Development of an Adaptive Food Preservation System for food quality and energy efficiency enhancement

Accepted Manuscript Title: Development of an adaptive food preservation system for food quality & energy efficiency enhancement Author: Andrew H.F. Tsang, KC Yung PII: DOI: Reference:

S0140-7007(17)30058-0 http://dx.doi.org/doi: 10.1016/j.ijrefrig.2017.02.006 JIJR 3550

To appear in:

International Journal of Refrigeration

Received date: Revised date: Accepted date:

7-6-2016 13-1-2017 11-2-2017

Please cite this article as: Andrew H.F. Tsang, KC Yung, Development of an adaptive food preservation system for food quality & energy efficiency enhancement, International Journal of Refrigeration (2017), http://dx.doi.org/doi: 10.1016/j.ijrefrig.2017.02.006. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Development of an Adaptive Food Preservation System for Food Quality & Energy Efficiency Enhancement. Tsang, H.F. Andrew1*, Yung, KC1 1

Department of Industrial & System Engineering, Hong Kong Polytechnic University, Hung Hom, Hong Kong

* Corresponding author. Tel.: +852 6112 2960 E-mail address: [email protected] General PO Box 10099, Central, Hong Kong Highlights:     

Adaptive Food Preservation System is proposed to customize food storage conditions Key improvements in food quality and energy efficiency Key components include vortex tube and storage packages Freezing capacity and efficiency of key components have been evaluated Regression model of the simulated AFPS package thermal efficiency was developed.

Abstract This paper proposes a system design of an Adaptive Food Preservation System (AFPS). It is motivated by the fact that constant storage condition in today’s refrigerators has deficiency. Customized storage with fast freezing capability can better manage food quality and energy efficiency. Key components include AFPS packages and vortex tubes. Superior fast freezing capability is demonstrated by comparisons with benchmarks from refrigerator tests and regulatory standards, and experimentation with a simulated test setup at various settings of input. Theoretical and analytical models are proposed to predict package inlet and exit temperatures, freezing capacities, and freezing efficiencies. At 7 bar inlet pressure, the maximum available freezing efficiency, mean efficiencies with vacuum insulation and with ABS insulation of the AFPS Package & Vortex Tube Assembly are 6%, 4.66%, and 2.80%, respectively. AFPS technology consumes 0.18% in time and 45% in energy during fast freezing comparing with what a typical household freezer does.

1

Keywords Adaptive Food Preservation, Food Storage Customization; Refrigeration, Food Quality, Energy Efficiency, Vortex Tube

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

1

Specific heat capacity at constant pressure Coefficient of Performance Depth of package Hydraulic diameter Friction factor Heat transfer coefficient of the air inside the package wall Heat transfer coefficient of the air outside the package wall Joule Kilojoule Log to base 10 Natural log Length of package (duct length) Nusselt number Nusselt number considering duct friction factor Internal gauge pressure

Page

Nomenclature Cp COP D Dh f hinside houtside J KJ Log10 Ln L Nu Nuf Pg

Jan 2017

Page 1 of 29

Pi Pr Re SLPM Tenter Tmiddle Texit Twall tf U Uav VT μ μs ρ

Air pressure at the inlet Prandtl number Reynolds number Standard Litre Per Minute Air Temperature at the Package Inlet Temperature (or VT Exit Temperature) Air temperature measured in the middle of the AFPS package Air temperature at the package exit Temperature on the package wall outside surface Freezing time (from 0°C to steady state temperature below 0°C) Overall heat transfer coefficient of the package Air speed (average) inside the package Vortex Tube Fluid viscosity at bulk fluid temperature Fluid viscosity at the heat transfer boundary surface temperature Air density

Page

2

2

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 2 of 29

1

Introduction

1.1 Areas of Improvement in Today’s Refrigerators The fact that different types of foods have their own best storage conditions (temperature, relative humidity, etc) has been known for many decades [1]. New technologies [2] have been introduced during the last two decades to improve food storage quality along the cold chain. Despite of their merits, there are still much room to improve on factors that may compromise food thermal stability and distribution and consequently cause direct impact on food quality and energy efficiency. Table 1-1 shows the details. The purpose of this paper is to introduce a novel concept called Adaptive Food Preservation System (AFPS) which provides fine segregation and customized storage (e.g. temperature, relative humidity, gas types, etc) of individual food items in order to improve food quality and energy efficiency. The AFPS Appliance can greatly alleviate the impact or remove altogether the causes of the issues. This brings a paradigm change from “CONSTANT storage conditions for ALL food categories” to “CUSTOMIZED storage conditions for INDIVIDUAL food item”, hence the term “Adaptive”.

1.2

3

Customization of Food Storage as the Solution

AFPS Appliance customizes the storage environment for specific food types and on piece by piece (or a small bundle) basis. It functions as a “mini-freezer” or “mini-chiller” inside a refrigerator - Table 1-2 tells how food storage customization contributes to improve the issues in Table 1-1.

1.3

Main Goals of this Research Work

The goals of this Paper are threefold: (a) Provide a conceptual design of customized storage of food items with fast freezing capability. Section 2 will address this topic. (b) Evaluate analytical and experimentally the fast freezing capacities of the key components with different package wall insulation materials. Details can be found in Section 3.

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page

2 Conceptual Design – Overall System & Key Components Of an Adaptive Food Preservation System (AFPS) Appliance

3

(c) In Section 4, freezing efficiency with analytical and theoretical approaches will be evaluated considering the factors that cause loss in freezing capacities. Efficiency from theoretical formulation is compared with regression model built from experimental data. To further demonstrate the advantage of customized food storage, energy efficiency will be compared with that of a typical household freezer.

Page 3 of 29

2.1

Overall System and Main Operations

In an AFPS Appliance, many individual AFPS packages work along with vortex tubes. Each package stores one piece of food item (within the size and capacity limits). Various sizes are available for different food categories and are connected with tubings to the Appliance’s main air or gas supply and compressor. Figure 2-1 shows the overall system of the Appliance, the key components and the structure of an AFPS package. In addition to a traditional compressor for refrigerant processing, an air compressor or other compressed air source supports VT operations.

