ML20206H144

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Direct Containment Heating Analysis W/Contain Computer Code, Ltr Rept
ML20206H144
Person / Time
Site: Sequoyah, 05000000
Issue date: 09/02/1986
From: Bergeron K, Carroll D, Tills J
JACK TILLS & ASSOCIATES, INC., SANDIA NATIONAL LABORATORIES
To: Silberberg M
NRC OFFICE OF NUCLEAR REGULATORY RESEARCH (RES)
Shared Package
ML20204G644 List:
References
CON-FIN-A-1146, CON-FIN-A-1198, CON-FIN-A-1412, RTR-NUREG-1150 NUDOCS 8704150271
Download: ML20206H144 (22)
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) * [* 2 6 Sandia National Laboratories i

Albuqueteue, New Mexico 87185 September 2, 1986 i

Mr. M. Silberberg, Chief Accident Evaluation Branch Office of Nuclear Reactor Research U. S. Nuclear Regulatory Commission Washington, D. C. 20555 i

Dear Mel,

requested a short time ago that we in the CONTAIN code project Tim Lee l

cpply the newly-developed Direct Containment Heating (DCH) models in the CONTAIN code to the sequoyah ice condenser plant in a sensitivity study for Appendix J of NUREG-1150.

In view of the high priority assigned by NRC to these issue

papers, and in view of the rapidly disappearing i

window of time before the deadline for NUREG-1150, we have devoted an j

intensive effort.since then to producing the letter report which we are now transmitting to you.

principal results of the study are given in Table 2 and Figure 3 of The letter report.

We think these results are extremely important and the quite interesting. It should be kept in mind, of course, that this also study is different from the simpler analyses of DCH in Surry performed the CLWG and reviewed in the current draft of Section J.5 of NUREG-for 1150; in particular, the calculations are not intended to be bounding.

In

fact, all parameters in the calculation except the two sensitivity parameters and the amount of pre-existing hydrogen in containment (see i

below) were chosen to have values which were our best-estimates; the Sequoyah TMLB' was our principal guide for'many of these l

BMI-2104 choices.

Thus, while the pressures shown in Figure 3 are lower than for the worst cases in the Surry CLWG calculations, it should not be concluded that the DCH problem is worse for Surry than for Sequoyah.

l Naturally, the details of these results are dependent on the choices made for uncertain parameters and assumptions about accident progression.

However, a number of qualitative conclusions emerge from which we believe will have rather broad applicability.

study this This r

it is clear that the dominant metal reaction is with steam.

First,a consequence of the lack of oxygen in the environment of the debris is l

particles early in their histories, and the high reaction rates.

one cannot isolate the DCH phenomenon from hydrogen combustion.

Second, used default combustion criteria, but it is highly In this
study, we likely that they are inappropriate.

Lower combustion thresholds,

however, would probably not dramatically change the likelihood of containment failure for Sequoyah.

However, one feature which will be 8704150271 870408 i

PDR NUREG 1150 C PDR 2f

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M. Silberberg September 2, 1966 c

censitive to the combustion threshold is the location of the sharp around 20% melt ejection in Figure 3.? This transition i

transition seen is due to the onset of hydrogen combustion (i.e., no burns occur at melt j

fractions below this point).

The location of the transition is also offected by the presence of hydrogen in the containment just before vessel failure.

In these calculations, no pre-existing hydrogen was assumed (the hypothesis being that independently-powered igniters or recombiners removed the hydrogen and corresponding amount of oxygen prior to vessel failure).

Non-zero pre-existing hydrogen would shift the transition to the left.

We feel that our treatment of pre-existing is somewhat non-conservative, but we made this choice in hydrogen. here to have a cleaner sensitivity study,(i.e., we are not interested orderpresent in the problem of combined steamcspike and hydrogen burns in at the absence of DCH--a scenario demonstrated by SARRP to be a major concern by itself.)

/

A third conclusion is that the results are' auch less sensitive to assumptions about de-entrainment (or trapping) than has been previously thought.

The two choices of debris de-entrainment time, 0.3 and 10

ceconds, are, in my mind, reasonable estimates of the upper and lower bounds of the plausible range for this parameter.

But, as Figure 3

shows, the differences in peak pressure are not great (though peak temperatures show a

greater sensitivity.)

This is an extremely important

result, and it has important implications for model development priorities, for experimental matrix
designs, and for assessment of plant geometry effects.

For example, it would suggest that the heuristic plant geometry categorization proposed by IDCOR may be less relevant than they suggest.

The study of DCH phenomena with CONTAIN will continue into the next fiscal

year, of
course, supported in part by the SASA and QUECLA projects.

In fact, we have already developed and exercised an improved and heat transfer (to be described in a forthcoming of mass treatment paper at the ACS conference in Anaheim in October), and are developing a droplet field model.

However, for the Sequoyah calculations multi-size presented here, we applied the version of the model which was presented 4

at the April 1986 meetings on DCH in Silver Spring and Bethesda.

The reason for choosing this version is that the opportunity for peer review has taken place, and the code has been extensively exercised over the months.

Also, it is the version of the model which was so past four successful in semi-blind post-test predictions of the DCH-1 experiments (cf.

letter to T.

Lee, June 4,

1986).

For inclusion in a high-document such as NUREG-1150, therefore, it seemed prudent to visibility i

use the older version, especially since our experience with the improved models leads us to believe that they would not give significantly different results for the cases considered here.

summary, the sensitivity study we have done in support of the NUREG-In 1150 issue paper on DCH must be considered only part of the story of the ongoing progress in this rapidly evolving area, but it can serve an j

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/ Ssptemb3r 2, 1986 M. Silberberg

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-sg in conveying the basics of our current understanding important purpose of the phenomena.

We have a relatively high degree of confidence in these predictions (certainly more so than in the ultra-conservative CLwo calculation) and we feel that this work is suitable for inclusion in the issue paper.

Please let me know if you have any questions on this material.

Sincerely, J+

Kenneth D. Bergeron, Supervisor Containment Modelling Divsion j..

Encl.:

Letter report

" Direct Containment Heating Analysis with the CONTAIN Computer Code" V

cc: w/ encl:

h J. Mitchell, NRC/RES R. Meyer, NRC/RES P. Wood, NRC/RES T. Walker, NRC/RES F. Eltawila, NRC/NRR 11 6422 D. A. Powers 6422 W. W. Tarbell 6422 M. Pilch 6440 D. A. Dahlgren 6449 D. C. Williams j

6449 D.

E., Carroll 6449 J. L. Tills 6449 K. E. Washington 6449 File 3.7

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s Attachment to Latter from K. D. Bergeron to M. Silberberg, September '2,1986 y_

Direct Containment Beating Analysis with the CONTAIN Computer _ Code

  • K. D. Bergeron, D. E. Carroll, J. L. Tills

Containment Modeling Division 6449

[.

