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Modelling and Simulation systems PRESENTATION.pptx
1. MODELLING AND SIMULATION OF
NATURAL REFRIGERATION SYSTEMS
EXTERNAL GUIDE:
Dr.SUNIL SHAH
(CEO Modelicon InfoTech LLP)
EVAN AALEX 1MS20CH016
NEHA S PATWARDHAN 1MS20CH024
SARAH FATIMA 1MS20CH030
VISHWANATH SABARAD 1MS20CH043
DEPARTMENT OF
CHEMICAL ENGINEERING
PROJECT GUIDE:
Dr.BRIJESH
2. TABLE OF CONTENTS
1. Scope
2. Objectives
3. Introduction
4. Vapour Compression Refrigeration Cycle
5. Modelling and Simulation
6. Results and Discussions
• COP and Flow rate trends
• Comparison based on COP
• Sensitivity analysis
• Optimization
7. Conclusion
3. Comparison of refrigerants based on factors
such as environmental impact, safety
considerations, application specificity, cost and
energy consumption helps in selection of the
best suited model for the respective application.
SIMULATION
• To optimize the design and maximize the system
efficiency by minimizing energy consumption
and operating cost.
• To scale up the process.
The global green refrigerants market was valued at
US$ 18.8 billion in 2022 and is expected to reach US$
32.1 billion by 2030.
FUTURE OF REFRIGERANTS
• Predict refrigeration system performance with
respect to parameters such as cooling capacity,
COP, temperature etc.
• Process optimization by adjusting parameters such
as flow rate, pressure ratio, temperature etc.
MODELLING
COMPARISON
SCOPE
4. OBJECTIVES
Model and simulate a simple refrigeration loop for each of the four fluids –
carbon dioxide, ammonia, isobutane, and 2,3,3,3-tetrafluoropropene (R1234yf)
using Aspen HYSYS.
Analyse the refrigeration loops over a range of operating conditions and conduct
sensitivity analysis.
Compare these models on the basis of their performance.
Optimize each refrigeration loop to maximize COP
5. INTRODUCTION
• Refrigeration technology plays an
important role in various industries
• 15–20% of the world’s electricity is
used by refrigeration (Yatangababa et al., 2015)
• Most synthetic refrigerants, released
into the atmosphere cause depletion of
ozone layer and global warming.
• Natural refrigerants have low or no
GWP and ODP. (Cavallini 2020; Abas et al.,2018)
6. REFIGERANTS AND THEIR PROPERTIES
Refrigerant R717 R744 R600a R1234yf
Chemical Formula NH3 CO2 CH(CH3)2CH3 CF3CF=CH2
GWP <1 1 4 <1
ODP 0 0 0 0
Critical Pressure (MPa) 11.33 7.38 3.64 3.4
Critical Temperature (oC) 132.2 31.1 134.7 94.7
Normal Boiling Point (oC) -33 -78.4 -11.7 -29.54
Specific Heat capacity
(kJ/kg-K)
4.7 0.63 2.4 1.39
Latent Heat (kJ/kg) 1370 571.0 345.83 180.25
ASHRAE safety group A1 A1 A3 A2L
ASHRAE flammability No No Yes (high) Yes (mild)
ASHRAE toxicity Yes No No No
• Ammonia – R717
• Carbon Dioxide – R744
• Isobutane – R600a
• 2,3,3,3-Tetrafluoropropene
– R1234yf
(Kyriakides et al.,2020)
7. VAPOUR COMPRESSION
REFRIGERATION SYSTEMS (VCRS)
VCRS mainly consists of – Chilled fluid Fluid
EVAPORATOR
CONDENSER
COMPRESSOR
VALVE
Cooling fluid
Evaporator: Heat is absorbed from the medium to
be cooled. Refrigerant evaporates.
Compressor: Refrigerant is compressed to high
temperature and pressure. Compressor circulates
the refrigerant.
Condenser: Refrigerant gives up heat and is
condensed to a liquid.
Expansion valve: High-pressure refrigerant expands
to low temperature and pressure.