2.2

Two Main Components of the AFPS Appliance

2.2.1

Structure and Operations of the Proposed AFPS package

From Figure 2-1, during fast freezing, air / gas produced through VT passes through Flow Path I. Non-moving air or vacuum is created (with two valves closed) along Flow Path II for higher insulation. Other than air, nitrogen, oxygen, carbon dioxide, or ionized air can be used optionally at a higher Appliance cost. These gases can be used alternatively to maximize effectiveness of food preservation. During long-term low temperature maintenance, cold air from refrigerant compressor circulates through Flow Path II. The wall between Flow Path I and II has high thermal conductivity to facilitate thermal conduction. Outside of the Flow Path II, the wall material has high thermal insulation in order to resist heat influx from the Appliance’s interior space.

4

When thawing or defrost is needed, the hot air or gas from VT passes through Flow Path I, at appropriate flow rate and temperature. In this process, air or vacuum insulation reduces heat loss and can maximize thermal efficiency. AFPS packages are hidden inside the Appliance from the ambient so that double insulation is afforded. This helps to alleviate the issues raised from the single insulation system like today. 2.2.2

Operations of the Proposed Vortex Tube (VT)

Even though a VT itself has an inherently low COP, normally less than 10% [8], there are still compelling reasons stated below to use VT for fast freezing in the Appliance. (a) Due to completely segregated storage of individual food item, there is no need to cool, freeze, thaw, or defrost all the food items in the compartment at the same time.

(c) Temperature cycling of refrigerant compressor may detrimental to food quality. Cold air from VT can serve as backup or secondary cooling option to minimize food temperature cycling during the long-term low temperature maintenance.

4

(d) Due to the very nature that VT generates cold air and high air speed at the same time, no

Page

(b) Since the package space is much smaller than that of the whole refrigerator compartment, the time necessary to achieve steady state low temperature inside the package is much shorter, hence reducing the energy input.

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 4 of 29

extra mechanism is needed to drive up air speed or air flow rate. Heat transfer rate has a direct relationship with both the temperature difference between the food surface and cold air, and flow rate (or speed) of the cold air (related to heat transfer coefficient). Increasing the temperature difference means that refrigeration compressor must be pushed to its limits in energy usage and operating time, hence not a desirable option [9]. VT can improve cold air flow rate with much lower energy consumption. (e) Furthermore, current evaporator design does not allow cold air flow from picking up high speed. Even if it is possible, the fact that food items stacked up on top of each other tend to block or disrupt air flow path causing high air speed less effective in improving heat transfer coefficient.

3

Freezing Capacities of the Vortex Tube and AFPS Package

3.1

Comparisons with Two Benchmarks

The fast freezing capacity of VT can be compared with two benchmarks in terms of the freezing and cooling rates calculated based on heat energy (KJ) removed per minute. This is a more accurate account because calculations based on °C being pulled down per minute from the food items does not take into account latent heat, causing the per unit time change not representative. Note that the calculations below focus on VT itself only and do not consider such real-life factors such as food item sizes and shape factors, container insulation, heat transfer coefficients, etc. 3.1.1 Comparisons with Current Refrigerators

5

The first benchmark is common refrigerators in which a minimum of two hours are necessary to freeze food items based on the tests demonstrated in [10], In addition to three types of meats tested with current refrigerators in [10], water is also compared in the freezing time calculations because thermal properties of food can be extrapolated from that of water [11] and calculated as a function of temperatures [12]. There are many ways to obtain food thermal properties [13], but water serves as a common basis of comparisons with different food items in both theoretical calculations [14] and experimentation results [15]. Part A-1 of Table 3-1 shows the calculated equivalent energy removal rates for the benchmark Calculations based on factory (Exair) specification [16] demonstrate that the VT Model #3215 can remove heat from the meats at around 35 times faster (Part B-1) than the typical refrigerators could perform. Model 3299 can remove heat at around 350 times faster (Part B-2). 3.1.2 Comparisons with Regulatory Standard The second benchmark is based on the US FDA Food Code 2013 requirements in suppressing foodborne illness outbreaks. The Code states that cooked foods in commercial environment should be cooled from 21°C to 5°C in less than four hours [17] as shown in Part A-2 of Table 3-1. Model 3215 and Model 3299 can remove heat at around 300 times (Part B-1) and 3,000 times (Part B-2), respectively, faster than the FDA Food Code demands.

Page

5

3.2 Measurement of the AFPS Package & VT Assembly Operations (Temperature & Pressure) 3.2.1. Experimentation Setup

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 5 of 29

Experiments have been be designed and executed so that fast freezing rate can be demonstrated through the simulated test setup (Figure 3-1). The hardware is made up of such custom-made fixture and standard measurement equipment as mentioned below. (a) Vortex tube – Model 3215 from EXAIR. (b) Simulated AFPS package – An off-the-shelf water-proof (ABS material) box with transparent top lid (Internal dimensions = 73x73x47 mm). (c) Measurement Equipment – Accuracy values 1) Digital Thermometer (2-channel) - ±0.1%+0.5°C 2) Hot-wire aneomometer - ±(5%+0.1ms-1) 3) Digital air pressure gauge - ±2%Full Scale±1digit 4) Digital air flow rate meter – ±1%Full Scale (d) Test Set Up #1 (Fig 3-1) – This setup creates fast freezing of test specimen inside the package container. Compressed air is supplied to 8 bar maximum.

3.2.2

Measurement During Tests – Temperature & Pressure

To measure Tenter (temperature at the inlet hole) related parameters, Air inlet pressures from 4bar to 7bar at a 0.5bar interval are selected for tests. 21 trials were made in total for Tenter. Regarding Tmiddle (temperature in the middle of the package), only 17 trials provide meaningful data because they could bring temperature down below 0°C at Tmiddle. Other data were disregarded.

6

Temperature data are collected along with the corresponding freezing time (as long as necessary to reach a steady state temperature), inlet pressures, and cold mass fraction (it is represented by package internal gauge pressures of 0.3, 0.4, 0.6 and 1.0 kPa). Inlet air flow rate is measured to yield the compressed air power supplied (= air flow rate X pressure). Package internal gauge pressure (above atmospheric pressure) varies from 0 kPa to a maximum which is different for different inlet pressure. It is linearly proportional to cold mass fraction (from 0% to 100%). Therefore, the VT cold mass fraction can be measured indirectly by a digital gauge pressure meter – 0 kPa and the maximum kPa indicate 0% and 100%, respectively. Table 3-2 contains the measured data at various trials. Measurement of data starts when Tenter passes 0°C such that all Tenter have the same starting temperature of 0°C. All temperatures (°C) and pressure (bar) readings are converted to °K and kPa for calculations. No food load is used so that only air temperature is being measured.

