Core Reload Analysis Techniques in the Advanced Test Reactor

Abstract

Since becoming a national user facility in 2007, the type of irradiation campaigns the Advanced Test Reactor (ATR) supports has become much more diverse and complex. In prior years, test complexity was limited by the computational ability to analyze the tests’ influence on the fuel. Large volume tests are irradiated in flux traps which are designed to receive excess neutrons from the surrounding fuel elements. Typically, fuel elements drive the test conditions, not vice versa. The computational tool, PDQ, was used for core physics analysis for decades. The PDQ code was adequate so long as the diffusion approximation between test and fuel element remained valid. This paradigm changed with the introduction of the Ki-Jang Research Reactor—Fuel Assembly Irradiation (KJRR-FAI) in 2015. The KJRR-FAI was a prototypic fuel element for the KJRR research reactor project in the Republic of Korea. The KJRR-FAI irradiation presented multiple modeling and simulation challenges for which PDQ was ill suited. To demonstrate that the KJRR-FAI could be irradiated and meet safety requirements, the modern neutron transport codes, HELIOS and MCNP, were extensively verified and validated to replace PDQ. The hybrid 3D/2D methodology devised with these codes made analysis of the ATR with KJRR-FAI possible. The KJRR-FAI was irradiated in 2015-2016.

1. Introduction

In 2015, the advanced test reactor (ATR) began irradiations of the Ki-Jang Research Reactor—Fuel Assembly Irradiation (KJRR-FAI) test. Concurrent with the KJRR-FAI experiment program, the ATR was in the process of software quality assurance (SQA) for a more robust transport-based code, the Studsvik-Scandpower HELIOS code. The use of HELIOS enabled high quality (i.e., NQA-1) core reload and safety analysis of the ATR cycles for which irradiated the KJRR-FAI test.

The neutronic communication between the KJRR-FAI and the ATR fuel elements required 3D analysis. However, HELIOS is a 2D code. At the time, high fidelity 3D transport simulation of the ATR was too computationally expensive to be used for fuel reload and safety analysis. The solution of intra-plate power peaking in the ATR fuel elements was particularly challenging as this requires a significant number of particle histories in a Monte Carlo method and excessive mesh density in a deterministic transport method. As a workaround, the well-known Monte Carlo N^th Particle (MCNP) code was used to provide the axial peak-to-average power peaking factors which allowed for computationally efficient calculation of new core reload patterns that would satisfy the irradiation needs of the KJRR-FAI while ensuring safe operation of the ATR.

2. Background

2.1 The advanced test reactor

The ATR is a water-moderated, beryllium-reflected, pressurized water reactor with a serpentine arrangement of plate fuel taking on a four-leaf-clover likeness [1]. Each of the cloverleaves plus the center region are each referred to as lobes. The design power rating is 250 MW. However, it is currently operated at about 110 MW, and occasionally at powers approaching 250 MW to support higher power experiments. The metallic fuel plates consist of a highly enriched uranium (HEU 93wt% ²³⁵U/U) uranium-aluminide (U-Alx) dispersed in aluminum. This dispersion is sandwich clad in aluminum alloy, Al-6061. The fuel serpentine contains 40 fuel elements, each containing 19 curved plates. The fuel plates are swaged into side-plates forming the fuel element. The angular separation between the two side-plates is 45 degrees. The inner and outer four fuel plates contain natural boron carbide (B4C) to suppress radial (i.e., plate-to-plate) power peaking. The inner 11 fuel plates do not contain B4C. Also, the UAlx concentration is varied by plate to minimize radial power peaking.

Initial criticality as well as the power share among the lobes is maintained using hafnium plates on rotating control drums, called Outer Shim Control Cylinders (OSCCs). The burnup reactivity decrement is made up partly with OSCCs but also with annular hafnium neck-shims (i.e., 24 hafnium control rods) which are removed from the four aluminum neck arms in the center region. Numerous penetrations in the reflector and neck arms allow for non-instrumented “drop-in” as well as instrumented capsules, in addition to the nine flux traps. A picture of a typical reactor configuration is provided in Figure 1.

Figure 1.

The ATR basic configuration.

