🛠️ Using Exergy Balances in Practice

Now that the conceptual foundations are in place, this page shows how exergy balances are actually used — and what precautions to take when interpreting them. Three questions are addressed in turn: how to optimise a cycle step by step, how the choice of source temperature Tk affects the results, and how two reactors with very similar energy efficiencies can have very different exergy profiles.


U1 — Reading a Balance to Guide Optimisation

An energy balance tells you how much energy is lost. An exergy balance tells you where, how much, and in what order to act. This is a fundamental difference for the engineer.

The example below follows four successive configurations of a steam cycle based on the AGR design (CO₂ gas coolant, Tk = 700 °C, T₀ = 20 °C). Each configuration was chosen by reading the balance from the previous step.

The four configurations

The exergy balance files are accessible through the links in this table.

Configurationη Xhη energyDominant irreversibility
Simple cycle53.6 %37.5 %Source / SG: 73.5 %
+ Reheat57.0 %39.9 %Source / SG: 74.1 %
+ Reheat + 1 FWH60.4 %42.2 %Source / SG: 63.4 % — FWH: 7.4 %
+ Reheat + 2 FWH60.7 %42.4 %Source / SG: 62.3 % — FWH: 8.1 %

What is striking is the evolution of the overall exergy efficiency as technological modifications take place.

Step-by-step reasoning

Simple cycle — η Xh = 53.6 %

The balance is immediately readable: the source (steam generator) accounts for 73.5 % of total irreversibilities. The economiser alone absorbs 49 %. Turbines represent only 20.7 %, the condenser 5.7 %. The message is unambiguous: the main lever is not in the turbines — it is in the heat transfer from the gas to the steam.

+ Reheat — η Xh = 57.0 % (+3.4 pts)

In a cycle with reheats, we begin by partially expanding the steam, then it passes again into the boiler, where it is heated at the new pressure to approximately the maximum cycle temperature.

This results in efficiency gains of a few percent and, most importantly, as shown in the diagram, increased quality at the end of expansion, which is always beneficial for extending the life of turbine blades.

Reheat redistributes some of the SG heat through an additional turbine stage and improves mean isentropic efficiency. Yet the source remains dominant at 74.1 % — its relative weight has barely changed. A different lever is needed.

+ 1 feedwater extraction (FWH) — η Xh = 60.4 % (+3.4 pts)

In a steam cycle, it is possible to undertake partial regeneration by using part of the heat rejected during expansion for preheating the pressurized liquid water before it enters the boiler.

Consider a cycle with reheat. If we extract a small quantity of steam, called extraction steam or bleed steam, at the outlet of the first expansion, at point 4a in the figure, its pressure remains high enough to condense it at a temperature that allows preheating the pressurized water leaving the pump at point 2.

The enthalpy of the vapor is much greater than that of the liquid, due to the latent heat of vaporization. It is then possible to preheat the liquid using a small extraction of steam during expansion.

This operation is carried out in specific components called feedwater reheaters FWH.

This cycle is called a regenerative Rankine cycle, also known as an extraction and reheat steam cycle.

Now the source falls to 63.4 % (−10.7 pts). Preheating the feedwater reduces the temperature gap in the economiser, which had been the dominant component since the start. The FWH carries its own irreversibility cost (7.4 %) but saves far more on the source.

+ 2nd extraction — η Xh = 60.7 % (+0.3 pts only)

The source falls slightly again (62.3 %), but the marginal gain collapses. The balance signals that diminishing returns have been reached: the second extraction costs almost as much as it saves.

Steam extraction allows the feedwater to be preheated (via the FWH) before it enters the economizer. By reducing the temperature difference in the economizer, exergy analysis shows that its irreversibilities have been halved (from 278.5 kW to 129.4 kW).

The lesson: at each step, the exergy balance indicated which lever to pull by tracking the dominant component. It serves as a guide for optimization.


U2 — The Source Temperature Convention: the Choice That Changes Everything

All the balances in this section use a source temperature Tk chosen according to the type of heat exchange between the coolant and the steam. The convention is:

Exchange typeΔTRationale
Liquid coolant → boiling (WCR)+35 °CTypical pinch for liquid/boiling exchange
Liquid sodium → steam (SFR)+50 °CLarger pinch for liquid/vapour exchange
Supercritical water → steam (SCWR)+50 °CSame
Gas → steam (AGR, HTR)+60 °CLarger pinch for gas/vapour exchange

This convention has a direct consequence: a higher Tk mechanically reduces η Xh, because more of the core irreversibilities are attributed to the source component. Two reactors cannot be compared on η Xh alone without knowing their respective Tk values.