Sandia National Laboratories Albuquerque, NM 87185 i

1. Introduction phenomena of melt ejection, debris dispersal, c'nemical reactions and heat The transfer between debris, water and gases which collectively contribute to the Direct Containment Heating (DCH) phenomenon are extremely difficult 'to predict with confidence using existing calculational tools. An ongoing NRC research program is underway to study these processes experimentally, and it is expected that a significantly improved understanding of DCH will' result from these experiments.
However, in the interim, it is useful to analyze the with the best calculational _ tools available in order to assess the problem important uncertainties and to be able to interpret the' results of the experi-as efficiently as possible when the data become available.

There are a ments number of phenomena involved in direct heating (e.g., debris transport through i

complicated pathways) for which there are virtually no verified or verifiable better understood (e.g. heat and mass transfer models; tother ~ phenomena are from a suspended droplet). A model which treats the highly uncertain class of phenomena parametrically, and the better understood phenomena with best-models is therefore a reasonable goal for an interim calculational estimate tool.

This report describes an Interim Direct F*oting Model (IDRM) which has been developed as an module of the CONTAIN corrWtt code, and which is work supported by the United States Nuclear Regulatory Commission under j

  • This 1146,1198, and 1412 and performed at Sandia National Laboratories which FINS for the U.S. Department of Energy under Contract Number DE-AC04-is operated 76DP00789.
  • J. L. Tills and Associates, Albuquerque, NM

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provide an improved understanding of the uncertainties in the intended to accident sequences involving direct heating, and which can be of analysis of use in interpreting and guiding the DCH experiments. This model is then applied in a sensitivity study to the TM13' sequence at the Sequoyah ice condenser plant.

2. Backaroundt, Previous DCH Calculations The uncertain aspects of DCH limited early modeling efforts to relatively simple paremeter studies in which the mass and composition of the debris in the direct heating was simply assumed by the analyst.

participatingarbitrary assumptions were made concerning the degree of complete.

Similarly, ness of the oxidation of the metallic constituents of the debris with steam or oxygen in the atmosphere.

In October, 1983, the direct heating question was raised at a meeting of the Containment Loads Working Group (CLWG) in reference Problem No. 1 (SP-1), which was a THLB' sequence at a Zion-to tHe Standard In the next CLWG meeting at Palo Alto in February, 1984, CONTAIN like plant.

calculations of DCH for SP-1 and SP-2 were presented which were based on The energies were assuming varying amounts of energy transmitted to the gas.on the specified composition of the in side calculations based calculated debris and varying degrees of debris participation in the process.

of this calculational approach was that the equilibration of deficiency One between the debris and the gas was not explicitly taken into account, so heat that the sensitivity parameter was not the fraction of debris mass participating, but rather the fraction of the debris enthalpy transmitted to code, designated DHEAT, was developed which was this a new the gas.

ForCONTAIN in many respects (e.g., heat transfer to and conduction l

simpler than are neglected) but which explicitly equilibrated heat between in heat sinksgas, making it impossible for example to calculate a situation in debris and This code-gas was hotter than the debris at the end of the event.

which the was used extensively for the DCH parameter studies used in the CLVG final report, NUREG-1079, which was published in draft-for-review form in the summer However, DHEAT was limited in a number of ways; it was restricted to of 1985.

it neglected heat transfer to sinks, it did not a, single control volume,the atmosphere during the chemical reactions, and it add gas to the user to specify the fractions of participation of the debris, in remove or required transfer and also in terms of oxidation. However, it had the terms of heat The being extremely fast and well-suited to parameter studies.

of code has been informally distributed to a number of participants in the advantage DHEAT Accident Risk Reduction Program (SARRP) containment event tree experts A paper which Severe panel to assist in assessing the DCH problem for SARRP.CONTAIN a l

review includes both and Design (K. D. Bergeron and D. C. Williams, EED. 22, 153, 1985.)

Another model development effort which contributed to our understanding of DCH to M. Pilch, in support of the SPIT and HIPS experiment series which This model followed the trajectory of a single was due were fielded in 1984 and 1985.

the atmosphere under gravity. Unlike the through debris droplet falling this calculation tracked the debris temperature and

above, models described function of time, taking account of heat and mass transfer composition as a I

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. i limitations in the gas boundary layer surrounding the droplet. Atmosphere temperature and pressure was simultaneously tracked for a self-consistent calculation based on the simple picture of a field of droplets falling through single volume containment. This model and a number of the atmosphere of a sensitivity studies using it are presented in NUREG/CR-4051, SAND 85-2435.

In February,1986, L. Baker of Argonne National Laboratories presented a paper Diego ANS/ ENS meeting on direct heating modeling.

This was an at the San extension of the Baker-Just model for metal droplet oxidation which had been for LMFBR applications in the 60's.

Unlike other models discussed developedBaker's treatment explicitly considered liquid-side as well as gas-side

here, diffusion limitation on chemical reaction rate of a droplet moving through a gas environment.

Corradini and his colleagues and students at University of In another effort,developed computational models for heat transfer and chemical Wisconsin have reactions of debris suspended in the atmosphere in a code called DIRHEAT.

A of parameter studies with this code have been performed, and in variety addition UW personnel have used it in conjunction with a suite of containment (HECTR, KEDICI-M1, and CORCON) which were developed by Sandia analysis codes The direct heating models and calculations were documented in for the NRC.

two UW reports, designated UWRSR-34 and UWRSR-35.

In November, 1985, the CONTAIN code project at Sandia National Laboratories was requested by the NRC to develop improved models to serve the purpose of interim issue resolution, and also to assist in guiding or interpreting the data expected in early 1986 from the Surtsey facility.

It was experimental decided to improve the existing models by including mechanistic heat transfer and chemical reactions, and by allowing multiple volumes, but with debris volume controlled by relatively simple parametric transport from volume to models.

In the following sections the resulting model is described.

The features of the new model reflect the influence of the earlier models described above.

A number of model development efforts have taken place concerning melt ejection from the vessel and the cavity. These include work done at Sandia, University of Wisconsin. However, since the focus of the IDRM Argonne and work which is the subject of this report is on mass and heat transfer, these models will not be described here.

3. Eescriction of CONTAIN and the Interim Direct Heatine Model are two aspects of the new calculational capabilities under discussion:

There standard CONTAIN models and the new features of the IDHM.

These will be briefly discussed below, with no attempt at completeness.

Also to be discussed are verification calculations done to compare the new models against earlier calculational tools.

Finally, we will flag a number of modeling uncertainties of which the reader should be aware in order to put calcula-tional results in the proper perspective.

i l

4-3.1 Relevant CONTAIN Models CONTAIN is a system-level best-estimate containment analysis code specifically accident containment phenomena. Figure 1 designed for analysis of severe the phenomena modeled for a typical LVR problem.

schematically illustrates CONTAIN models can be found in the CONTAIN User's Manual, so Details of the only a brief description of the standard features which will be utilized in typical direct heating calculations will be presented here. All of the CONTAIN models are keyword-enabled, so if the appropriate keywc*;d does not the input deck, the model is not activated. Thus, for many direct appear in it would be unnecessary to activate the CONTAIN models heating calculations, for aerosol physics, fission product decay and transport, debris-concrete interactions, and a number of other features.