2.2 Ki-Jang Research Reactor—Fuel Assembly Irradiation

The Ki-Jang Research Reactor is a new isotope production reactor being pursued by the Republic of Korea [2]. This fuel is the first-of-a-kind of U-Mo fuel for commercial utilization; thus, it requires a license to be granted and a qualification of the fuel at scale. Thus, the KJRR-FAI is a full-size prototype designed to test mechanical integrity, geometric stability, acceptable dimensional changes, and assurance that the performances of the fuel meat and fuel element are stable and predictable during irradiation. This testing was conducted in the northeast lobe of the ATR from October 2015 to February 2017 in cycles 158A, 158B, 160A, and 160B [3]. These irradiations successfully demonstrated the KJRR fuel element’s reliability in prototypic conditions to a burnup of 83.1% U-235.

The KJRR fuel element is based on the very successful plate-in-box fuel concept used in many research reactors across the world. Coincidently, this type of fuel has its origins in ATR’s predecessor, the Materials Testing Reactor (MTR) [4]. The KJRR fuel is of the genre of high-density High Assay Low Enriched Uranium (HALEU) research reactor fuels, enriched to 19.75% ²³⁵U/U [3]. The fuel meat is a dispersion fuel consisting of uranium-molybdenum alloy (U-7Mo) (i.e., seven w/o Mo) dispersed in an Al-5Si matrix (i.e., five w/o Si) (Figure 2). This dispersion fuel is clad in aluminum alloy Al-6061. There are 21 straight (not curved) fuel plates. The inner 19 fuel plates have a uranium density of 8.0 g-U/cm³. The outer two fuel plates have a uranium density of 6.5 g-U/cm³. The enrichment zoning is to reduce the radial power peaking in the fuel element (Figure 3).

Figure 2.

KJRR-FAI fuel plate showing U-7Mo dispersion in Al-Si matrix.

The overall dimensions of the KJRR fuel element are 76.2 × 76.2 × 1010 mm. However, the active height of the KJRR-FAI fuel meat is only 60 cm (23.6 inch), which is less than half that of the active height of an ATR fuel element which is 48 in [5]. The KJRR-FAI was irradiated in the ATR northeast flux trap (Figure 1).

Figure 3.

Profile view of the KJRR-FAI prototype fuel element.

2.3 Computer codes

2.3.1 HELIOS

HELIOS version 2.1.2 is a general x−y coordinate deterministic transport code. Arbitrary geometry is created by user defined nodes, connected to form line segments, then closed to form the spatial mesh. The code supports property overlays, such as composition, temperature, and density. These overlays are mapped to each mesh in the arbitrary 2D geometry. Geometry-corrected resonance integrals are calculated on-the-fly for every spatial mesh of the arbitrarily heterogeneous geometry description using the subgroup resonance treatment. HELIOS uses 49 groups derived from ENDF/B-VII. Very large and complex geometries are supported by subdividing the geometry into smaller subsystems. Each subsystem is solved explicitly via the collision probability (CP) transport solution, or method of characteristics (MOC), and then coupled with adjacent subsystems by sharing interface currents [6]. The angular dependence of the interface currents is discretized by a subdivision of outward/inward angles (i.e., a directional half-sphere). In the HELIOS model, all possible azimuthal directions crossing the interface are discretized into four equal sectors of equal weight. A HELIOS model containing the KJRR-FAI is provided in Figure 4.

Figure 4.

HELIOS model of ATR (cycle 158A) with the KJRR-FAI loaded in the northeast flux trap.

From 2010−2015, the HELIOS code underwent extensive Verification and Validation (V&V) to elevate the software quality of HELIOS to Nuclear Quality—1 (NQA-1) [7, 8]. The HELIOS code replaced the neutron diffusion code, PDQ, for performing core reload analysis and associated safety calculations.

2.3.2 MCNP

MCNP uses the Monte Carlo method for solving particle (e.g., neutron and photon) transport in a continuous energy, angle, and three-dimensional space representation of the reactor core [9]. MCNP also makes use of ENDF/B-VII cross-section libraries. The Monte Carlo solution method represents particle interaction as probabilistic collisions between traveling particles and atomic nuclei. Therefore, the MCNP solution can be considered to be a near exact representation of reality to within the accuracy of the input nuclear interaction cross-section data. However, this level of solution fidelity comes at greater computational expense compared to a 2D deterministic code such as HELIOS.