A concrete illustration — what happens when Tk increases on the Flamanville EPR:

The ExergyTkSensitivity tool sweeps Tk from the balance value to 1000 °C, keeping T₀ and all other irreversibilities fixed. Applied to the EPR Flamanville detailed balance (Tk = 334 °C, T₀ = 15 °C):

EPR Flamanville — Tk sensitivity EPR Flamanville — Tk sensitivity Sensitivity of η Xh (blue), source % (red) and condenser % (green) to source temperature Tk for the EPR Flamanville detailed model.

  • At Tk = 334 °C (reference): η Xh = 73.4 %, source = 30.0 %, condenser = 22.7 %
  • At Tk ≈ 445 °C: source and condenser curves cross (~30 % each) — the source becomes dominant
  • At Tk = 700 °C: η Xh ≈ 54 %, source ≈ 49 %, condenser ≈ 12 %
  • At Tk = 1000 °C: η Xh ≈ 35 %, source ≈ 57 %, condenser ≈ 9 %

The cycle has not changed. Only the accounting of the source has changed. This is why the AGR (Tk = 699 °C, η Xh = 61.8 %) and the EPR (Tk = 334 °C, η Xh = 73.9 %) cannot be compared directly: the AGR balance includes the irreversibilities of the entire CO₂ coolant circuit, while the EPR balance only includes the near-boiling heat exchange at 334 °C.

The crossing point at ~445 °C is particularly informative: below this temperature, the condenser is the larger structural loss term; above it, the source dominates.

The physical basis: Carnot factors and what Tk really controls

The source temperature Tk enters the exergy balance through the Carnot factor (1 − T₀/Tk), which converts a heat flow Q into its exergy equivalent:

Xh = Q × (1 − T₀/Tk)

Changing Tk therefore changes the exergy attributed to a heat exchange — and this has very different consequences depending on whether it is the hot source or the cold source that is varied.

Varying the hot source temperature Tk affects only the components that exchange heat with the hot source — typically the steam generator, economiser, core, or IHX. All other irreversibilities in the balance (turbines, feedwater heaters, mixing valves, pumps) are computed from fluid state differences and do not depend on Tk. This is exactly what the ExergyTkSensitivity tool exploits: it sweeps Tk over a range and recomputes only the source component contributions, keeping everything else fixed. The result is a clean sensitivity curve that answers the question “how much of the η Xh difference between two reactors is due to the Tk convention?”

It is precisely because the thermal power Q transferred by the hot source can be back-calculated from the source exergy and Tk — via Q = Xh_source / (1 − T₀/Tk) — that the values Q_th and η energy have been appended to the bottom of the exergy balance files. Knowing Q_th allows the energy efficiency to be derived directly from the balance, without requiring a separate energy model. The ExerBalanceHX post-processing tool computes and writes these two values automatically when it processes a balance.

Varying the cold source temperature Tcond is an entirely different matter. Tcond is the temperature of the condenser cooling fluid. If it changes, the condenser thermal equilibrium shifts, its condensation pressure changes, and — through the turbine expansion ratios — the pressures and enthalpies at every turbine stage are modified. The irreversibilities of all turbine stages change, the extraction flows to the feedwater heaters change, and the entire cycle operates at a new off-design point. This cannot be studied by a simple balance recalculation: it requires a full thermodynamic cycle model operating at the new conditions.

This is one of the specific strengths of Nuscle: because it models the complete secondary circuit thermodynamically, it can simulate the effect of a change in condensation temperature and generate a new consistent exergy balance for the modified operating point — something that a post-processing tool like ExergyTkSensitivity cannot do. The NuScale US460 and ABWR cases (both designed with air-cooled condensers at 35 °C rather than the standard 15 °C) will be studied this way when the corresponding Nuscle parametric models are available.

Two valid questions, two valid conventions:

  • “How good is the secondary cycle alone?” → Use a Tk close to the actual heat exchange temperature (Tprimary + ΔT). Differences between reactors reflect cycle quality.
  • “How efficiently does the full plant convert nuclear heat?” → Use a common Tk for all reactors. Differences reflect the combination of core and cycle performance.

