Heat Exchanger Performance Monitoring
Monitoring heat exchanger performance is a common practice, primarily when fouling poses an issue. It's a process as simple as a single computation in a spreadsheet, or it could be more complex and managed by software tools capable of dealing with heat exchanger networks, processing large volumes of historical data, and simulating various heat exchanger types. These tools can also predict the fouling process for future decisions and execute these tasks automatically at a chosen time interval. There are also hybrid methods that blend software with manual computations and estimations.
Irrespective of the complexity of the calculation, a fundamental necessity in monitoring heat exchanger performance is to quantify the fouling impact (or the losses), which should be assessed using the heat duty. The financial equivalent of the loss (heat duty translated into money) should guide decision-making, determining the measures to be taken and analysing the cost vs benefit of these measures.This blog post provides a fundamental understanding of heat exchanger monitoring and its prerequisites. It is framed under the assumption that the objective of monitoring is not merely to observe the decline in performance, but to make action-oriented decisions, based on data quantification.
Data Requirements and Definitions
Data Availability
For the computation of heat duty (Q), we require details on flow rates, inlet/outlet temperatures, as well as specific heats or enthalpies corresponding to these temperatures. Provided that such data can be sourced from either the hot or cold side, the operational heat duty can be estimated.
Precision
It's important that flow and temperature instruments are working properly to achieve a reasonable accuracy in heat duty computation, ideally within ±15%.
Heat Balance
The heat duties from both sides (hot and cold) should align, preferably within an acceptable range of ±15%. Major discrepancies may lead to high inaccuracies in cost and benefit estimation, depending on which side is considered as the reference point.
Frequency
Daily averages of flows and temperatures are adequate for effective quantification and decision making. It is only in rare circumstances that we may need data at a higher frequency, such as hourly averages.
Actual Heat Duty (Qa)
This is determined daily by using current flow rates and temperatures to calculate the operational heat duty. This value is naturally subject to change, and the changes could be significant depending on the stability of process flows and temperatures.
Clean Heat Duty (Qc)
This refers to the heat duty calculated without fouling, using the same flow rates and temperatures as in the calculation of Qa. Please note, this computation requires a simulation and hence, cannot be accurately done if only simple formulas on a spreadsheet are employed for monitoring.
Fouling Losses
Looking at the heat duty, the loss due to fouling is denoted by (Qc-Qa). This loss can further be translated into financial losses based on the heat exchanger's function. If it affects energy (for example, furnace fuel consumption), the cost of fuel along with related emissions will rise. If the fouling results in reduced process rates, the financial burden will be in terms of lost output and its corresponding profits.
Simple Heat Exchanger Monitoring
Whenever a fluid is in a single-phase state, liquid or gas, and we have access to the flow rate and temperature data at both the point of entry and exit, we can compute the heat duty (Qa) on a daily average basis and establish trends. The clean heat duty (Qc) can be approximated as the heat duty right after cleaning on the first day, when the full operational status is attained.
Sometimes, operating engineers extract a further parameter from the heat duty and temperatures, the overall heat transfer coefficient (OHTC), which is also known as the U-value. This is typically "normalized" to set flow values and then trended. This method doesn't offer a specific measure of the losses due to fouling; all it highlights is a decline in heat transfer, which is not helpful unless Qc is calculated as a subsequent step.
In situations when the data from the single-phase side is not accessible, or when both sides undergo a phase change (condensation and boiling), calculating a heat duty using the operating pressures and temperatures becomes challenging.In such scenarios, computer tools are essential.
Network Impact
Heat exchangers can constitute a part of a heat integrated network of multiple exchangers. In this case, the performance of one heat exchanger influences the flow and temperature conditions of the other ones. A simple illustration is provided in Fig. 1. If heat exchanger E3 fouls or is detached for cleaning, the temperature of the Hot1 stream that goes to heat exchanger E1 varies, which also impacts the hot and cold temperatures in heat exchanger E2. Rather than considering the Qa and Qc values for individual heat exchangers, the values for all three heat exchangers (the network heat duty) should be the basis for decision-making.
Common Issues
Let's look at some of the common issues that arise while performing heat exchanger monitoring and executing the recommended actions. Cleaning the heat exchanger is often the most common action, where the cleaning technique and its subsequent benefits can be important (see article “Understanding and Selecting Heat Exchanger Cleaning Techniques”).
Unreliable or partial data
An impact on the heat duty calculation's precision can be traced back to this, which might affect the heat balance, further adding to the uncertainty of which figures to apply. An ideal solution for critical heat exchangers would be to install or repair the essential flow and temperature measurement tags.
Two-phase heat exchangers
Carrying out precise monitoring on services like condensers and reboilers is almost unattainable without employing computer tools. The computations for Qa and Qc necessitate two-phase attributes like vapor fraction, teamed with robust computer software to conduct two-phase calculations.
Optimum Cleaning
Despite precise monitoring, cleaning at the best time isn't always feasible, which is when the total of the fouling and cleaning costs is the lowest. For instance, it may not be acceptable to interrupt the process as the heat exchanger will be out of service. Practical methods adopted by operators include planning in advance, requiring monitoring calculations to estimate which heat exchangers would be ideal to clean on a specific future date. Or, cleaning at fixed intervals and choosing the heat exchangers that offer the maximum advantages at that particular moment.
Impact on Network
To accurately monitor a network, even with very few heat exchangers, it is essential to use a computer tool that can simulate the heat exchangers and the network interactions. If done manually, you must guess (perhaps based on past cleanings) the effect a heat exchanger cleaning will have on the network's heat duty.
Duty Controlled Heat Exchangers
Certain heat exchangers function at a controlled fixed heat duty, like on pumparound or reflux streams. Monitoring may reveal fouling, but cleaning them before the process is impacted may not be beneficial. Accounting for this in network computations is crucial.
Conclusion
The optimal method for monitoring fouling in heat exchangers entails measuring the pros and cons of executing actions like cleaning. We can achieve this assessment by comparing the operating heat duty with the one of a clean heat exchanger under the same working conditions. While basic manual techniques can suffice in single-phase services, for accuracy in measuring networks and two-phase heat exchangers, we need heat exchanger and process simulation software tools.
What’s next
Our next article will delve deeply into the financial aspects of fouling in heat exchangers, focusing on how to assess the most efficient fouling mitigation action.