The features which would ordinarily be used include the following:

a.

Intercell flow. CONTAIN uses a control volume approach to gas each specified volume or cell as a well-mixed repository transport, treating Flow between cells occurs via an orifice flow correlation when of the gases.

a flow path of a given cross-sectional area and friction coefficient is specified between the cells.

Arbitrary interconnections between cells are allowed. An arbitrary number of computational cells is allowed.

b.

Two-phase gas-steam-water thermodynamics. A realistic equation state for two-phase water and a variety of non-condensible gases is solved of every time step to give the pressure and temperature of each computational at cell based on the internal energy and masses of the constituent gases.

c.

Heat transfer to structures. Each cell can have an arbitrary n==her of heat transfer structures inside the volume.

Heat transfer occurs via convection, condensation (including evaporation), and radiation betweer.

the gas and the structure surfaces.

Gas-structure radiation heat transfer sophisticated model for the emissivity of steam and utilizes a reasonably condensation model is applicable to both saturated and carbon dioxide.

The conditions.

Each structure can be represented as a atmospheric superheated a half-cylinder, or a half-sphere, and it can be composed of an planar slab, arbitrary number of layers of materials (e.g. steel, concrete, gas). Each the user through input, and the one-dimensional heat by layer is nodalized is solved to obtain the temperature at each point in the conduction equation film is allowed to collect at the structure surface A condensate material.

reaches a user-controlled depth, at which point the excess runs off 4

until it and is added to the water pool, if one is specified for that cell.

d.

Hydrogen combustion. The hydrogen burn model is taken from the EECTR code, which was developed at Sandia for the analysis of containment Unless burns have been problems involving hydrogen transport and combustion.it is assumed that an ignition source isf explicitly inactivated through input,the concentrations of hydrogen, oxygen, and always present, and that whena burn occurs.

Propagation from cell to cell steam are in a certain envelope, take place depending on whether certain other concentration criteria are All burns are treated as deflagrations occuring over a time period will satisfied.

5-determined by the characteristic len5th of the cell sed a flame speed which is calculated from correlations.

e. Pool boiling.

If a water pool is specified for a given cell, and a debris layer is present below the pool, heat transfer between the debris and and if the pressure-dependent boiling temperature is the water will occur, reached, the pool will boil.

f.

Ice condenser.

The ice condenser model involves both thermal-

' hydraulic and aerosol decontamination modeling, but since fission products are primary interest in a typical direct heating calculation, we will not not of describe the scrubbing model. The ice is modelled as a surface held at the which changes in area as the ice melts. Condensation heat temperature ice is modeled between the atmosphere and the ice with a thin water film transfer Radiation heat transfer to the ice from the gas is also separating the two.

modeled. The melted ice exits the cell and is added to the pool of a user-at a user-specified temperature.

Doors between the lower specified cell and the ice bed and between the ice bed and the upper containment compartment the being either one-way or two-way; in the latter case, can be modeled as be different depending on which direction the flow effective flow area can

occurs, g.

Containment Sprays.

Like the ice condenser, sprays have important effects on thermal-hydraulics as well as on radioisotope inventories, but the latter will not be discussed here.

It is assumed in the model that all droplets exiting the spray nozzle are the same size, but spray that the size can change through evaporation or condensation as the drop The fall velocity is the terminal velocity. Heat transfer from the falls.to the droplet t. 'ces place via the same condensation model as is used for for t..a ice condenser, except the Nusselt number used is that gas structures and When the sphere moving in a gas at the terminal velocity.

appropriate to a droplets reach the floor, they are added to that cell's water pool (or another cell's pool, if the user so specifies in input.)

3.2 Direct Heatine Models

)

modification is that a new field has been added to the code.

principal The debris field is like the gas in that each cell is a well-mixed repository The However, the debris mass in each cell is of the debris mass and its energy.

assumed to be composed of a large number of spherical droplets having A realistic debris equation of state identical composition and temperature.

is solved at each time step to give the debris temperature in each cell. There are five debris constituents allowed: Zr, Zr0, Fe, Feo, and UO '

2 2

flows with the gas in a dispersed droplet mode; that is to say, The debris is transported from one cell to the next with the gas in proportion to debris Such a the mass of debris and gas present in the donor cell at each timestep.

model is sometimes referred to as a homogeneous flow model.

In the cavity can be justified by the fact that gas velocities are so

area, this approach which impinge on surfaces are quickly resuspended in the high that droplets i

i

i gas stream and fragment down to about the maximum Weber-stable radius.

However, in the model, the droplet diameter, D. 18 8pecified in input and d

This picture of debris transport does not change throughout the calculation.of the critical Kutateladze velocity is at gas velocities well in excess

_ justified by theory, the HIPS experiments, and simulant fluid experiments conducted at Brookhaven.

However, as gas velocities drop, it is to be expected that some de-entrainment This is analogous to the that is not followed by re-entrainment.

will occur transition from dispersed droplet flow to annular flow in two-phase flow in

However, so little is known about the flow patterns under these in the complex geometries and large scales of reactor containments pipes.

conditions it is not possible to develop reasonable mechanistic models of two-phase the situation under consideration, especially when the material is that flow for of eutectic, metal and oxides at an unknown temperature.

an unknown mixture process of de-entrainment is treated parametrically:

a user-the Therefore, removal rate, f, is assigned to each cell, and in each second, that specified cell's debris content is assumed to be removed from the fraction of thedeposited in a debris layer at the bottom of the cell (if the atmosphere and The remaining debris layer has been enabled for that cell in the input deck).

transported, without slip, with the gas to downstream suspended debris isof the debris contributes to the inertia of the gas if the cells.

The mass in the flow equation is important. The mass and energy of acceleration term cell is added to that cell's debris field, resulting in a debris entering a new debris temperature and a new composition.

Heat transfer occurs between the debris and the gas via convection and heat transfer coefficient is calculated based on a radiation.

A convection Reynolds correlation for turbulent flow over a sphere, with a droplet

velocity, v,

for cell i relative to the gas specified by the user. The g

Nusselt number is the same as used by Pilch in NUREG/CR-4053, and is given by:

Nu - 2.0 + 0.6 (Re /2)(Pr /3)

(1) l

)

The use of a the Reynolds number and Pr is the Prandt1 number.

I where Re is non-zero relative velocity of the droplets is not necessarily inconsistent

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with the zero-slip assumption when it is realized that the debris field consists of a collection of particles moving in random directions superimposed on an overall drift equal to the gas velocity.

the radiation heat transfer from the droplets are available:

I Two models for In the gray gas model, radiation heat gray gas model and the clear gas model.between the debris and a gray, non-transmitting l

transmission assumed.

