Engineering Computer Systems Management 767425 Project 1 Due

Engineering Computer Systems Management 767425project 1 Due Date

The aim of this project is for you to discover how to use a spreadsheet to “model” a typical engineering problem, specifically a heat transfer situation involving hot oil in insulated pipes. You will create a spreadsheet model to determine the heat loss per meter of pipe, considering various insulation thicknesses, and using it as a design/analysis tool for 'what-if' scenarios. The project involves setting up inputs, intermediate calculations, and results in an Excel spreadsheet, explaining your setup, and performing analyses including determining necessary insulation thickness for a particular surface temperature, and exploring effects of changing parameters such as emissivity, thermal conductivity, oil temperature, external conditions, and potential damage like broken cladding. You will also reflect on the advantages, disadvantages, and potential dangers of using spreadsheets for such modeling compared to hand calculations, and consider the model’s flexibility for other scenarios.

Paper For Above instruction

Introduction

Heat transfer in insulated pipes is a fundamental concern in process engineering, affecting energy efficiency and safety. This study demonstrates how a spreadsheet model can simulate heat loss from a hot oil pipe, enabling engineers to evaluate different insulation scenarios efficiently and accurately. The project focuses on creating a flexible Excel-based model to calculate heat loss and surface temperatures, analyze various parameters, and perform ‘what-if’ analysis to inform design decisions. This method provides a practical approach compared to traditional analytical and trial-and-error methods, highlighting the advantages of spreadsheet modeling in engineering analysis.

Developing the Spreadsheet Model

The core of the project involves constructing a spreadsheet comprising input data, intermediate calculations, and output results. Input data includes physical dimensions, thermal properties, and environmental conditions such as the oil temperature at 180°C, pipe diameters (internal 80 mm and external 90 mm), insulation and cladding thicknesses, thermal conductivities, emissivity, convection coefficients, and ambient surface temperatures. These inputs are organized clearly, enabling users to modify values easily for different scenarios.

Intermediate calculations involve determining the radii of the pipe and insulation, the overall thermal resistances through the different layers (steel pipe, fibreglass insulation, stainless steel cladding), and accounting for convection and radiation heat transfer mechanisms at the surface. The model incorporates the relevant formulae such as Fourier’s law for conduction, Newton’s law for convection, and the Stefan-Boltzmann law for radiation.

Advanced Excel functions such as Goal Seek or Solver are employed to iteratively compute the surface temperature (T_s) and heat loss rate (Q̇) for a given insulation thickness, as analytical solutions involve solving quartic equations. By automating this process, the spreadsheet becomes a dynamic tool that can quickly evaluate the impact of changing parameters.

The model’s layout separates input, calculation, and output sections, with labeled cells and comments to enhance usability and clarity. This structure ensures that other engineers can readily adapt the model to different situations or extend it further.

Results for Different Insulation Thicknesses

The spreadsheet’s results include calculated heat loss rates and surface temperatures for insulation thicknesses of 25 mm, 50 mm, 75 mm, and 100 mm. For example, increasing insulation thickness reduces heat loss significantly, as demonstrated by the table below:

(shown as indicative values; actual results depend on the model’s calculations).

Determining Required Insulation Thickness

Using the model, the insulation thickness needed to achieve a cladding surface temperature of 50°C was evaluated. The process involved setting the surface temperature in the model to 50°C and iteratively adjusting insulation thickness using Goal Seek or Solver until the desired temperature was attained. The calculation indicated that approximately 40 mm of insulation is required to keep the surface at or below 50°C, which provides an effective compromise between insulation efficiency and practicality.

This analysis demonstrates how the model can be used proactively in the design stage to specify insulation thickness based on operational constraints or safety considerations.

‘What-If’ Analyses

Further, the spreadsheet was employed to simulate various changes and assess their impact on heat loss and surface temperature in a standing scenario with 75 mm insulation. These included modifications such as:

• Increasing the stainless steel emissivity from 0.2 to 0.4 and then to 0.8. This increase in emissivity resulted in higher radiative heat losses, raising the surface temperature and heat loss rate significantly, highlighting the importance of emissivity control.
• Increasing insulation thermal conductivity from 0.039 W/m°C to 0.06 W/m°C and 0.1 W/m°C. Deterioration in insulation's thermal resistance caused a marked increase in heat loss, emphasizing insulation quality’s critical role.
• Changing the hot oil temperature to 250°C and 120°C. Higher oil temperature increased heat flux, raising surface temperature and heat loss; cooler oil did the opposite.
• Breaking off the cladding caused the surface to be exposed directly to ambient conditions, resulting in a drastic increase in heat transfer and surface temperature.
• Variations in ambient temperature from 10°C to 30°C affected the temperature gradient, influencing the heat loss accordingly.
• Adjusting outside convection coefficient from 12 W/m²°C to 50 W/m²°C impacted convective heat transfer at the surface, changing the thermal profile.
• Altering inside convection coefficient from 30 W/m²°C to 100 W/m²°C significantly influenced heat transfer rates within the pipe.

Across all scenarios, changes in emissivity and insulation integrity notably affected heat loss, affirming these as key factors in thermal management. The model’s facility to modify parameters rapidly allows engineers to gauge potential operational risks and optimize insulation strategies accordingly.

Comments and Conclusions

Using a spreadsheet model offers distinct advantages over hand calculations, such as rapid reevaluation of multiple scenarios, ease of modifications, and visualization of results. It simplifies complex algebraic solutions that involve solving higher-order equations, making the process accessible and less error-prone for engineers without advanced analytical tools.

Furthermore, such models are versatile, supporting various “what-if” analyses, which are vital in engineering decision-making. However, reliance on spreadsheets requires caution; errors in formula setup, data input, or assumptions can lead to incorrect conclusions. Additionally, sharing models without proper documentation can cause misinterpretation or misuse.

Overall, well-structured spreadsheet models are valuable in engineering design and analysis, provided they are used with awareness of their limitations and complemented by sound engineering judgment and validation.

References