MCNP 3D models, shown in Figure 5, of the ATR core with the KJRR-FAI loaded were developed for comparison with HELIOS. The MCNP model of an ATR fuel element consists of homogenized regions. The 19 fuel plates and associated coolant channels are homogenized into three radial regions. Each of these radial regions are partitioned into seven axial layers. Each axial layer is depleted separately during the depletion calculation. Though increases in computational speed is currently enabling 3D Monte Carlo solutions to be much cheaper, production calculations are still very time-consuming. Thus, the homogenization is done to reduce the required computational burden of resolving the geometry of every plate while still providing the desired level of accuracy for heating rates in the experiments. This is common practice when using MCNP to solve for heating rates in ATR experiments.

Figure 5.

MCNP model of ATR (cycle 158A) with the KJRR-FAI loaded in the northeast flux trap.

Fuel depletion is solved using the ORIGEN2 code using the tallied neutron fluxes from each of the MCNP 21 regions. The ATR operating cycle is broken into discrete time-steps. MCNP solves for the one-group neutron flux and coalesced absorption and fission cross-sections in each of the 21 regions in each fuel element. These fluxes are passed to ORIGEN2. ORIGEN2 solves the Bateman equations to deplete the fuel. The depleted compositions are then passed back to MCNP.

MCNP is used to compute the axial peak-to-average peaking factor which is multiplied against HELIOS intra-plant powers during post-processing. The combination of the HELIOS 2D solution for every sub-plate region with the axial peak-to-average factor for every fuel element allows the final predictive core performance calculations to provide adequate 3D information. Typically, many design evolutions of different fuel loading patterns, and OSCC and neck-shim withdrawal patterns are needed to demonstrate the cycle’s operating requirements can be met while respecting all safety limits. HELIOS is used for these design evolutions with axial peak-to-average factors provided by MCNP in the final design calculation.

The MCNP code was also validated against extensive fission wire activation measurements made in the advanced test reactor critical (ATRC) facility [5, 10]. The ATRC facility is zero power replica of the ATR used for low-power activation analysis to verify power distributions and to measure the reactivity worth of experiments prior to being inserted into the ATR.

3. Irradiating a square fuel element in a round flux trap

3.1 Managing core reactivity for high worth tests

Typically, ATR flux traps irradiate large volume experiments having high flux requirements. By definition, a flux trap is designed to ‘trap’ the excess flux from the surrounding fuel elements. This typically implies that the neutrons from the experiment do not greatly influence power production (or power distribution) in the ATR fuel elements. However, given the sheer quantity of fissile U-235 introduced by the KJRR-FAI, it became readily apparent that the KJRR-FAI could drive the northeast lobe power, rather than the northeast lobe driving the KJRR-FAI power. The thermal limits of the KJRR-FAI test could be exceeded unless the excess reactivity introduced by the KJRR-FAI could be managed. The KJRR-FAI test needed to be maintained at a power <2.3 MW to ensure its thermal margins could be met. Several burnable poison options were investigated, but ultimately abandoned as this would interfere with the desired neutron flux environment.

It was decided that highly burned ATR fuel elements could be loaded into the northeast lobe to essentially “sponge” the reactivity introduced by the KJRR-FAI. However, even with the use of these highly burned fuel elements, the northeast quadrant of OSCCs would need to be rotated inwards to keep the northeast lobe at the desired 19 MW.¹ Typically, the burnup distribution of the fuel elements is selected such that the OSCCs can be rotated relatively (though not exactly) evenly. Said differently, it is desirable to manage power distribution around the serpentine using the fissile content of the fuel elements, not by using the OSCCS for power shaping. This does not always happen in practice, but this is a general goal of the fuel reload analysis. Figure 6 shows the localized power distribution for 10 regions per plate for every plate in the core for cycle 158A. The OSCC are in the startup position at 29 degrees.

Figure 6.