A multiplier, a,

is provided to reduce the heat transfer occurs g

the gas from the black body value. This multiplier can be to be the product of the debris and gas emissivities and any other transfer to reduction or enhancement factors which might come into play in gas-debris considered i

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. radiation heat transfer.

With the multiplier equal to 1, this model will probably over-estimate heat transfer to the gas.

The clear gas model assumes the gas is transparent to debris radiation and that the debris radiates to heat sink surfaces without attenuation. The maximum interfacial area for this heat transfer is the structure surface area, a multiplier, o,, is provided to reduce this area in order to account for but the possibility that not all of the structure area can "see" the debris plume, or to account for non-unity emissivity, etc. With this multiplier equal to one, the clear gas model will underestimate heat transfer to the gas from the debris.

4 Chemical reactions can take place at the surface of the droplets if they contain oxidizable metal. The metal oxidation reactions allowed are performed in a hierarchical fashion in the following order:

(1.) Zr + O Zr0 2

2 (2.)

2 Fe + O 2 Fe0 2

(3.)

Zr + 2 H O Zr02+2H2 2

(4.) Fe + HO Fe0 + H 2

2 (5.)

2H+O 2HO 2

2 2

The first four reactions are limited to (1.) the mass of metal in the droplet and/or (2.)

the mass of oxygen or steam which can diffuse throught the boundary layer to the droplet surface from the bulk gas. The heat from these reactions is added to the droplet field energy. All mass inventories (debris appropriately updated in accordance with the extent of and gas fields) are each reaction.

The fifth reaction is marked with an asterisk because it is different from the normal hydrogen combustion event discussed in Section 3.1.

The only hydrogen involved in this reaction is the by-product of reactions 3 and 4, and the oxygen mass, if any, is taken from the bulk gas, rather than the quantity which can diffuse to the droplet surface. This reaction represents the result of diffusion of the hydrogen byproduct back to the bulk gas.

It is assumed that the near-drop environment is so hot that hydrogen-oxygen recombination occurs without need of a flame or spark source.

It is also assumed that the back-flow of hydrogen does not impede the diffusion of oxygen, a reasonable assumption given the high diffusivity of hydrogen, and the uncertainty in other aspects of the mass transport model. The heat from this reaction is added to the bulk gas, not to the debris.

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8-Oxidation of UO by oxygen is not treated in this model since there is 2

and since it evidence that it is not favored at the temperatures of interest, The chemical reactions discussed above has little significance energetically. diffusion of the oxidizing gases through the are rate-limited in only one way:

around each droplet.

It is also possible that the layer gas boundary limited by diffusion on the droplet side, either in the liquid reactions are or in a solid crust. Baker's ANS/ ENS paper was based on a particular phase model for the droplet-side diffusion limitation, for example. However, there For example, the is a great deal of uncertainty in how to model this process.

solubility of the oxides in the metal phases must be considered. Also, one must consider the possibility of mixing inside the droplet due to internal For the present model, therefore, droplet side limitations circulation loops.

will rely on two parametric are not modeled mechanistically; instead, we features.

First, all reactions are shut off at a user-specified droplet temperature, T,.

Second, multipliers on the diffusivity of the gases is and a fr xygen and steam diffusi-available; these are designated a,x st vities, respectively.

In a gross sense, reducing the diffusivity will limit the reaction in a way similar to the liquid side limit, though the dependence on droplet composition will not be the same.

the droplet is calculated with a mass transfer coefficient Mass transfer to In other words the dimension-based on a heat transfer / mass transfer analogy.

Sherwood number, Sh, is calculated from a correlation quite like that of less the Nusselt correlation in Eq. 1, except the Frandel number is replaced by the Schmidt number:

Sh - 2.0 + 0.6 (Re / )(Sc ! )

(2) for diffusion of oxygen and steam to the droplets is equal to used The area of a single droplet times the total number of droplets in the cell.

the areathis treatment does not properly account for the fact that at any given Since time there will actually be a distribution of particle compositions, some with unoxidized metal left and some without, this treatment may overestimate the reaction rates. Therefore, in a model variation, a multiplier on the area for diffusion is used which is based on an estimate of the fraction of debris particles which still have some metal left.

The Sch=idt nu=ber in Eq. (2) is given by (4)

E Sc -

pD the gas viscosity, p is the gas density, and D is the binary gas where p is (Equ. 16.3-1, p. 505, diffusivity in air, given by Bird, Stewart and Lightfoot i

. 1960 edition).

All gas properties are evaluated at conditions intermediate between the droplet and the bulk gas.

exercise, a simple problem was defined which could be run As a verification both on the Pilch model from NUREG/CR-4053, and on an improved version of for gas inventory changes due to chemical reactions).

DHEAT (which accounts The problem involved injecting debris consisting of four materials into an air No 10 m/s, and observing the pressure and temperature rises.

environment at haat sinks were modeled, and no trapping was allowed.

After thermal equilibration had been achieved, the CONTAIN and DHEAT pressures and The Pilch model agreed within about 74 in temperatures agreed to within 0.34.

the total number of moles of gas due to temperature, but it does not adjust More important, since the Pilch model calculates droplet the reactions.

function of time, it is possible to compare the time required behavior as a for the droplet to reach its peak temperature. On this quantity, the Pilch model and CONTAIN agreed to within 10-154. Given the differences in the models, this was considered adequate verification.

3.3 Modeline Uncertainties There are many uncertainties in modeling a process as complex and poorly as the melt-ejection / direct heating problem.

It is important that understood of any calculations using this model be interpreted in the light the results of these uncertainties.

(This is true of all direct heating calculations performed to date, though it is too often true that the uncertainties are paid little attention.) As indicated in the model descriptions, our basic strategy for dealing with these uncertainties is to provide adjustable parameters (defaulted to our best estimates) so that sensitivity studies can be performed Many of the limitations of the present model have been through input. the course of the model descriptions, but it is worth while to identified in In the list below, we identify a nuiber of the re-iterate some of them here.

or input uncertainties, and indicate what control the user has in modeling parameters to account for each uncertainty. Ongoing model development varying will alleviate many of the problems identified below.

Fraction of debris eieeted. This amount depends on the extent of melting at the time of vessel failure, on the location of the break, and Very little certainty is core possibly on the way the hole in the vessel enlarges.Since the mass and composition of the ejec on these subjects.

possible debris is specified as tabular input, this uncertainty is fully controlled by the user.

The droplet size may be estimated on the basis of a Droelet size.

stability criterion, but smaller droplets are possible depending on the if nature of the fragmentation processes, and larger droplets are possible Weber velocities are smaller than assumed in the Weber relative local gas-debris Therefore, the diameter itself is specified by the user.

number calculation.

This uncertainty is possibly the most intractable Debris transoort.

principal purposes of the Surtsey experiment in the problem.