8. Specifications Value Unit
Chiller Capacity 200 kW
Chiller water inlet Temperature 12 ℃
Chiller water outlet Temperature 7 ℃
Evaporator Superheat 0, 1, 2 ℃
Cooling water inlet Temperature (Condenser) 24 ℃
Cooling water outlet Temperature (Condenser) 28 ℃
Table 1: Process conditions of the
simulation
Process flow sheet
9. STEADY STATE MODELLING
Equipment Parameter Equation
Evaporator Heat Balance (kW) Q=m Cp ∆T
Compressor
Work done (kW)
Volumetric Capacity (m3/hr)
𝑊 = 𝑧𝑅𝑇
𝛾
𝛾 − 1
[(
𝑃𝑑
𝑃𝑠
)
𝛾−1
𝛾 − 1] × 𝑚
𝑉 =
𝑚
𝜌
Condenser Heat Balance (kW) Q=m Cp ∆T
Expansion
Valve
Pressure Drop (kPa) Δ𝑃 =
Δ𝐻
𝜌. 𝑔. 𝜂
Overall
System
Coefficient of Performance
(COP)
Carnot COP
𝐶𝑂𝑃 =
𝐸𝑣𝑎𝑝𝑜𝑟𝑎𝑡𝑜𝑟 𝐷𝑢𝑡𝑦
𝐶𝑜𝑚𝑝𝑟𝑒𝑠𝑠𝑜𝑟 𝐷𝑢𝑡𝑦
𝐶𝑂𝑃 =
𝑇𝑒
𝑇𝑐 − 𝑇𝑒
Q – heat rate (kW)
m – mass flowrate (kg/h)
Cp – Constant pressure specific heat
capacity
T – absolute temperature (K)
z – compressibility factor
R – universal gas constant (J/mol-K)
Pd – Discharge pressure
Ps – suction pressure
𝜌 – density of fluid (kg/m3)
𝛾 – adiabatic index
𝜂 – adiabatic efficiency
Te − Evaporator temperature (K)
Tc – condenser temperature (K)
10. SIMULATION
1. SETTING THE PROPERTIES
2. SIMULATION ENVIRONMENT
• Four components
• Peng-Robinson fluid package
Heat exchangers
• Tube side – water, Shell side – refrigerant
• Pressure drop
• Chilling water flow rate = 33350 kg/hr
• Inlet and outlet temperatures
Compressor
• Efficiency = 75%
• Pressure ratio = 3
17. OPTIMIZATION
𝐶𝑂𝑃 =
𝐸𝑣𝑎𝑝𝑜𝑟𝑎𝑡𝑜𝑟 𝐷𝑢𝑡𝑦
𝐶𝑜𝑚𝑝𝑟𝑒𝑠𝑠𝑜𝑟 𝐷𝑢𝑡𝑦
𝐶𝑂𝑃 =
𝑇𝑒
𝑇𝑐 − 𝑇𝑒
Refrigerant
Temperature
Variables
Upper bound
(C)
Lower bound (C)
Optimized value
(C)
Carnot COP Correction factor Actual COP
i-butane
Evaporator
temperature
5 -5 -5
8.579 0.706 6.053
Condenser
temperature
39.89 26.24 26.24
NH3
Evaporator
temperature
5 -5 5
12.64 0.434 5.492
Condenser
temperature
39.67 26.81 26.81
R1234yf
Evaporator
temperature
5 -7 -7
8.313 0.576 4.785
Condenser
temperature
48.23 28.01 28.01
CO2
Evaporator
temperature
6 -1 6
13.24 0.331 4.38
Condenser
temperature
32 27.08 27.08
18. • Natural refrigerants are an environmentally friendly alternative to synthetic refrigerants
owing to their low ODP and GWP.
• A comparison among the four natural refrigerants shows that ammonia has the highest COP
followed by the two hydrocarbons (iso-butane and R1234yf), and CO2 has the least COP.
• The sensitivity analysis shows that the condenser temperature has a greater influence on the
COP than the evaporator temperature
• In the optimization studies, COP was maximized by adjusting the condenser and evaporator
temperatures.
CONCLUSIONS