The dimensionless point-to-average power density ratio for every fuel region in the HELIOS model for ‘balanced’ OSSCs at startup. Note, that the HELIOS 2D power density is corrected for axial power peaking using data from MCNP.

Rotating the northeast control bank to nearly “all-in” acceptably suppressed the northeast lobe’s power but unacceptably robbed the whole core of excess reactivity. This required adding fresh assemblies somewhere else in the core such that the requested cycle-length could be met.

3.2 Updating power peaking factors

Prior to HELIOS, the 2D Cartesian mesh version of PDQ was routinely used to predict core reactivity, lobe-power distribution, and localized plate power peaking. However, the axial component of power peaking had been incorporated via an empirical correlation assuming the ATR thermal flux was a “chopped” cosine shape. The fresh fuel axial peak-to-average ratio was 1.43. The bounding thermal-hydraulic analysis for the ATR assumes this axial power shape, originally calculated by PDQ, as universal for every cycle. Changing the axial power shape requires an update to the ATR thermal-hydraulic safety analysis, or at minimum a calculation to assure that the existing safety limits are not challenged by the new axial shape.

Prior to the KJRR-FAI, the chopped-cosine rule was rigorously enforced by ensuring that new experiments would not cause a major deviation from the established axial power shape.² An acceptance band is used to ensure that new tests would not violate the chopped cosine rule. Experiments that did not meet this criterion would require redesign if the chopped cosine rule could not be met. Typically, the MCNP code is used to design ATR experiments and used to predict the axial peak-to-average factor. If the MCNP analysis finds the axial peak-to-average power factor will likely be non-compliant to the chopped cosine rule, a measurement of the axial shape in the ATRC facility is considered to verify the calculated axial shape.

Note that the axial power peaking factor is significantly greater for the MCNP calculation with the KJRR-FAI in the northeast flux trap than it is for the chopped cosine rule. This is primarily contributed to the influence of the KJRR-FAI fuel loading being concentrated near the mid-plane, i.e., within ±30 cm about core-midplane. The axial peak-to-average power factor was calculated using MCNP by tallying the power in the fuel every two inches when the ATR fuel elements are all assumed to be fresh. This calculation was repeated with a generic test configuration typically used as an experiment backup in the northeast flux trap, called the Large Irradiation Housing Assembly (LIHA). The LIHA consists of an arrangement of cobalt and aluminum rods and is considered a standard backup for the northeast flux trap when not in use. The axial peak-to-average power factor in fresh ATR fuel elements was found to be ∼1.5 when neighboring the KJRR-FAI and ∼1.4 when neighboring the LIHA. The MCNP tallied power profile for fresh ATR fuel elements adjacent to the KJRR-FAI versus the LIHA is shown in Figure 7.

Figure 7.

Comparison of the axial power shape in ATR fresh fuel (Fuel Element 5, Coolant Channel 2) computed using MCNP due to the KJRR-FAI versus the standard LIHA northeast flux trap configuration.

Modifying the test design was not an option for the KJRR-FAI; thus, the empirical chopped cosine shape would need to be rederived. Furthermore, the evolution of this power shape considering depletion effects would need to be considered. Even without the significant axial distortion due to the KJRR-FAI, fuel naturally depletes preferentially at mid-plane due to geometric shape or buckling of the neutron flux. This axial variation in burnup, and hence fuel nuclide distribution, needs to be represented in the HELIOS model (just as previously with the PDQ code). This axial burnup variation also impacts the axial power shape as represented in Figure 8.

Figure 8.

Approximate axial power-to-average factors created as 2D/1D factors using the r−z PDQ RCC lobe model.