Page

6

It is desirable to achieve an optimum balance of the smallest possible pressure input (to minimize compressor loading), the largest possible cold mass fraction (to fully utilize a VT), and the shortest possible time to achieve lowest possible freezing temperature. In fact, four combinations of inlet and internal gauge pressures (5.5/0.3, 6.5/0.4, 7/0.3, 7/0.4 from Trial #6, #15, #18, and #19 respectively) are found to be able to drive Tmiddle down to -10°C.

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 6 of 29

3.2.3

Regression Models of Tenter and Tmiddle and their Validation

Regression models for Tenter and Tmiddle are developed after natural log transformation of the raw data, the final models are representative since the adjusted R2 square are close to 1, standard errors of regression are less than 95%, P values are much less than 5% (Table 3-3), and the residuals of this model are randomly distributed (Figure 3-2).

The models for Tenter and Tmiddle can now be established per Formula (1) and (2), respectively, as follows. Note that the gauge pressure (Pg) is a parameter measured in the middle of the package which is downstream of the VT, and therefore, has no effect on any variable being measured upstream, such as Tenter. Ln Tenter = 5.8641 - 0.0057 • Ln tf – 0.0477 • Ln Pi

(1)

Ln Tmiddle = 5.7911 – 0.0105 • Ln tf – 0.0244 • Ln Pi + 0.0069 • Ln Pg

(2)

The models can also be validated by comparing the freezing efficiency derived from Formula (1) and (2) and that from a theoretical model to be built in Section 4-2 (A). Details will be shown in Section 4.5. 7

3.3

Model Analysis with Test Data

3.3.1

Background Data

To calculate the freezing efficiency of AFPS package - VT assembly, relevant dimensional and other information are first identified and calculated as in Table 3-4. Temperature and other measured data based on the setting of 7 bars and 0.4 kPa (inlet air pressure and internal gauge pressures) are used in this calculation.

3.3.2

Real-Life Factors Compromising The Package Freezing Capacity

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page

(a) Duct length - This “rectangular” duct (simulated APFS package) is too short for developing a fully laminar or turbulent flow. This is an inherent problem because a package always means to be short. In addition, the air inlet and outlet of the package induce sudden expansion and contraction of air flow. They, in turn, cause disruption of flow pattern and turbulence. Currently available mathematical tools do not fit such “short duct”. This factor

7

During fast freezing, air at the inlet, middle of the package, and at the exit ideally have the same temperature when no heat gain occurs inside the package – freezing capacity is maximized. Several real-life factors listed below, however, compromise the fast freezing capacity – causing a penalty. The rest of Section 3 assumes that no other factor contribute to penalty to freezing capacity.

Page 7 of 29

will be ignored in capacity calculation but can be identified in efficiency calculation. (b) Friction factor - The package wall internal surface has roughness and structural features (like ribs or poles) that cause turbulence or disruption of air flow. Friction factor will be more serious if a food item is loaded because it normally has high surface roughness. (c) Wall insulation – The simulated package in the experiment uses a single layer of wall made of ABS material. This allows high heat influx from the environment to the package interior causing higher than desirable Tmiddle and Texit. However, the conceptual design in Figure 2-1 proposes a Flow Path II with which air or vacuum can be used to augment wall insulation. 3.3.3

Heat Gain Analysis of the AFPS Package

To proceed with calculating the heat gain, the Reynolds Number (Re) is determined as 2,470 (transitioning to turbulence flow). After comparing with several formulations, Number (Nu) is best approximated by using the Sieder & Tate formulation for entrance region [19] per Formula (3). Nu = 1.86 • [ Re • Pr / (L/D) ]1/3 • ( μ / μs )0.14 = 20.0927

(3)

Friction factor (f) is now evaluated per Formula (4) below [20]. Friction factor (f) = 1 / [1.82 • Log10(Re) - 1.64 ]2 = 0.3378

(4)

The next step is to work out a Nusselt Number (Nuf) considering the Friction Factor (f) per Formula (5) below and it is found to be 4.08 times higher than the original Nu per Formula (3) [21]. Nuf = ( f/8 ) • (Re - 1000) • Pr / [ 1+ 12.7 • ( f / 8)0.5 • ( Pr2/3 - 1 ) ] = 82.04

(5)

From this Nuf, the heat transfer coefficient of the package is estimated. This information leads to the calculation of the overall heat transfer coefficient (U) of the package considering the thermal resistance of the package interior, the package wall (made of ABS plastic), and the package external environment. U is then found to be 10.79 Wm-2 K-1 per Formula (6) below [22]. 1/U = [ (1 / (hinside) + (1 / Wall Thermal Resistance) + (1 / houtside) ]

8

(6)

The exit air temperature (Texit) is calculated to be at -17.05°C per Formula (7) [23] which is much lower than the measured exit air temperature of -7.2°C. That means the exiting air actually picks up more heat energy than the calculation demonstrates. This is due to short duct length that causes a loss in freezing capacity. ( Texit – Twall ) / ( Tenter - Twall ) = exp [ ( -4 • U • L ) / ( ρ • Uav • Cp • Dh ) ]

(7)

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page

If the insulation is improved by using air or vacuum, the insulation is not simply a single layer of wall but two walls with air or vacuum in between (like Flow Path II). Typical values for gas-filled -2 -1 [24] and vacuum-based [25] are 0.015 and 0.0046 Wm K , respectively. Consequently, loss in freezing capacity will be reduced, causing the air exit temperatures to decrease (approach inlet

8

Since any heat gained inside the package is a loss to freezing capacity, it must be evaluated thoroughly. One approach is to evaluate how much heat must be added to the air flow in order to raise the exit air temperature from -17.05°C to -7.2°C. After several iterations of raising the overall heat transfer coefficient, it is found that the new U should be 44.85Wm-2K-1 which is translated into a heat gain of 36.67W. The conclusion is that the freezing capacity of the VT provided to the package is reduced by 36.67W due to short duct length effect. Table 3-5 below shows the calculated and measure temperatures at four gauge pressure at 7 bar inlet pressures and all four gauge pressures with ABS and vacuum insulation materials. In case of 0.4 kPa, short duct length effect raises the exit temperature from -17.05°C to -7.2°C with ABS insulation as discussed earlier.

Page 8 of 29

temperatures). Table 3-5 below shows the resulted exit temperatures with vacuum insulation. With vacuum insulation, the calculated exit temperature is lowered to within 1°C from the measured enter temperature. This minor difference is due to loss in freezing capacity by the friction factor. Note that if the exit and enter temperatures are the same the loss in capacity will be 0% which is, of course, not feasible.