One of the series and the simulant fluid experiments at Brookhaven is to improve our l

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understanding of the way debris-gas mixtures can be transported through complicated pathways and around obstacles. De-entrainment and isolation from the high velocity flow region is an important_ potential ILuitation on debris transport.

So is freezing on metal structures, although conduction limita-tions may prevent this process from being very efficient if the debris expulsion time is short. Freezing on concrete is a little more difficult to

credit, since outgassing and/or spalling of the concrete will prevent the-debris from " sticking". The principal control the user has on this process is l

the trapping fraction, which removes debris at a rate which is proportional to the, amount of debris in the cell. The removed debris is deposited in the i

debris layer, and does not participate in continued direct heating.

j Heat transfer.

There is some uncertainty concerning how effective i

the mixing between the gas and the debris plume might be..The Nusselt Eq. 1 assumes a mean droplet velocity relative to the flowing i

correlation in gas which is quite arbitrary.

Similarly, in the clear gas option radiation heat transfer is based on good optical contact between the walls and the debris plume, and that the plume exterior is at essentially the same temperature as the bulk debris.

To study that uncertainty, the user can l

sdjust the interfacial area. The gray gas model has no such problem, but it probably overestimates the heating of the gas and underestimates the heating of the walls.

On the other hand, the presence of copious quantities of l

aerosols and steam probably make the gray gas model more reasonable than the clear gas model.

i chemical reactions. The chemistry model is quite simple, and it is

{

that the actual processes going on would be far more complex.

One likely important assumption is the neglect of a limitation on diffusion on the liquid side of the droplet / atmosphere interface.

A solid crust could inhibit gas diffusion even more. To accomodate this uncertainty, the user I

oxidizing control of an overall multiplier on the diffusivity, which can be used as l

has i

a surrogate for the liquid side limit. The temperature cutoff serves the purpose of simulating the effects of the crust formation and freezing of a 1

droplet, and the value of the cutoff temperature is available throught input

]

)

to the user.

Flownath and control volume confiruration. As is always the case with computational simulations, part of the model is the nodalization. Of i

particular concern is the possibility that the flow paths specified are incorrect after the melt ejection begins. For example, dynamic loading of the boundaries' of the cavity region in Sequoyah could result in a failure which j

would create a new flow path to different parts of the containment. The j

analyst can study such possibilities with alternate nodalizations and flowpaths between cells which can only open when the pressure difference 2

number specified in the input.

(This option is a standard CONTAIN exceeds a I

feature.)

Effect of distribution of droelet nrocerties.

The well-mixed i

assumption applied to the droplet field requires that material entering a cell l

mixed with the existing cell material, resulting in a new effective single l

be i

drop properties (composition, temperature, etc.) In reality, the history of 1

i I

. each droplet is different, and there will be a continuous distribution of properties.

This difference may not be important for some processes, such as heat transfer, since there may be good radiant heat exchange among the droplets, and the overall heat transfer rate may not be very sensitive to the width of~ the various distributions.

It may be more important for chemical reactions, since all of the unreacted metal may reside in a relatively small number of droplets.

As discussed above, a model variation is available to take the latter effect into account in a simple way, but there is still a good deal of residual uncertainty associated with this problem.

Hydromen combustion.

In the chemistry model used, the hydrogen liberated by metal steam reactions on the surface of the suspended drops is assumed to recombine with the oxygen in the bulk. However, it is also possible that the pre-existing hydrogen may be ignited by the melt dispersal Conventional steam inerting criteria are probably irrelevant for this event.

situation.

A modification of CONTAIN has been developed to allow the user to modify the ignition criteria for the gas concentrations, but what is probably needed is an ignition criterion based on cell gas temperature or debris temperature, or some kind of average.

Such a capability for CONTAIN is under development.

4. IDEM Calculations of the Beauovah Ice Condenser Plant Containment Resnonse to the TMLB' Station Blackout DCH Scenario.

In this section, we will present direct Containment Heating calculations performed with the IDHM for the Sequoyah ice condenser plant ~. Before discussing these calculations, functional differences between the Sequoyah containment and conventional large dry containment designs which may affect containment response to a DCH event are worth noting.

Sequoyah is a small containment with a failure pressure slightly above 4 bars.

In comparison, large dry containments such as Surry typically have design pressures in the vicinity of 9 bars.

The relatively low failure pressure of Sequoyah is-primarily a consequence of the ability of the ice condenser to remove large quantities of blowdown steam, thereby dramatically reducing peak containment pressures in the design basis accident scenario (double-ended severance LOCA).

l In a DCH event, hydrogen burns fueled by copious amounts of ex-vessel hydrogen not greatly mitigated by the and other relevant DCH phenomena which are i

I of the ice condenser may give rise to a previously unforseen threat.

presence CONTAIN IDHM predictions of Sequoyah peak pressures in a TMLB' DCH scenario are therefore warranted.

4.1 Problem Descrintion The main objective of this study is to estimate peak containment pressure as a function of corium ejection fraction for the Sequoyah ice-condenser plant with performed using a-3 cell nodalization as the IDRM.

The calculations were shown in Figure 2.

The standard 3 cell CONTAIN input deck for Sequoyah was supplemented by the required IDHM input parameters and corium source tables.

Relevant IDRM options, corium source masses, vessel blowdown characteristics,

4 and other user-selectable inputs chosen for the calculations are discussed This discussion will focus on those parameters most closely related to below.

the modeling uncertainties outlined in section 3.3.

f s.

De-entrainment.

The results are presented as two separate sets of The first set of calculations were performed with a debris de-calculations.

entrainment time (t ) for all three cells of 0.3 seconds. The debris de-d entrainment tbne is defined as the inverse of the fractional trapping The

rate, f,

which governs the rate of debris removal from the atmosphere.

g second set of calculations were done with a e of 10.0 seconds. These two d

believed to provide practical upper and lower limits with values of t are d

effects of debris removal from the atmosphere via interaction regard to the (a process which is not modeled mechanistically in the with cell structures IDHN).

The debris content was taken to be that of the Composition.

l b.

Corium the time of RPV failure for the Sequoyah plant as provided in TMLB' melt at BMI-2104 vol 4, Table 6.8.

In each case the corium was assumed to enter the The mass source rates lower cavity at a steady rate over a 5 second period.

(in kg/sec) for the corium constituents in the 100% case were therefore 20198 (UO ), 2360 (Zr), 3052 (Zr0 ), and 9968 (Fe). All cases other than 1004 j

2 2

ejection consisted of uniformly scaled down corium masses with all other parameters held constant.

i Hydrogen. Based on the debris composition described above, c.

In-Vessel the in-vessel zirconium-steam reaction was calculated to have liberated 496 kg

  • l 2

of hydrogen.