Both are legitimate. The key is to state which question is being answered before presenting the numbers.


U3 — Exergy Balances as a Diagnostic Instrument

The AGR four-step example in U1 illustrates a general principle: as a cycle approaches its thermodynamic optimum, the dominant irreversibility shifts from the source to the components that are harder to reduce.

The EPR Flamanville 3 is a 1 650 MWe pressurised water reactor, primary at 300 °C / 155 bar, steam at 294 °C / 75 bar, with eight feedwater heaters, double reheat, and six LP turbine stages. It is the most powerful reactor currently operating in France.

For the EPR Flamanville detailed model (η Xh = 73.9 %), the exergy balance shows:

Component% of total irreversibilities
Source (SG + economiser)30.0 %
Turbines32.2 %
Condenser22.7 %
Feedwater heaters (FWH)0.7 %
Reheaters3.8 %
Remaining10.6 %

No single component dominates. The balance is well distributed — a signature of a well-optimised cycle. Any further improvement would require acting on multiple components simultaneously for marginal gains.

The VVER-70 is the first Soviet pressurised water reactor design, installed at the Novovoronezh plant (units 1–2, 1964–1969). Three K-70-29 turbines of 70 MWe each give a total output of 210 MWe from a thermal power of 760 MWth. The primary coolant operates at approximately 248 °C, steam is produced at 29 bar — saturated, with no superheat. Between the HP and LP turbine sections, a moisture separator reduces liquid content to ~1 % but does not raise steam temperature.

For the VVER-70 (η Xh = 57.5 %, Nuscle model), the exergy balance shows:

Component%
Source39.5 %
Turbines36.6 %
Condenser19.2 %
FWH1.6 %

Here the source is clearly dominant (39.5 %) and the FWH contribution is almost negligible (1.6 %). The balance immediately points to two actions: reduce the temperature gap in the steam generator (e.g., by adding superheat) and increase the regenerative feedwater heating. These are precisely the changes made in the VVER-1000, which achieves η Xh = 68.0 % — a gain of 10.5 points.

Two modelling notes for the VVER-70 are important for correct interpretation:

No reheat after the separator. The K-70-29 turbine uses a moisture separator only — there is no steam reheater between the HP and LP sections. The separator reduces liquid content to approximately 1 %, but without raising the steam temperature. The Nuscle model reflects this by setting the reheat flow to effectively zero; the corresponding lines have been removed from the published balance. This means the VVER-70 and VVER-1000 are not simply two generations of the same design — they represent two fundamentally different cycle philosophies (saturated steam + separator vs superheated steam + MSR).

Talim is estimated. The feedwater inlet temperature to the steam generator (Talim) is not documented in available sources for the Novovoronezh unit 1-2. It has been estimated from the known thermal power (760 MWth) and electrical output (210 MWe). A ±20 °C uncertainty on Talim propagates to approximately ±3 pts on the source % and FWH % individually, but affects η Xh global by less than ±0.5 pt. The η Xh = 57.5 % figure is therefore robust; the component breakdown carries a moderate uncertainty on the source/FWH split.

The exergy balance is a diagnostic instrument. It does not prescribe solutions, but it ranks the components by their contribution to total irreversibility — and that ranking is the starting point for any systematic optimisation effort.


U4 — η Xh and η Energy: Two Readings of the Same Cycle

η Xh and η energy (= net electrical output / thermal power input Q_th) are two important indicators. This is why we have included both in all balances.

Here are some results:

ReactorTk (°C)η Xhη energyRatio η Xh / η energy
EPR Flamanville (detailed)33473.9 %38.5 %1.92
Canadian SCWR67068.5 %47.6 %1.44
AGR Hartlepool69961.8 %43.5 %1.42
Superphénix60064.7 %43.3 %1.49
CANDU29268.4 %33.5 %2.04
RBMK32465.2 %33.7 %1.93
HTR-PM62459.2 %

The ratio η Xh / η energy is roughly constant (~1.9–2.0) for WCR designs with Tk near 300–340 °C, but falls significantly for high-temperature reactors (SCWR: 1.44, AGR: 1.42). This reflects the fact that at high Tk, the source Carnot factor (1 − T₀/Tk) is large — the exergy of the heat supplied approaches its energy value — so η Xh and η energy converge.