3.3.4

Freezing Capacity of the Vortex Tube

Based on the factory specifications from EXAIR [16], the required input power of compressed air supplied to the VT Model 3215 is calculated as 4,887.5W (inlet pressure X flow rate). The freezing capacity is equivalent to 293.1W (available from the cold air side of the VT) which is 6% of the input power. This is consistent with the general understanding that VT has a low COP [26]. The rest of the power can be consumed by hot side exhaust for thawing and defrosting, or optionally as energy storage for later use. Calculations related to thawing and defrost are beyond the scope of this Paper. The laboratory in this experiment supplies air at a pressure and at a flow rate of 7 bars and 279 Lm-1, respectively, resulting in 3,255W of input power. A COP of 6% equals to 195.18W which is the maximum available refrigerating or freezing capacity provided to the package. 4

Freezing Efficiencies of the Vortex Tube, AFPS Package, and the Assembly

Freezing efficiency of the whole assembly is calculated based on the efficiency of the VT and the package calculated separately. If, ideally, the package is 100% efficient (no loss), the assembly’s efficiency will be the same as the VT one. If not, the assembly’s efficiency will be reduced by the non-ideal package. 4.1

9

Vortex Tube

In this Paper, COP of a VT and freezing efficiency of an AFPS package equivalently mean the ratio of refrigeration effect to power input and therefore can be used interchangeably. The COP derived from factory specifications per Section 3.3.4 is 6% which is also the theoretical maximum efficiency of the AFPS Package & VT assembly because, ideally, the package has no heat gain and causes no loss of refrigeration effect. 4.2

AFPS Package

4.2.1

Theoretical Model

The theoretical efficiency of an AFPS package is 100% if none of the real-life factors takes effect. In reality, the relationship Texit > Tmiddle > Tenter always holds (due to heat influx). If the package interior is above 0°C (i.e. insulation fails), its freezing capacity will be lost. Consequently, the freezing efficiency will be less than or equal to 0%. Two key relationships become:

Formula (8) below satisfies the above conditions and can be used to calculate the theoretical freezing efficiency. Note that efficiency less than 0% or more than 100% is physically meaningless and will be disregarded. Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

9

Efficiency is 100% if Tenter equals Tmiddle Efficiency is equal to or less than 0% if Tmiddle is at or higher than 0°C, respectively. Page

a) b)

Page 9 of 29

Efficiency = (273.15°K - Tmiddle) / (273.15°K - Tenter)

(8)

By applying data from Table 3-2 to Formula (8), Table 4-1 shows that, at 7 bar inlet pressure, the mean theoretical efficiency of the package alone is 46.77%. The table also shows that the theoretical efficiency at 0.4 kPa is 48.08% which takes into account all the losses.

4.2.2

Analytical Model

The analytical efficiency is calculated by adding the theoretical efficiency and the efficiency loss if short duct length factor is not considered. It is also the difference between the maximum available efficiency and the efficiency losses due to ABS insulation and the friction factor. If vacuum insulation is used, the analytical efficiency will rise such that the only difference with the available freezing efficiency is the efficiency loss due to friction factor (Figure 4-1). 4.3

Freezing Efficiency Maximization - Vacuum Insulation

To maximize the freezing efficiency, wall insulation must be minimized. Using the same logic of analytical calculations in Section 3.3.3 and Section 3.3.4, with vacuum insulation (part of the function of Flow Path II per the conceptual design), the new U becomes 1.38Wm-2K-1 which is translated into a 99.42% of analytical efficiency. In the other words, friction factor consumes only 0.58% or 1.12W of freezing capacity. The air exit temperature is calculated as -20.48°C, slightly above the inlet temperature of -20.8°C, again, due to friction factor as shown in Figure 4-1.

4.4

10

Efficiency of the AFPS Package & VT Assembly – ABS & Vacuum Insulation

The last two columns in Table 4-1 has also shown that the mean efficiency of the whole assembly with ABS and vacuum insulation are 2.80% and 4.66%, respectively, (less than the theoretically calculated 6% efficiency or COP per Section 4.1), after considering only the theoretical efficiency and the efficiency gain as a result of vacuum insulation. 4.5

Validation of the Regression Models for Tenter and Tmiddle

The regression models can also be validated for all the inlet pressures (from 4.5 bars to 7 bars) measured. Table 4-2 shows that the mean theoretical efficiency from Formula (1) is 44.22% (based on the temperature data measured shown Table 3-2). The mean efficiency calculated from the regression models for Tenter and Tmiddle, or Formula (1) and (2), are found to be 45.44%. The results from the regression models approximate to the theoretical one because the standard deviation of the % differences, 11.28%, is considered small. If only the four most desirable settings (Trial #6, #15, #18, #19) are considered, the standard deviation of the % difference becomes 4.06% which, again, confirm the validity of the regression models. The conclusion is that the regression models can reproduce temperature data and reliably predict the freezing efficiency.

Comparisons of freezing time and energy consumption with a typical household freezer (W-80) are made to demonstrate the advantages of using AFPS packages. Figure 4-2 is schematic side-

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

10

Comparisons of Freezing Time and Energy Consumption Between AFPS Package & VT Assembly with a Typical Freezer. Page

4.6

Page 10 of 29

by-side comparison of the freezer and the simulated AFPS Appliance (using Model 3215 VT and AFPS packages same as that in Test Setup #1 inside the compartment). The number of packages is such that their total internal volume equals to the freezer compartment volume (80 Litre). Input and output powers are labelled in the figure. The main reason for choosing Model W-80 freezer from Lianpin is that it has no other function except being a freezer so that the power input will not be diverted for other use during the test. Section 3.3.4 mentioned that four settings of inlet pressure and gauge pressure are found to drive Tmiddle down to -10°C. For the purpose of energy consumption comparison, the setting (5.5 bar / 0.3 kPa) is selected because it translates into the lowest VT power input (2,026W). The compressed air source, assuming with 50% efficiency, needs an energy input of 4,051W in order to provide 2,026W of power.

Table 4-3 has shown that the freezer compressor operates for 1.2 hour to drive down the air temperature inside the compartment from +23.5°C to -10°C. With a rated input power of 100W and refrigerating capacity of 17.38W, totally 75,038J of energy is consumed. Table 4-3 also shows that in the AFPS Appliance, 22 simulated packages have the same internal volume as the freezer. With an input power of 2,026W to the VT and refrigerating capacity of 120.31W (6%) provided to each package, the VT refrigerates the packages one by one, at a rate of 1.29 seconds per package, until all 22 packages have reached -10°C. Assuming that a typical household uses up to 25% (not the whole 100%) of the freezer compartment volume for fast freezing at one time, this is equivalent to the internal volume of 6 AFPS packages. Therefore, AFPS technology consumes only 0.2% (6.97 seconds) and 28,244J (45%) of what the freezer consumes in time and energy, a significant saving from the practical point of view.