One half of this hydrogen was assumed to recombine with oxygen in the containment prior to RPV failure (This assumption atmosphericjustified by hypothesizing igniters or recombiners with independent could be i

power supplies). The remaining hydrogen was assumed to enter the containment This treatment of the in-vessel hydrogen may be non-with the blowdown steam.

conservative; however, it separates the DCH problem from the more conventional hydrogen burn problem which by itself is known to be a problem for ice Hydrogen burns fueled by hydrogen produced after vessel condenser plants.

Zr-steam and Fe-steam chemical reactions were considered and i

failure by the are shown below to be the major contributing factor to the DCH induced

{

pressure rise in the cases that predict containment failure.

i d.

Blowdown Characteristics.

The vessel steam / hydrogen blowdown was 30 seconds following RPV. failure. The blowdown was assumed to last forassumption of constant mass flow rate over.this 30 second modeled under the made to account for a ramp at the beginning of the period.

No attempt was blowdown nor a tail at the end of the blowdown. The total steam mass of 3

39,652 kg was determined from the total primary system volume (373 m ) and the volume of saturated steam at the failure conditions (T-578 K. P-15.6 specificTherefore, the steam blowdown mass rate was 1322 kg per second.

l MPa).

i i

i

?

,.,.7.-

,____.y.

---.--.---,..-.__.m,-

,.,,,____._.,_,,.,_,__my.

y-%.,

, -, -,,,,,,, ~ -,,, -., _ - ~,, - -,,,,,, - _ _ -, - -,, _. -,, _ _,,, _,,.

. e.

User Selectable IDHM Input Parameters. As discussed in Section 3.3, selectable input parameters are provided to account for various i

several user direct containment heating modeling uncertainties. The parameters of primary interest are those listed in Table 1.

The values chosen for the present i

calculations are now given. All calculations were performed assuming 0.5 mm drops (D ),

c nsistent with the Surtsey DCH-1 experimental results of debris d

mass median diameters.

The multiplier on oxygen diffusivity, o,g, and the were both assumed to be unity. The multiplier on steam diffusivity, o,g, chemical reaction cutoff temperature, T,, of the bulk debris field was assumed to be 1000 K.

Radiative exchange between drops and the' surroundings was the gray-body model with a chosen effective drop emissivity of treated under 0.8.

An opaque gas model was assumed in which all of the radiated energy was deposited in the gas and none in cell structures (o - 0.8, a,- 0.0).

The g

debris velocity relative to the gas, v, (used in the evaluation of Re) was g

assumed to be 6 m/sec in each of the three cells. This velocity roughly corresponds to the terminal fall velocity of a 0.5 mm debris drop.

In all calculations the hydrogen recombination option was used.

In this option hydrogen produced in a cell is assumed to immediately combine with bulk oxygen in that cell with the reaction energy going to the gas.

Finally, the fraction of ice left at vessel failure, b, was assumed to be 0.8.

TABLE 1. Ilser Specified Parameters for IDHM Fraction of nominal core mass of debris ejected rem Multiplier on black body radiation from debris to gas a

Multiplier on radiation from debris to wall a,

Multiplier on oxygen diffusivity a,x Multiplier on steam diffusivity a,e T,

Cutoff temperature for chemical reactions (K)

Cas-debris relative velocity in cell i (m/s) vg Trapping parameter; fraction removed from cell i per second (s'1) f g D

Debris droplet diameter (m) d Fraction of initial ice left in ice condenser at vessel failure b

l l

'h.

14 I

4.2 Discussion of Results CONTAIN predictions of peak pressure in Sequoyah as a function of corium ejection percent, r,,, are shown in Figure 3 for the two de-entrainment times discussed in Section 4.la.

For purposes of discussion, these curves will be divided into 3 separate regimes. The first regime is between 0 and 15 core percent for the t -10 case and 0 and 20 percent for the t -0.3 case. This d

d hydrogen burn in the upper regime is characterized by the sbsence of a containment (cell 3).

The resulting predicted peak pressures are high enough to threaten but not exceed the failure pressure. Note that at r,g-204, occurrence of a hydrogen burn in the upper compartment depends on the de-entrainment time.

While the location of this threshold depends on td' I' I' seen that t has little impact on peak pressures before the burn threshold is d

crossed.

In the second region the peak pressure is primarily driven by the 1

hydrogen burn process in the upper dome. Near the end of the second region, an interesting yet physically realistic behavior is predicted when tg-0.3.

i That is, the peak pressure for a 404 corium ejection was predicted to be higher than for a 50% corium ejection. Study of the detailed code output indicates that this behavior can be attributed to the fact that the hydrogen burn in the 50% case began at an earlier time than it did in the 40% case.

The timing of the burn has this effect on the peak pressure because at early times (immediately after debris ejection) the lower-cavity temperatures are l

considerably higher than at later times.

Due to subsequent cooling, the more efficiently as a " pressure-sink" for 4

lower-cavity can therefore serve early burns than it can for late burns. When t -10 this behavior is somewhat d

t overshadowed by the severity of the early burn. Note that this burn timing l

phenomenon does not have the same effect on the peak containment temperatures l

which are monotonically increasing with core percent as shown in Table 2.

]

Beyond r,g-40% is the third regime of the curve. The peak pressures in this l

regime for case 2 (t -10) diverge significantly from those of case 1 (tg-0.3).

d is attributed to differing availabilities of hydrogen in the divergence This dome at late times (near the end of and following the vessel blowdown).

upper i

During debris ejection, the gas reaches the temperature of the debris for core i

ej ection fractions above 40 percent in both cases. Consequently, further increase in the ejection debris mass cannot result in further heating of the

]

atmosphere during the debris ejection phase.

Therefore, predicted peak

)

pressures for cases above 40t core ejection will primarily depend upon the i

amount of debris in the atmosphere after the debris ejection. Following the gas temperature in the lower cavity drops in case 1 due to the ejection, the rapid fall out of the debris.

On the other hand, in case 2, considerable amounts of debris remain in the atmosphere following the ejection as a consequence of the slow fractional trapping rate.

Since this debris is a reservoir of thermal energy incoming steam continues to be heated, which thereby increases the driving force that pushes hydrogen through the ice 1

l i

i m...-..-__

c

..._.__._,_-..___,_.._,_,__._.~.._,m,.

i' i 5

condenser and into the upper done.

In case 1 the peak pressure reaches a j

plateau beyond 404 core ejection as a result of a saturation of this driving r

force.

That is, the amount of debris in the atmosphere following the debris ejection. phase is insufficient to further heat the vapor in the lower cavity.