For low-Tk WCR designs, Q_th must be much larger than the electrical output to provide the same exergy resource, so η Xh appears much higher than η energy. This is thermodynamically consistent: the available work fraction of heat at 300 °C is only ~50 %, meaning the reactor must supply roughly twice the exergy to produce a given electrical output.

Practical implication: η energy is the efficiency most familiar to plant operators and regulators. η Xh is the efficiency most useful for cycle optimisation and inter-design comparison. Neither is “more correct” — they answer different questions.


U5 — Exergy Diagrams: Visualising Irreversibility

Numbers in a table tell the story. Diagrams make it immediately visible. Three complementary representations are used in this section.

The Grassmann / exergy Sankey diagram

The Grassmann diagram is the exergy counterpart of the Sankey energy flow diagram. Each arrow is proportional to the exergy flow it represents. Irreversibilities appear as arrows branching off to the side — they literally show exergy “leaking out” of the system at each component.

For the four AGR configurations (U1), a Grassmann diagram shows the economizer branch shrinking between configurations 1 and 3 as the FWH reduces the temperature gap — while a new branch appears for the FWH itself. The net reduction in total branch width is the gain in η Xh.

The Grassmann diagram is most readable for simple cycles (4–8 components). For complex cycles like the EPR (40+ components), it becomes dense; the stacked bar chart is then more practical.

AGR cycle — four configurations AGR cycle — four configurations

Grassmann diagrams for the AGR configurations will be added here when available.

Stacked bar charts of irreversibility distribution

This is the representation used in U1. Each bar shows the percentage distribution of irreversibilities across component groups (source, turbines, condenser, FWH, reheaters) for one configuration. Overlaying the η Xh curve on a second axis makes the link between component-level changes and global efficiency immediately visible.

The stacked bar chart is the most practical format for comparing multiple configurations or multiple reactors, because it is compact, easy to read, and directly generated from the balance data. It answers the question “where do the losses go?” at a glance.

*Evolution of irreversibility distribution across four AGR cycle configurations. The source (green) dominates until feedwater heating is introduced (step 3). The marginal gain from the second extraction (step 4) is immediately visible.*

Sensitivity curves (ExergyTkSensitivity)

The ExergyTkSensitivity is a tool that accepts any Thermoptim exergy balance (pasted into a text area), and sweeps Tk from the balance value to 1000 °C, and plots three quantities in real time: η Xh, source %, and condenser %. An Export CSV button allows the data to be retrieved for further processing.

The tool is distributed as a standalone JAR and accepts both the modern RAW_FORMAT (UTF-8, dot decimal) and legacy locale-formatted balances.

A JAR or Java Archive is a software package that bundles all the compiled Java class files, resources and metadata needed to run an application into a single compressed file. Like a ZIP archive, it can be opened and inspected with any standard archive tool. To run it, the user only needs a Java Runtime Environment (JRE) installed on their machine — no installation, no dependencies to manage. A double-click or the command java -jar filename.jar is sufficient.

ExergyTkSensitivity — EPR Flamanville ExergyTkSensitivity — EPR Flamanville The ExergyTkSensitivity tool applied to the EPR Flamanville detailed balance. η Xh (blue) falls from 73.4 % at Tk = 334 °C to ~35 % at 1000 °C. Source % (red) rises from 30 % to ~57 %. Condenser % (green) falls from 22.7 % to ~9 %. The source and condenser curves cross at ~445 °C.

This diagram answers a specific question: how much of the apparent η Xh difference between two reactor types is due to the Tk convention, and how much reflects genuine cycle quality? Sweeping Tk from 334 °C (EPR convention) to 699 °C (AGR convention) shows η Xh falling from 73.4 % to approximately 54 % — entirely due to the change in accounting, with no change to the cycle itself.

For the NuScale US460 and ABWR, which use a condenser at 35 °C (air-cooled design basis), the sensitivity to Tcond will be demonstrated when the corresponding Nuscle parametric models are available.


U6 — The Five Pillars of Exergy Analysis

In U1, we used exergy balances to optimise an AGR cycle. But optimisation is only the entry point. Beyond it, exergy analysis opens five fundamental pillars where it provides something no other method can.

