegies for the Activ8ted Sludge Treat ment. pr-o<·pss. EPA- 670/2- 75 - 039 , 1975 . Rant8 , ,T.; K'lit81a, V. ; Halme, A.: and s i rnul"t i on of bacterial population '.lge distribution in activ'.ltedsludge plant, p"per present "rJ i [j IPA C Wo r'ksh op on Systems 8n:;lysis appli l''.l.ti~'ns to ,;omplex pr·oe; n ,mmps . Fielsko Biala, Poland , 1977 . 39 .

~.10delling

Lindrolm , O.G . ; Modelling of sewerage 40 . systems , Norwec;irm Institute for Water Re search , 1973. 41. Field, R. ; Laf~e r . J.A. ; IJrbAn Runoff Pollution Control-Str]tp of thp Art , Journal of the Env ... Er~_Div..:. . Pro:' . AS(;E, EEl 19'75. 42 . Lnbadie , ;' . W. ; Grigg . N. S . ; Bradford,B . ; Automnt.ic Control of 1Il,r't3P - scalt' Combined Sewer Syst ems , Jour'n81 of th<' Env . Eng . Div . P roc. ASCE . EE 1-:-T915-.~----------

27 . Rant.'1- , J .; Dynamic models and simulation 43 . j\1an Loong Chan ; Optimal Real Ti me Conof wastewater t.reatment processes , Helsinki t.ro l of Urban St.o rmw 8t.e r Dra inage , Studies in Uni versit.y of Technology , Systems Th e ory Laboth e An ll,lysis of t0et ropolit.an Wat.er Resource ratory , Rese arch Report C 25 , 1976 (in Finnish) . Syst.ems , Volume X, Technic8.1 Report N:o 87. 1974 . 28 . Ranta , J . ; Hiimiiliiinen , R.; Rummukainen , Reinicke , K. ; Polak , E .; A Computer 44 . R.: Gyl l enbprg , A. ; Kaila , J. ; Halme , A. ; (;ontrol1ed Stratel'Y fo r an Open Channel Waste Ylety i nen , P .; Simulation and cont.rol of a Hater System , in System Simu lat.ion in Water biologi cal wastewat.er t.reatment sy:~tem . He l Resou rce s (ed . C. C. Vanst.eenkist.e) , North s i nki Universit.y of Technology , Syst.ems Th eory Ilollan d , 1976. Laboratory, Report '3 25 , 1975 . (Paper presen45 . Wynn , C.B .; Moo re , J. B.; The Applicat.ed i n the Soviet - Finish s ci. ,~nti fi c - t. e chni cal tion of Opt.imal Li near Re(l:ulator Theory to a symposium on "Cybernet.ic systems modelling in b i o l ogy and medicine ", in Kiev 15 .- 19 . 9 .1 975) . Problem in \~ater Pollut.ion , IEEE Trans. Act . on systems , Man and Cybernetics , sl'4C- 3 , No 5 , 29 . Ranta , J .; Rummukainen , R . ; Kai la , J. ; 1973 . Modell i ng of sewage treatment plants, Proc . 46 . Trot ta , P . D. ; On- line Adaptive Control Simulation - 75 , Acta Press , Zurich 1975 . for Combi n ed Sc'wer Syst.ems , Wat.er Reso urce 30 . Rant.ll" J . ; Rummukainen , R. ; Programming System Program , Colorado St.ate Uni versi ty , 1976 . techniques in a simUlation package for waste Grigg , N. S .; Labll,die , J . W.; Wenzel , H.G . ; 47 . water treatment plants . SH1S - !,1eet ing , Taripere , Met rop olitan Hater Intelligence Syst.ems , Comp1976 . let.ion Report - Phase Ill , Colorll,do State Uni 3 1. Ranta, J .; Rummukainen , R. ; Kaila , J.; versit.y , Colorado 1974 . Simulat i on model of wastewll,ter treatment. plants. Proc . the ~:econd Nat.ionll,l Meet.ing on Biophysics 48. T.:;gp .. , J . A. : Smit.h , W. G.; Urban Stormwater j·.lanagement and Technology , An As 8nd BiotechnoloR{ in Finland , Espoo 1976 . sessment. EP.l\ - 670/2- 74- o40 32. Rebhlill , M. ; Anulm'Jn . Y. : EV81u .,tior. of hydr8ulic effi('ienC'y of s(; rJimentCition busins , JournA l of the S"m . Eng. Div . , Proc. ASCE, Sll , N: 0 5 , 1965. -33. Shib8, S .; Inone , Y . : [)ynamic r-espons e of settling basins , Journal of t'-J":' Env ~~E!£' Di~ , Proc. ASCE . 101 , N: o 5 . 197,) . ,4 . Tak8mll,t.su, T.; Naito . r~ . ; Gr,i.b8 , S.: Ueda , Y; Effect" of deposit resusptCnsion set t ling b8sin, Jourr181 of the Envi r . Eng . Div. , Proc. ASC~lO(1', N:o 4, 1974.

'.In

35. Tucker , L . C . ; Hill , D.W .: Guidel1n·.·s for t.he consideration of Automation and con-

49. Plan nin 8 and Wast.ewater /·lan agenent of a combined sewer system in San Fransicco , Metropolit.an Water Int.elligence Systems , Repo r t 10, Colorado 197 3 . 50 . Anderson, J.J.; Callery , R.L.; Remote Control of Combi.ned Sewer Owerflows, Journal WPCF , 46 , No . 1 1, 19 74 . 51 . Pew , K. A. ; Callery , R. L . ; Brandstetter , A.; Jlnderson, J . J. ; Data Acquisit.ion and Combined Se,-rer Controls in Cleveland JOllrnal WPCF , 45 , No . 1 1.