5

11

Achievements & Conclusions

Analysis was performed to compare the maximum fast freezing capacities (in terms of energy removal rate in KJ per minute) of 2 off-the-shelf vortex tubes with two benchmarks. Model 3215 and Model 3299 (from Exair) can outperform typical refrigerators by 35 and 350 times, respectively. In addition, these two models can surpass the relevant FDA requirements by 350 and 3,000 times, respectively.

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page

Theoretical and analytical approaches in evaluating freezing efficiencies are performed on the VT, the package itself, and the whole assembly at the setting of 7 bar inlet pressure at all four gauge pressures. Efficiency losses contributed by short duct length, wall insulation, and friction factor have been evaluated. Efficiency is found to be maximized if vacuum insulation is used to reduce heat influx into the package. In addition, the regression models developed for the Tenter and Tmiddle are validated by comparing with the theoretical model in predicting package efficiency reliably. Finally, time and energy consumption of the proposed customized storage are found to be superior to that of a typical household freezer.

11

Experimentation was set up and executed to acquire temperature, pressure, cold mass fraction, and inlet air flow rate data of the AFPS package & VT assembly at 21 settings. Regression models for Tenter and Tmiddle are then developed to evaluate AFPS package freezing efficiency in subsequent section. Analytical model is used to evaluate the freezing capacities of the VT and the package after considering short duct length, duct friction factor, and wall insulation.

Page 11 of 29

This Paper has provided a conceptual design of customized storage of individual food item, known as Adaptive Food Preservation System (AFPS) Appliance. Individual storage allows fast freezing at targeted food item on need basis, strengthen overall thermal insulation, and alleviate the impact of user behavior. This, in turn, helps to improve food storage quality and energy efficiency. In engineering design of the Appliance, various models of VT can be selected from off-the-shelf for different food categories. Customized design of VT can be considered to best fit the operations of the Appliance. Future work should be carried out to further develop and verify the concept of the AFPS Appliance – Calculations related to thawing and defrost functions, experimentations and development of regression models with food materials, analysis of Appliance’s energy consumption for compliance to standards such as the Energy Labelling scheme, IEC 62552, etc. References

[2]

Priyanka Prasad, Anita Kochhar, Active Packaging in Food Industry: A Review, IOSR Journal of Environmental Science, Toxicology and Food Technology (IOSR-JESTFT), Volume 8, Issue 5 Ver. III (May. 2014), PP 01-07

[3]

Melo Cláudio, Thermal Insulation of Household Refrigerators: Perspectives and Evaluation Methods, Research Laboratories for Emerging Technologies in Cooling and Thermophysics, Federal University of Santa Catarina, Sectorial Panel: Thermal Insulation for the White Line, Keynote 1, pg 21, August 2012.

[4]

Guadalupe Huelsz, Fabrisio Gomez, Miguel Pineirua, Jorge Rojas, Mauricio de Alba, Victo Guerra, Evaluation of refrigerator/freezer gaskets thermal loads, HVAC & R Research, 2011

[5]

Erik Björk. Energy Efficiency Improvements in Household Refrigeration Cooling Systems, Doctoral Thesis, Department of Energy Technology, Royal Institute of Technology Stockholm, Sweden, pg 72-77, 2012.

[6]

Geppert Jasmine, Modelling of domestic refrigerators’ energy consumption under real life conditions in Europe, Institute of Agricultural Engineering, Rheinischen Friedrich-WilhelmsUniversität, pg 27-28, May 2011.

[7]

Geppert Jasmine, Modelling of Domestic Refrigerators’ Energy Consumption Under Real Life Conditions in Europe, Institute of Agricultural Engineering, Rheinischen FriedrichWilhelms-Universität, pg 28-29, May 2011

[8]

Polihronov Jeliazko G. & Straatman A., The Maximum Coefficient of Performance (COP) of Vortex Tubes, Canadian Journal of Physics, Vol 93, Issue 11, p1279, November 2015.

[9]

Cleland A.C. & Ozilgen S., Thermal design calculations for food freezing equipment – past, present, and future, International Journal of Refrigeration, Vol. 21, No. 5, pp. 361, August 1998.

[10]

Anderson Brent A., Suna Spring, Erdogdub Ferruh, Singh, & Paul R., Thawing and freezing of selected meat products in household refrigerators, International Journal of Refrigeration 27, pg 67-68, 2004.

[11]

Onia N., & Ivan E., Estimation of the specific heat and thermal conductivity of foods only by their classes of substances contents(water, proteins, fats, carbohydrates, fiber, and ash),

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

12

12

Ranken M.D., Handbook of Meat Product Technology, Blackwell Science, Chapter 6, pg 100, 2000.

Page

[1]

Page 12 of 29

Scientifical Researches, Agroalimentary Processes and Technologies, Volume XI, No. 1, pg 218, 2005.

[13]

Nesvadba P., Thermal Properties of Unfrozen Foods, Rao M.A., Rizvi Syed S.H., & Datta Ashim K. (ed.), Engineering Properties of Foods, CRC Press, pg 151-152, 2005.

[14]

Fricke Brian A. & Becker Bryan R., Calculation of food freezing times and heat transfer coefficients, ASHRAE Transactions: Research, Report RP-1123, pg 147-149, 2004.

[15]

Pham Tuan Q., Trujillo J. Francisco, Davey Lucy M., & McPhail Neil, Cooling curves for the preliminary design of beef chillers, International Journal of Refrigeration 32, pg 1944-1953, 2009.

[16]

Exair Corporation, Cabinet Cooler© System, Exair Corporation, Cincinnati, Ohio, (www.exair.com), pg 154-157, 2014.

[17]

Elsayed Amr O & Hariri Abdulrahman S, Effect of Condenser Air Flow on the Performance of Split Air Conditioner, World Renewable Energy Congress 2011 – Sweden, pg 2141, May 2011.

[18]

Owen J. McCarthy, Thermal Properties of Foods, 2014 ASHRAE Handbook – Refrigeration, American Society of Heating, Refrigerating and Air-Conditioning, Chapter 19, pg 19.2 – 19.4, 2014.