Within the PDQ-based methodology, a three-dimensional extension of the “x−y” PDQ analysis was needed to compute the effect of the axial burnup shape on excess reactivity, axial power peaking, and axial burnup peaking. PDQ could be used to solve a 1D r-dimensional as well as a 2D r−z coordinate system. These two features were used together to calculate 1D and/or 2D reactivity biases and axial multipliers due to fuel burnup. To derive a generic peak-to-axial power factor, a single lobe is approximated by a right circular cylinder (RCC) comprised of a generic in-pile tube (IPT) encircled by eight fresh ATR fuel elements. These ATR fuel elements are represented by seven fueled concentric annuli with no side-plates. The modelled seven annuli represented fuel plates 1, 2, 3-4, 5-15, 16-17, 18, and 19, respectively. Each fueled annulus is represented by a homogenized cell containing water, aluminum, and UAlx fuel matrix. The RCC lobe is also recast as a 1D r-dimensional model. Both the 1D r-dimensional and 2D r−z model are depleted at 60 MW for 50 days, or 3000 MW−days (MWD) of “lobe-exposure”. The 2D/1D reactivity bias and the axial power peaking factor are then set to a polynomial fit as a function of lobe-energy.

The PDQ axial peak-to-average factor is provided in Eq. (1).

$$A\left(t\right)=\frac{\raisebox{1ex}{$P_{\mathrm{m}}\left(t\right)$}\!\left/ \!\raisebox{-1ex}{$V_{\mathrm{m}}$}\right.}{\raisebox{1ex}{$\sum P_{\mathrm{i}}\left(t\right)$}\!\left/ \!\raisebox{-1ex}{$\sum V_{\mathrm{i}}$}\right.}=\frac{{\mathcal{P}}_m\left(t\right)}{{\mathcal{P}}_a\left(t\right)}$$E1

P_m represents power at midplane. This is the average power for regions of fuel on core-midplane. V_m is the volume of these regions. P_i and V_i represents the power and volume of all fuel mesh in the PDQ r−z model. Note that the cursive, 𝒫, represents power density. Time, t, represents fuel burnup in units of MWD, referred to as lobe-exposure. The fuel element axial burnup peaking factor is then derived from the indefinite integral of the axial power peaking factor.

$$B\left(t\right)=\frac{{\int }_0^t{\mathcal{P}}_m\left(t\right)\mathrm{d}t}{{\int }_0^t{\mathcal{P}}_a\left(t\right)\mathrm{d}t}=\frac{{\int }_0^{t}A\left(t\right){\mathcal{P}}_a\left(t\right)\mathrm{d}t}{{\int }_0^t{\mathcal{P}}_a\left(t\right)\mathrm{d}t}$$E2

The average power density of the simple r-z model is held constant; thus, this factor may be eliminated.

$$B\left(t\right)=\frac{{\int }_0^{t}A\left(t\right)\mathrm{d}t}{{\int }_0^t\mathrm{d}t}=\frac{1}{t}{\int }_0^{t}A\left(t\right)\mathrm{d}t$$E3

The behavior of B(t) with depletion can be represented with a simple polynomial. In fact, for the duration of only one cycle, it is essentially linear.

$$A\left(\mathrm{t}\right)=A_0+A_{1}t+A_1{t}^2\dots A_n{t}^n$$E4

From basic calculus, the power rule can then be used to find the antiderivative of A(t).

$$B\left(t\right)=\frac{1}{t}\left(A_{0}t+\frac{A_1{t}^2}{2}\dots \frac{A_n{t}^{n+1}}{n+1}\right)$$E5

This process is simplistic but allows for accurate reproducibility of 3D power and burnup behaviors with burnup. This is true so long as power and burnup behavior in the x-y frame are separable from the axial-z frame. This is generally the case with ATR. This process was used to compute A(t) and B(t) for HELIOS using the MCNP code.

The beginning-of-cycle 3D/2D MCNP calculations occur just after the HELIOS fuel selection. With the core load pattern found, the MCNP 21-region model is created. The ORIGEN2 code is used to independently deplete each of the 21-regions assuming an approximate flux shape for an ATR fuel element. The depletion time is carried such that the sum of the 21 U-235 masses and the end of the depletion agrees with the U-235 inventory of that element used in the HELIOS model. The combination of 3D fuel nuclides, 3D experiment models, as well as OSCC and neck-shim positions as a function of burnup constitute the 3D MCNP model.

Unlike the 2D/1D peaking factor used in the PDQ methodology, the 3D/2D MCNP peaking factor may be derived for every fuel element. Here again, it is important to note that this method is very useful only when the x−y frame is separable from the axial frame. Figure 9 shows the change in the axial peak-to-average factor for fuel element five (shown in Figure 1) in the northeast lobe computed with MCNP compared to the generic PDQ factors.