1. Advanced Diagnostics and Physical Analysis

Exergy acts as a “medical scanner” for industrial processes, making “invisible” losses visible.

  • Anomaly Detection: It identifies components with disproportionate irreversibilities, such as a feedwater heater with low isentropic efficiency or a turbine struggling with wet steam conditions, which would remain hidden in a standard energy analysis.

  • Internal vs. External Losses: It distinguishes between exergy rejected to the environment (exhaust) and exergy destroyed internally due to friction, chemical reactions, or heat transfer across large temperature gaps.


2. Universal Benchmarking and Technology Comparison

Exergy provides a “unique currency” that enables rigorous comparison of disparate energy flows and systems.

  • Heterogeneous Systems: It allows designers to compare the efficiency of a biomass boiler with an electric heat pump or a solar thermal system on equal footing.

  • Architectural Benchmarking: It facilitates the comparison of different reactor architectures (e.g., VVER-70 vs. VVER-1000) or low-carbon technologies (e.g., nuclear vs. combined-cycle gas turbines) by using consistent reference temperatures ((T_k)).


3. Strategic Design and “Blank Page” Engineering

In the early stages of design, exergy balances guide the choice of system architecture before detailed engineering begins.

  • Identifying Leverage Points: Simplified models can immediately reveal if a design is “source-dominated” or “turbine-dominated”, indicating whether the designer should focus on upstream primary temperatures or downstream turbine efficiency.

  • Systems Integration: It forms the foundation of Pinch Analysis, helping to identify optimal couplings between processes—such as using 200°C waste heat as a resource for a process requiring 150°C—to create coherent multi-energy networks.


4. Sustainability and Environmental Impact

Exergy is a primary indicator of resource depletion and true environmental efficiency.

  • Sustainability Metrics: It measures what is irreversibly lost versus what could potentially be recovered, such as identifying the cogeneration potential of waste heat rejected by a condenser.

  • Exergy-Based Life Cycle Assessment (ELCA): It serves as the basis for Exergy-Based Life Cycle Assessments (ELCA), quantifying the exergy footprint of industrial processes and the degradation of raw materials.


5. Economic Valuation and Policy Governance

Because exergy is correlated with the economic value of an energy flow, it serves as a tool for strategic decision-making.

  • Investment Prioritization: Higher exergy flows (like electricity) command higher economic value than low-exergy flows (low-temperature heat), allowing factories to establish internal pricing and prioritize investments.

  • Technological Arbitrage: It provides a scientific basis for policy decisions, such as demonstrating why using hydrogen for domestic heating is a “strategic heresy” due to exergy destruction, whereas its use in heavy industry is justified.

  • Pedagogical Tool: It clarifies the fundamental difference between energy quantity and quality, helping to explain the structure of losses in any complex system.



U7 — Nuscle Models vs Detailed Models: What the Gap Means

When the same reactor is modelled with both Nuscle and a full Thermoptim model, the η Xh values differ systematically — by 6 to 8 points for WCR designs. This is not a flaw; it is a known and quantifiable property of the simplified model.

EPR Flamanville — two models, same reactor:

Modelη Xhη energySource %Condenser %Turbines %
Detailed73.9 %38.5 %30.0 %22.7 %32.2 %
Nuscle65.8 %34.6 %22.7 %18.6 %39.5 %
Gap−8.1 pts−3.9 pts−7.3 pts−4.1 pts+7.3 pts

The Nuscle model uses fewer feedwater heaters and larger extractions to reach the same feedwater temperature. This pushes more of the work through the turbines (hence the higher turbine percentage) and reduces the apparent source and condenser contributions. The η Xh is lower not because the reactor is worse, but because the cycle model is simplified.

Why this matters for comparisons: when comparing a Nuscle model with a detailed model, the gap is real but not a direct measure of reactor quality. The Nuscle result tells you where the cycle sits relative to other WCR designs modelled the same way. The detailed result gives the absolute reference.

Nuscle is best understood as a rapid prototyping and pedagogical tool — it answers “how does this WCR design compare to others under the same modelling assumptions?” rather than “what is the exact η Xh of this reactor?”


This page corresponds to posts U1 through U7 of the companion LinkedIn series on exergy analysis of nuclear reactor thermodynamic cycles.