[19]

James R Welty, Charles E Wicks, Robert E Wilson, Gregory L Rorrer, Fundamental of Momentum, Heat & Mass Transfer, John Wiley & Sons, Inc., Chapter 20, pg 307, March 2000.

[20]

James R Welty, Charles E Wicks, Robert E Wilson, Gregory L Rorrer, Fundamental of Momentum, Heat & Mass Transfer, John Wiley & Sons, Inc., Chapter 19, pg 291-293, March 2000.

[21]

John H Lienhart IV and John H Lienhart V, Heat Transfer Textbook, Phlogiston Press, Chapter 7, pg 372, 2011.

[22]

John H Lienhart IV and John H Lienhart V, Heat Transfer Textbook, Phlogiston Press, Chapter 7, pg 374, 2011.

[23]

James R Welty, Charles E Wicks, Robert E Wilson, Gregory L Rorrer, Fundamental of Momentum, Heat & Mass Transfer, John Wiley & Sons, Inc., Chapter 19, pg 291-293, March 2000.

[24]

Griffith Brent T., Arasteh Dariush, & Türler Daniel, Energy Efficiency Improvements for Refrigerator/Freezers Using Prototype Doors Containing Gas-Filled Panel Insulating Systems, Lawrence Berkeley Laboratory, Proceedings of the 46th International Appliance Technical Conference, pg 5, June 1995.

[25]

Dow Corning® High Performance Insulation brochure, Vacuum Insulation Panel, Form No. 62-1556B-01 EU, www.dowcorning.com/HPInsulationBrochureEU, (Last accessed on 2016/06/01), pg 2, 2013.

[26]

Karthik S., Design & Computation of COP of Vortex Tube, International Journal of Scientific and Engineering Research, Volume 6, Issue 4, pg 437, April 2015.

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

13

13

Owen J. McCarthy, Thermal Properties of Foods, 2014 ASHRAE Handbook – Refrigeration, American Society of Heating, Refrigerating and Air-Conditioning, Chapter 19, pg 19.1, 2014.

Page

[12]

Page 13 of 29

AFPS Package (VT is not shown) AFPS Appliance

AFPS Package

AFPS Package

AFPS Package

AFPS Package

AFPS Package

Both cold and hot air generated by Vortex Tube are circulated back to the air compressor.

14

Air for freezing or thawing Along Flow Path I

Cold Air Along Flow Path II Cold Air for Low Temperature Maintenance (Evaporator is not shown)

Refrigerant Compressor

Vortex Tube (VT) – can be many with different capacities. Compressed Air For Fast Freezing & Thawing

Cold air (or refrigeration) is NOT provided to the outside of the AFPS packages and the associated tubings.

Compressed Air Source

Page

14

Fig 2-1: Conceptual design of the AFPS Appliance. In an AFPS package, Flow Path I is mainly for fast freezing, thawing, and defrosting. Flow Path II is for long-term low temperature maintenance.

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 14 of 29

Air Inlet Pressure Gauge Probe For Air Speed

Probe For Tmiddle

Vortex Tube

Probe For Tenter Air Flow Rate Meter

Simulated APFS Package

Anemometer

Digital Thermometer

Figure 3-1 – Test Set Up #1. 15

Residual plots for Tenter. Inlet Pressure - (Ln) Residual Plot 0.01

0.005

0.005

0 0.0000 -0.005 -0.01

2.0000

4.0000

6.0000

8.0000

Residuals

Residuals

Freezing Time (Ln) Residual Plot 0.01

0 5.6000 -0.005 -0.01

Freezing Time (Ln)

5.8000

6.0000

Inlet Pressure -

6.2000

6.4000

6.6000

Atm Pressure (kPa) (Ln)

Residual plots for Tmiddle. Freezing Time (Ln) Residual Plot

-0.005

0.005

10.0000

Time (Ln)

15.0000

20.0000

0.005 0 0.0000 -0.005

5.0000

10.0000

15.0000

Bar (Ln)

20.0000

Residuals

5.0000

Residuals

Residuals

0 0.0000

Gauge Pressure (Ln) Residual Plot

Inlet Pressure (Ln) Residual Plot

0.005

0 0.0000 -0.005

5.0000

10.0000

15.0000

20.0000

kPa (Ln)

Page

15

Fig 3-2: Residual plots for freezing time, inlet pressure, and gauge pressure indicates full randomness for both Tenter and Tmiddle.

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 15 of 29

Available Freezing Efficiency (Provided by VT) (=100% or 195.18W)

Analytical Efficiency (Insulation = ABS Materials) = Eana (= 66.86% or 130.51W)

Efficiency Losses Due to ABS Vacuum & Friction Factor ( = 33.14% or 64.67W )

Analytical Efficiency (Insulation = Vacuum ) = Evac (= 99.42% or 194.05W)

Theoretical Efficiency ( = 40.08% or 93.84W )

T exit = -7.2 C

Measured

Efficiency Loss if Duct Length Factor Is Considered ( = 18.79% or 36.67W )

Efficiency Loss Due to Friction Factor ( = 0.58% or 1.12W )

Efficiency Gain Due to Using Vacuum Insulation (= 32.56% or 63.55W)

-17.05 C

-20.30 C

Calculated – ABS

Calculated - Vacuum

T enter = -20.8 C

Measured

Figure 4-1: Relationships between various efficiencies and the losses at the 7 bars & 0.4 kPa setting along with the achieved temperatures.

Page

16

16

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 16 of 29

Electrical Power Input

Available Refrigerating Capacity

100 W

17.38 W Compartment of the Freezer

Refrigerant Compressor

Freezer – Model W-80 Simulated AFPS Appliance Electrical Power Input

Compressed Air Power Input

Available Refrigerating Capacity

2,026 W

193.35 W

4,051 W

Package Package

Compressed Air Source

Package

Vortex Tube

17

Package Package Package

Page

17

Fig 4-2: Schematic layout of Model W-80 freezer vs an AFPS Appliance in operations in comparing time and energy consumption.

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 17 of 29

Table 1-1: Factors that compromise the effectiveness of fast freezing, low temperature storage, and thawing, causing direct impact on food quality and energy efficiency.