Figure 9.

Comparison of axial peak-to-average factors in previously irradiated ATR fuel elements: power factor (a) and burnup factor (b).

The axial peak-to-average power factor is slower to change with burnup when the KJRR-FAI is present. This too can be attributed to the influence of the KJRR-FAI. It is noteworthy that because the KJRR-FAI is HALEU, as opposed to HEU, it has much more internal fertile-to-fissile conversion. This causes its own reactivity contribution to change slower with time. The KJRR-FAI generally drives the mid-plane power of the ATR fuel elements throughout the four cycles for which the test was irradiated. This caused an increase in the fuel burnup at mid-plane per assembly average burnup.

The combination of starting with heavily burned fuel elements to suppress lobe-power and the faster burnup rate of these elements required careful fuel element selection to ensure that the requested cycle-length could be achieved without exceeding the burnup limits on ATR fuel elements. Careful selection of fuel elements, essentially salvaging fuel elements slated for disposal, enabled the achievement of both the lobe-power and cycle-length constraints.

3.3 Finding a new equivalency

As mentioned previously, HELIOS assumes that all axial details are constant by nature of being a 2D code. This leaves the reactor analyst with one of two choices: extrude the most reactive axial region and assign this geometry and composition to the 2D HELIOS model (1), or axial homogenize all regions within the active core height and assign this composition to the 2D HELIOS model (2). For cases where it is important to preserve the overall reactivity worth of the experiment, its influence on lobe-power, and overall core reactivity, volume weighted axial homogenization is required. For cases where it is important to preserve the spatial self-shielding between the experiment and the nearby ATR fuel elements, extrusion is required. For KJRR-FAI, neither assumption could completely preserve the 3D behavior. Modeling the 21 fuel KJRR-FAI fuel plates as an extrusion artificially assigns the KJRR fuel density meant for 60 cm to the full 121.92 cm (48 in) active height of the ATR fuel. This would grossly over-estimate the fissile content of the test and artificially increase the reactivity contribution of the northeast lobe, thus producing a nonsensical estimate of required reactivity hold-down for the northeast OSCC quadrant. If the KJRR-FAI were homogenized with water and aluminum holders above and below it, the interplay between KJRR-FAI and ATR fuel element plates could be lost; thus, losing confidence in the burnup rate of the northeast lobe’s fuel elements. The solution was a compromise between extrusion and homogenization.

By representing the KJRR-FAI mid-plane geometry in the HELIOS model, but reducing the uranium concentration in the fuel meat, the power of the test and its influence on power of the eight neighboring ATR fuel elements could be preserved. Figure 10 shows the HELIOS computed KJRR-FAI power as a function of fractional uranium loading.

Figure 10.

As-modelled power, using HELIOS, of the KJRR-FAI.

MCNP analysis showed that in order to keep the peak heat flux below the KJRR-FAI programmatic constraint (200 W/cm²), the total fission power of the prototype fuel element would need to be kept to below 2.3 MW³. The minimum heat flux requested was 137 W/cm²; thus, providing a lower bound of 1.6 MW. Therefore, the fractional uranium loading was reduced to 20% in order to provide a representative test power, as well as accurate power sharing behavior within the northeast lobe. Note that the KJRR-FAI fuel meat height is roughly half that of the ATR fuel element, yet the fractional loading is only 20%. This is intuitive if one considers that fuel near the midplane has a greater importance (i.e., considering flux-weighting) compared to fuel further from mid-plane.

The adjustment process is verified against MCNP calculation of the 158A core with OSCC in the startup position of 29 degree rotated-out. This is referred to as the startup power distribution. The comparison of ATR calculated fuel element powers is shown in Figure 11.

Figure 11.

Comparison of calculated fuel element power between MCNP with full 3D detail and HELIOS using a 2D model of the KJRR-FAI with 20% of the true uranium loading.