\\

'l i

Table 2 CONTAIN Predictions of Peak Pressure and Temperature in Sequoyah Containment for a TM13' DCH Scenario, I

t =0.3 e -10.0 d

d Percent Peak Peak Temperature Peak Peak Temperature j

Core Pressure T(1) T(2) T(3)

Pressure T(1) T(2) T(3)

(t)

(bars)

(K)

(K)

(K)

(bars)

(K)

(K)

(K) 0 2.74 430 438 394 2.74 430 438 394 l

10 3.23 1254 915 477 3.32 1456 1035 504 3.58 1647 1154 548 15 20 3.61 1666 1107 528 5.81 1816 1235 1182 i

25 5.60 1803 1172 1128 30 6.21 1919 1226 1177

.7.26 2070 1342 1317 35 6.86 2010 1257 1247 40 7.18 2088 1298 1280 7.36 2246 1417 1338 l

50 6.90 2217 1351 1320 7.78 2283 1489 1415 i

75 6.72 2387 1478 1339 9.03 252:

1560 1663 100 6.95 2436 1557 1408 10.55 2865 2066 2076 4,3 Conclusions There is no question that there are many complexities to the DCH i

j problem, and 'that in many respects the simplifications inherent in the IDHM modeling (and in other parts of the CONTAIN code) are inadequate 4

)

representations of the phenomena.

Ultimately, we must depend on an improved experimental data base for improvements in some areas of our understanding.

However, in the meantime, the system-level analysis l

which the CONTAIN code affords makes it possible to make the connection between the existing knowledge base and the operating reactor situation.

l The uncertainties in our knowledge can, in many cases, be represented by t

ranges of the user-specified input parameters.

The understanding thereby gained can help guide the experimental program and future model development activities, as well as provide decision makers with interim assessments of the implications of DCH on reactor safety.

l l

Three important conclusions emerge from the sensitivity studies which l

have been described here.

First, the most important metal oxidation i

t l

l l

l

. 1 reaction is the steam metal reaction, a consequence of local oxygen starvation in the vicinity of the debris when it is first ejected, and of the rapid chemical reaction rates. A somewhat unexpected aspect of this issue is the importance of the iron / steam reaction, which in itself not particulary exothermic, and is usually limited under more normal is accident conditions by oxide crust formation, but which proceeds in these calculations because of high ambient gas temperatures.

second conclusion concerns the importance of hydrogen combustion in The DCH scenarios. The quantities of hydrogen generated by these processes are extremely large, and the generation rates are unprecedented in safety analysis.

In ice-condenser plant, the pressure rise due rasctor debris-gas heat transfer is often not as large as the pressure rises to from the subsequent hydrogen burns.

Uncertainty about the mode of hydrogen combustion, and the various criteria for combustion, therefore, has become a major concern for DCH analysis.

Finally, the third important conclusion is that, for Sequoyah, the details of intermediate debris transport--de-entrainment, re-entrain-
ment, sticking, bouncing, and so on--which have tended to dominate DCH discussions in the past, may be less important than we have previously rather vide range of our debris de-entrainment time believed.

Over a parameter, the sensitivity of peak pressure was not very large. This of course, due to the importance of the hydrogen generation result is, and combustion processes discussed in the previous two paragraphs.

While one cannot conclude that intermediate debris transport is unimpor-cant for this or any other plant, the reduced sensitivity to this aspect of the problem can have important implications for future research activities and current assessments for regulatory applications.

I 4

I f

1 i

l l.

.-._,_._._,,_.,._m.__-,_._,,

m._,,

_. _. _..., _,, _ -....,. ~ _ _. _,.. -,,,

17-

/////H l

ENGINEERED.. ?*:.:'.

/ g *.

SAFETY

/ j,*.,

FEATURES i

[ CONDENSATION EVAPORATION J h TWO PHASE THERMODYNAMICS AEROSOL EVOLUTION AND FLOW i

MYDROGEN SURN RADIOISOTOPE TRANSPORT AND DECAY TERCRL a

FLOW i

STRUCTURE HEAT TRANSFER

/ a - _-

l 1

i i

l h

i l

D

  1. .' N.:+.

c._,_ _..-

i REACTOR CAYlTY PHENOMENA i

\\

FIGURE 1.

SCHEMATIC DIAGRAM OF

\\

PHENOMENA ANALYZED IN THE CONTAIN CODEA. CONT i

i INDICATING THE I

,--%y-pe

,,-----w9-,,---v-,+

-__%-._w%,_,---,,,-,,__ym,.c m,,7m-

,-,y,.y.-.

.,,-,w-,w--..,w.w=vy-e-ww,,ve

l 3

l

+

+

2 2

~

1 I

1 Compartment Descriptors 1.

Lower compartment 2.

Ice compartment 3.

Upper compartment (Dome)

Figure 2.

SCHEMATIC DIACRAM OF THE CONTAIN 3 0 ELL NODALIZATION OF THE SEQUOYAH ICE CONDENSER CONTAINMENT.

I j

1, 11.0 s

i l

10.0 -

1 i

9.0-8.0-1 v

7.0-l l

6.0-en in o

5.0-1 L.

Q 4.0 -

.M a ta = 10.0 g

l g

3.0 ;

4 = 0.30 2.0-1 i

l 1.0-i 0.0 i

i 0.0 20.0 40.0 60.0 80.0 100.0 Percent Core Melt-Ejection 1

l Figure 3.

CONTAIN Prediction of Peak Pressure in Sequoyah Contaisument for a TMt.B' DCH Scenario. Results for 2 Values of Debris 4

De-Entrainment Time, e I'**)' *** 8 d

i

\\

t).f,2l

~)

\\

Sandia National Laboratories j

Albuquerque, New Mexico 87185 E

September 26, 1986 I

Dr. Thomas J. Walker NRC/RES i

7915 Eastern Avenue Silver Spring, MD 20910

Dear Dr. Walker,

't you and I have discussed on the phone, we have just completed As a

number of Direct Containment Heating (DCH) calculations with the CONTAIN code as part of our support for SASA, and this with some of the highlights.

Details letter will provide you you know, in a forthcoming NUREG report.

How-l will

appear, asof the interest which Tim Lee and Farouk Eltawila
ever, because have shown in this work in regard to their NUREG-ll50 issue l
paper, we are providing this summary immediately, in the hopes i

that it will be of use right away.

t new work is an extension of the sensitivity study which Dave l

The Williams reported in his American Chemical Society conference

paper, of which you have a copy.

What we have done is select a s

l number of his parameter variations for Surry and performed the on the sequoyah plant.

In addition, a few new i

same variations variations were performed for both Surry and Sequoyah.

parameter this way we can directly compare the plant specificity of the I

In modeling sensitivities.

The resulting matrix of calculations interesting insights on the DCH problem and provides some very d

adds to our growing understanding of the importance of different j

phenomena and plant characteristics.

representative result is shown in the attached Figure 1, which Ais the pressure-time history around the time of vessel breach for For this study, all the assumptions and parameter the Base Case.

choices described in Williams paper were also applied, so you can complete description of the conditions of the calculation get a

by referring to it.

Only plant-specific aspects changed; e.g.,

of corium ejected was scaled to the core size (but was 4

the mass still chosen to be 75%

of the core mass in the hase case).

Plant-specific parameter choices are described in my recent letter to Mel Silberberg (dated September 2, 1986).