Current thermal insulation system is not the most effective in keeping away the thermal loads from the environment and the refrigferator's own devices: 1. There is only one layer of insulation between food items and their ambient environment. 2. Door seal is the weakest link since heat flux through door seal can be ten times that of those through the wall [3]. Also, the ambient heat influx into a refrigerator's compartment through door seal varies between 10% to 30% [4]. 3. Temperatures of the ambient, condenser, compressor, etc have direct impact on compartment temperature stability and profile [5]. Reason for impact on food quality - food storage temperature cycles more often and with a larger amplitude; Reason for impact on energy efficiency - compressor has to run more often and longer time to remove heat from food, hence uses more energy. Temperature operations like freezing, fas freezing, chilling, thawing, or defrosting apply indiscrimately to all food items within a compartment (chilling or freezing). No finer segragation is possible. 1. Temperature operations must be executed to the whole designated compartment even though not all food items in a compartment need the same treatment at the same time. 2. Freezing and cooling compartments are normally separated so that the compartment space compete against each other and cannot be used interchangeably. 3. Air ciculation speed is limited so heat transfer in cooling or freezing is not the most efficient, especially when flow path is obstructed by food stacking up on each other. Reason for impact on energy efficiency - Unnecessary use of energy is not avoidable due to "large änd non-segregated compartment".

18

Page

18

User behaviors may compromise energy consumption and the protection that refrigerators intend to provide to food items due to the followings [6]: 1. Frequent door open and close cycles. 2. Excessive food load, improper food placement, and load filling level - block or disrupt cold air circulation patten, etc [6]. 3. Food temperature too high immediately before storage in refrigerator - raise thermal loads on food loads and lower energy efficiecy [7]. Reason for impact on food quality - Unstable compartment temperature and storage temperature higher than desirable may harm food quality. Reason for impact on energy efficiency - More frequent and longer compressor operating cycles.

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 18 of 29

Table 1-2: How food storage customization can resolve or alleviate issues per Table 1-1.

Thermal Insulation System With the customized storage installed inside a refrigerator, the storage itself serves as the primary thermal insulation while the cabinet wall and door seal actually becomes the secondary insulation. Customized food storage is dedicated for each food item which then enjoys the benefit of double thermal insulation. Food temperature stability is better maintained even in fluctuating ambient temperatures or other condition variations. Temperature Operations in the Compartment Since refrigeration is provided within the customized storage only, waste on refrigerating capacity and energy will be minimized. (1) Temperature operation like freezing, cooling, defrosting, or thawing can be applied specfic to the food items on demand basis - no waste on other food items. (2) Space of each customized storage is small (only enough to accommodate a piece of food). This helps to minimize the time of any temperature operations, like freezing or thawing and to reduce temperature cycling. (3) When a refrigerator door is opened, cold air will not come out as we normally see today. All the cold air is confined inside the customized storage, greatly enhancing energy efficiency.

User Behaviors (1) Item-by-item food storage eliminiates food stacking up on each other, air cirulation path blockage or disruption. Each food item has its own dedicated air flow path inside the storage. (2) With customized storage, food retrieval can be so specific that irrelevant food items will not be disturbed at all because of segregated storage, minimizing temperature fluctuation on food.

Page

19

19

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 19 of 29

Table 3-1: Freezing rate calculations based on various Exair VT models on different benchmarks. Food Property Data [18] Salmon Starting temp

Beef

Chicken

Water

Units

5

5

5

15

°C

-18

-18

-18

-18

°C

76%

72%

66%

100%

%

0.252

0.22

0.202

0.2

Kg

Specific heat capacity above freezing point

3.68

3.53

4.34

4.187

KJ Kg-1°K-1

Latent heat of water at freezing point

255

239

220

334

KJ / Kg

Specific heat capacity below freezing point

2.17

2.11

3.32

2.108

KJ Kg-1°K-1

Freezing point of water contents

-2.2

-1.7

-2.8

0

°C

79.07

65.35

56.48

Steady State Temp Water Contents Mass of Specimens

Part A-1: Freezing rates per the tests executed in [10] Total heat released from +5°C to -18°C

KJ Not Applicable

Equivalent energy Removal Rates (Average time to remove heat from food until -18°C is reached)

0.5342

0.5066

0.4483

KJ minute-1

1 Part A-2: Cooling rate requirements from FDA Food Code From 21°C to 5°C in four hours

0.0667

Equivalent energy removal rate during the 21°C to 5°C drop in 4 hr

0.0618

0.0518

0.0584

0.0667

°C minute-1

0.0579

KJ minute-1

Part B-1: Heat Removal Performance of Model 3215 Vortex Tube

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 20 of 29

Energy removal rates (from +5°C until -18°C is reached)

17.6

17.6

33

35

284

339

301

304

None

179.2

179.2

179.2

179.2

KJ minute-1

335

354

Number of times the VT removes heat faster than the tests done in [10] Numner of times the VT removes heat faster than the Food Code demands

17.6

17.6

39 Not Applicable

KJ minute-1 None

Part B-2: Heat Removal Performance Model 3299 Vortex Tube Energy removal rates (from +5°C until -18°C is reached) Number of times the VT removes heat faster than the tests done on [10] Numner of times the VT removes heat faster than the Food Code demands

2,899

3,462

400 Not Applicable 3,066

3,097

None None

2

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 21 of 29

Internal Gauge Pressure (kPa)

Inlet Pressure (kPa)

Trial #

Freezing Temp (K) at Package Inlet

Freezing Time (0 deg to Lowest)

Inlet Pressure (Bar)

Table 3-2: Raw test data in operating the simulated test setup – Data from 21 trials are shown on the left table for Tenter and data from 17 trials are shown on the right table for T middle.

1

260.15

245.0

298.7

0.1

4.0

2

260.15

338.7

298.7

0.3

4.0

3

261.75

182.0

298.7

0.4

4.0

4

261.65

286.2

298.7

0.6

4.5

5

256.15

272.4

348.7

0.4

4.5

6

258.15

236.2

348.7

0.6

5.0

7

255.15

177.8

398.7

0.3

5.0

8

257.65

259.8

398.7

0.4

5.0

9

256.15

195.6

398.7

0.6

5.5

10

253.15

359.3

448.7

0.3

5.5

11

254.15

238.4

448.7

0.4

5.5

12

254.85

201.6

448.7

0.6

6.0

13

252.65

155.3

498.7

0.3

6.0

14

253.65

345.0

498.7

0.4

6.0

15

256.15

156.1

498.7

0.6

6.5

16

252.65

224.2

548.7

0.3

6.5

17

256.15

19.4

548.7

0.4

6.5

18

254.65

204.9

548.7

0.6

7.0

19

252.15

229.5

598.7

0.3

7.0

20

252.35

185.5

598.7

0.4

7.0

21

253.65

102.4

598.7

0.6

1

Page

1

4.0

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 22 of 29

Internal Gauge Pressure (kPa)