This adjustment process is validated by the fact that the northeast lobe-power tracks well when compared to the lobe-power measurement system. ATR uses the water activation reaction, ¹⁶O(¹n,p)¹⁶N → ¹⁶N (T_1/2 = 7.13 s) → ¹⁶O + β⁻ + γ to indicate lobe-power. Ten flow tubes, two at central, four at ordinal positions near the lobes, and four at cardinal positions beyond the OSCC provide activation information to ion chambers. The ten ion chamber signals are converted via the least squares method to compute lobe-powers by a monitoring computer. This computer also records the gross calorimetric power of the reactor, as well as the OSCC, and neck-shim positions every hour. This information is combined into a post-cycle analysis of the ATR cycle using HELIOS. This “As-Run” calculation serves two purposes. It provides accurate fuel element depletion results which are then tracked for fuel management records. It also serves as a continuing improvement process for code maintenance of HELIOS and associated ATR models. A comparison of calculated by HELIOS versus measured by the N-16 system for all cycles containing the KJRR-FAI is shown in Figure 12. In the figure, the calculated northeast lobe power is shown with and without the KJRR-FAI. The KJRR-FAI power can be calculated by HELIOS, as was shown in Figure 10. However, calculating experiment power is not part of the typical As-Run process. Therefore, unfortunately, this data is not available. However, the MCNP As-Run for which provides data to the KJRR-FAI project is available and is included in Figure 12.

Figure 12.

Comparison of calculated versus measured (via the N-16 system) northeast lobe-power for ATR cycles: 158A, 158B, 160A, 160B.

4. Summary

The implementation of HELIOS as a design tool for core reload and safety analysis of the ATR is one of the first examples of using whole-core transport codes in such a capacity. Traditionally, codes such as HELIOS, are used for cross-section condensation for use with nodal diffusion codes. Since HELIOS is an arbitrary geometry code, this suits it well for creating cross-section datasets for much faster nodal diffusion codes that then analyze CANDU, RBMK, or VVER reactors. Generally, HELIOS would be an ideal code to support ATR fuel reloading analysis because the ATR was designed with minimum axial perturbation in mind; hence, the use of control drums over control rods. However, with the promise of higher solution fidelity has come more complex experiment designs. Since the KJRR-FAI cycles, more geometrically complex, high fissile worth, and/or high neutron absorber tests have been irradiated in ATR. The challenges of such experiments are as follows: finding fuel elements capable of providing the best irradiation conditions for all the customers of the ATR National Scientific User Facility (NSUF). In the case of high worth tests, this requires selecting fuel elements near the end of their life, but not so spent that they exceed their burnup limit by time the requested cycle-length has been reached.

Assuming this is possible, sufficient fuel must be loaded in the core to have sufficient excess reactivity to accomplish this cycle-length. However, this is limited by the amount of shut-down margin available in the OSCCs. If the loading is too rich, startup could occur in the non-linear range of the OSCC reactivity worth curve, risking a missed startup prediction. Not discussed here, but if a lobe is designed for much higher power operation, i.e., the core power is closer to the maximum rating of 250 MW, the margins to thermal-hydraulic safety limits can be challenged.

Finally, each time the chopped cosine assumption is challenged by such axial heterogeneity, the axial profile is calculated with MCNP, then measured in the ATRC, and ultimately triggers an update to the bounding thermal-hydraulic analysis using the new axial profile. Indeed, this was the case for the KJRR-FAI cycles. A new thermal-hydraulic limit for the ATR fuel element was derived such that the ATR’s flow instability, departure from nucleate boiling ratio, and other safety limits under transient conditions would not be challenged by the KJRR-FAI’s alternative axial profile.

The irradiation of the KJRR-FAI has essentially demonstrated that advanced codes can support advanced hardware. However, there is a tendency to believe that advanced codes can change the operating envelope of a nuclear reactor. The HELIOS and KJRR-FAI experience shows that the operating envelope is set by margins to the safety limits and that these margins are established by measurements. In the case of KJRR-FAI, these measurements were careful fission-wire measurements of the axial shape in the ATRC. The KJRRR-FAI test was a great success and required a great amount of teamwork among physicist and code developers that did the HELIOS code verification and validations, the reactor engineers who did the fuel reloading analysis, ATR plant operations who supported the fission wire measurements, and safety analysts who could understand the historical analysis with PDQ and connect those assumptions with modern application.