Two options for hydrogen combustion modeling were exercised for These are burn model "a", which is the r

all parameter variations. ignition, completeness, and propagation default model for all criteria in CONTAIN (as taken from HECTR).

The alternative model "b"

is described in the paper as " prescribed burn".

In this starting two seconds afthr vessel i

hydrogen is burned,there is oxygen, regardless'of concentrations model all

failure, whenever of steam, hydrogen, and oxygen in the cell.

As explained in the l

l

- 57enfomerg

=

'PP 1

j i

d Dr. Walker September 26, 1986

paper, this model may be more reasonable than the default model because of the presence of hot gas and hot debris.

In any case, we feel the two choices "a" and "b" are bounding on this impor-tant uncertainty.

The parameter variations are summarized in Table I.

A total of 8 variations are reported there for each plant and each burn op-tion.

Thus, with the base case, the total number of calculations is 36.

We present only the peak pressure (P,,x) and the ratio o

is the nominal failure pressure for each plant.

P,,g/P, where Pf f

We arbitrarily selected the failure pressures to be 135 psia for Surry and 60 psia for Sequoyah, consistent with SARRP studies (though there is a

lot of uncertainty about these numbers).

Details about other parameters (e.g. temperatures in different compartments) will be provided in the NUREG report, but this summary provides an at-a-glance picture of what the key uncer-tainties are.

The extent of each parameter variation was l

selected somewhat arbitrarily as being within the range of 1

uncertainty.

These are not bounding ranges, in general.

If one had uncertainty ranges on the parameters, it would be straight-forward to estimate resulting ranges in the peak pressure by linear extrapolation from the results in Table I.

~In general, the results in the table are self-explanatory, but a few key issues should be noted.

The debris de-entrainment times t

used were based on the scaling relation that Dave Williams d

used, but he described it in terms of a fractional trapping rate.

This is just the inverse of the de-entrainment time used in Table I.

Our approach here is in contrast with the Sepoyah study reported in the above-mentioned letter to Mel, which used the

. same t

in each cell.

Another important difference was that in d

i the earlier Sequoyah study, we did not include drop side limita-i tions on mass transfer.

However, this was shown by Dave not to i

i be of crucial importance in most cases.

Finally, the earlier Sequoyah study had a different debris composition, being based on BMI-2104

results, rather than Containment Loads Working Group j

Standard Problem 2, which is the basis for the results reported in Table I.

Please let me know if you have any questions on this material.

Sincerely, i

K~kv~~

Kenneth D. Bergeron, Supervisor Containment Modeling Division 6449 KDB:6449:mm l

l l

j

J Dr. Walker September 26, 1986.

Copy to:

NRC/RES T. Lee NRC/RES P. Wood NRC/RES J. Mitchell NRC/RES R. Meyer NRC/NRR F. Eltavila 6440 D. A. Dahlgren 6449 K. E. Washington 6449 D. C. Williams 6449 File 3.7 i

S i

l

Sequoyah Pressure History Predictions for TMLB' DCH Scenario with CONTAIN - IDHM (base case) 120.0 Default H-burn

Continuous H-burn 100.0 -

~ ~ ~ ~ ~.

3 m

,m p.,

80.0 -

f l

0

/

U En l

60.0 -

./

u O-.

40.0 -

20.0 i

i i

9400.0 9410.0 9420.0 9430.0 9440.0 Time (sec)

f P

0 8

2 0

2 2

8 5

2 6

3 1

1 8

0

/g 7

4 5

"b 1

1 1

1 2

1 1

1 1

P nr t

u n

B x

6 7

9 4

7 7

5 1

1 a

a 9

0 7

8 2

6 9

1 6

l m

1 1

1 P

P h

a y

o g

u P

3 8

5 4

5 2

3 7

7 8

8 9

8 0

q

/

8 7

5 5

x

"a a

1 1

1 1

2 0

1 1

0 S

a P

nruB 0

7 3

3 3

9 0

8 2

1 0

9 9

2 4

1 1

5 1

1 1

1 1

P f

P 0

6 0

7 3

2 5

6 2

3 0

2 0

0 9

9 8

/

0 x

b a

1 1

0 0

1 0

1 1

1 a

P nru B

x 5

2 3

0 9

1 2

9 7

t a

3 4

2 3

7 1

4 6

3 n

a 1

1 1

1 1

1 1

1 1

a P

lP I

y r

f r

P 8

5 9

4 3

4 6

5 4

E 6

6 L

u

/

7 8

7 0

7 9

7 B

x S

"a a

0 0

0 0

1 0

0 0

0 AT a

P nr uB x

5 5

3 0

8 6

3 7

0 a

0 1

9 0

3 8

0 2

0 a

1 1

1 1

1 1

1 P

no i

m

)

t o

f m

c r

r P

o n

a f

e

(

r w

r t

)

f o.

f n

r a

s e

dc 5

o e

w e

s we t2 i

t r

a n

os c

t a

d u

b a

l e0 a

w e

s aa im b0 j

d s

s ii

(

n g

dm 1

eo i

d r

e ss o

nd m

t x0 ge e

r pp i

g it p0 ao e

o3 ks p

P t

n p

o.

et r5 r

s 05 a

e i

p1 r1 t

o7 r0 4e 5i e63 i

s p

a.

d s0 c.

Z Ep Ed r

1 r

a p

r0 o

3 0

o 0s 0-u a

c a

t et e

e et

.i

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g gm gm g

2d 1c i h t=

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t s

sd a

ar ar a.

do dg F y:

a o

at h0 hf hf h0 dc dk oy B

N F

C C

C C

A A

d ur e qr m eu u Ss e

s 1

2 3

4 5

6 7

8 9

ss a

A C

J l

1 I

Surry DHEAT2 Calculations Without Blowdown Steam and no Stearn Spike 2400.0 16.0 l

n

,... ~...

  • Pressure 14.0 l

= Temperature

  • .. ~.. m-2000.0 q g

v L

12.0 d

a)

L CQ g

v 10.0 1600.0 a

e d

L L

U q) a 8.0 C

O L

L 1200.0 $

CL 6.0

~

d

~

g

.6 CE

~

E 4.0 800.0 2.0 0.0 /

400.0 i

i i

i 0.0 20.0 40.0 60.0 80.0 100.0 Percent Core Melt-Ejection 1

Surry DHEAT2 Calculations With Blowdown Steam and no Steam Spike

, 2400.0 16.0

  • Pressure 14.0

= Temperature 2000.0 2

'W L

12.0 n

v

.... s *... -

q) d CO g

v q) 10.0 1600.0 a

M D

' '. = ~

c)a 8.0 d

, ~.. =

1200.0 $

C q)u cL 6.0

-d dC C

C C

4.0,

800.0 2.0

,s' 0.0 :f' 400.0 i

i i

0.0 20.0 40.0 60.0 80.0 100.0 Percent Core Melt-Ejection

-

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