Inlet Pressure (kPa)

Freezing Time (0 deg to Lowest)

Trial #

Freezing Temp (K) at Package Middle

265.15

348.4

348.7

0.4

6

267.65

197.0

348.7

0.6

7

266.15

153.0

398.7

0.3

8

267.65

170.5

398.7

0.4

9

269.15

125.0

398.7

0.6

10

262.65

299.0

448.7

0.3

11

264.15

239.5

448.7

0.4

12

265.15

194.0

448.7

0.6

13

264.15

174.4

498.7

0.3

14

263.65

262.4

498.7

0.4

15

265.15

228.5

498.7

0.6

16

264.15

178.0

548.7

0.3

17

263.15

409.0

548.7

0.4

18

265.15

184.0

548.7

0.6

19

263.15

199.7

598.7

0.3

20

263.15

245.5

598.7

0.4

21

264.35

131.6

598.7

0.6

2

Page

2

5

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 23 of 29

Table 3-3: Validation of the regression models for Tenter and Tmiddle. Regression Results for T enter

Coefficients

Adjusted R Square

0.8338

Intercept (Ln)

Std Error of Regress

0.0048

Time (Ln)

0.010%

within the 95% prediction interval. Inlet Pressure (Ln)

Regression Results for T middle 0.8241

Intercept (Ln)

Std Error of Regress

0.0029

0.006%

5.8641

0.0000

-0.0057

0.0081

-0.0477

0.0000

Coefficients

Adjusted R Square

within 95% prediction interval.

P Values

P Values

5.7911

0.0000

Time (Ln)

-0.0105

0.0005

Inlet Pressure(Ln)

-0.0244

0.0000

0.0069

0.0196

Gauge Pressure (Ln)

Page

1

1

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 24 of 29

Table 3-4: Dimensional and specification data of the simulated package and the selected VT model used for the analytical model at the particular setting. Temp (Air entering the package) =

-20.8deg C

252.35deg K

Inlet Pressure

Temp (Air at center of the package) =

-10.0deg C

263.15deg K

Guage Pressure

Temp (Package wall - Average) =

-0.15deg C

273.00deg K

Speed (Air - Entering - Average) =

12.7m s-1

Temp (Air exiting the package) =

-7.20deg C

265.95deg K

23.0deg C

296.15deg K

Temp (Air - Room - Average) =

Package (Duct) size = Inside Surface Hole Diameter Hole Radius

a (width) 73

49

0.073

0.049

11.0 mm 0.0055 m

b (height)

L (length)

a x b x L (area)

73 mm 0.073 m

3,577

7

Bar

0.4

kPa

Wall Thickness (Average) mm2

3mm

0.003577 m2

0.003m

Area (inlet hole) =

9.5033E-05 m2

Area (outlet hole) =

9.5033E-05 m2

1

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 25 of 29

Table 3-5: Calculated and measured temperatures at different settings and with insulation materials. Reasons for the differences are also mentioned. Internal Gauge Pressures @ 7 Bar Inlet Pressure

Insulation Materials

Temperatures

0.3 kPa

0.4 kPa

0.6 kPa

Reasons for the Temperature Differences

1.0 kPa

ABS

T exit (Measured)

-5.90

-7.20

1.30

1.90

ABS

T exit (Calculated)

-17.12

-17.05

-15.78

-13.37

Vacuum

T exit (Calculated)

-20.48

-20.30

-19.00

-16.73

ABS

T enter (Measured)

-21.00

-20.80

-19.50

-17.30

Short Duct Length Wall Insulation

Friction Factor

Page

1

1

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 26 of 29

Table 4-1: Efficiencies and capacities of the package at 7 bar inlet pressure and four kPa levels. Available Freezing Settings (Inlet Capacity / Gauge (W) Pressure) Provided by VT

%

7Bar/0.3kPa

195.18

7Bar/0.4kPa

Freezing Capacity Loss due to Short Duct Length

Freezing Analytical Capacity Theoretical Efficiency % Loss due to Efficiency % (Vacuum Friction Insulation) Factor

Efficiency Gain % Due to using Vacuum Insulation

AFPS -VT Assembly Efficiency % (ABS Insulation)

AFPS -VT Assembly Efficiency % (Maximum)

Analytical Freezing Capacity (W)

%

100%

132.47

######

39.53

20.25%

47.62%

99.43%

1.12

0.57%

61.58

######

2.86%

4.75%

195.18

100%

130.51

######

36.67

18.79%

48.08%

99.42%

1.12

0.58%

63.55

######

2.88%

4.84%

7Bar/0.6kPa

195.18

100%

133.77

######

61.41

31.47%

45.13%

99.45%

1.08

0.55%

60.33

######

2.71%

4.56%

7Bar/1.0kPa

195.18

100%

137.95

######

47.70

24.44%

46.24%

99.47%

1.04

0.53%

56.19

######

2.77%

4.50%

46.33 23.74%

46.77%

99.44%

1.09

0.56%

60.41 ######

2.80%

4.66%

1.34%

0.02%

0.04

0.02%

0.08%

0.16%

Mean Standard Deviation

133.68 ###### 3.15

1.61%

11.09

%

5.68%

%

3.11

%

1.60%

1

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 27 of 29

Table 4-2: Comparisons of the theoretical efficiency, from Formula (1) with the efficiency calculated from the regression models or Formula (2) and (3). Trial #

Efficiency (%) Theoretical Approach

T enter

T middle

Efficiency (%) - Based on Regression Models

% Differences (All Trials)

% Differences (See Note)

5

47.06%

257.99

265.22

52.28%

-11.10%

6

36.67%

258.56

267.56

38.32%

-4.50%

7

38.89%

256.65

266.13

42.55%

-9.41%

8

35.48%

256.37

266.35

40.51%

-14.17%

9

23.53%

257.14

267.97

32.38%

-37.61%

10

52.50%

254.18

263.50

50.85%

3.15%

11

47.37%

255.02

264.64

46.93%

0.92%

12

43.72%

255.62

265.96

40.99%

6.25%

13

43.90%

254.05

264.32

46.23%

-5.31%

14

48.72%

253.18

263.71

47.29%

2.92%

15

47.06%

254.66

264.82

45.03%

4.30%

16

43.90%

252.35

263.65

45.68%

-4.05%

17

58.82%

256.07

261.87

66.04%

-12.27%

18

43.24%

253.09

264.81

41.58%

3.86%

3.86%

19

47.62%

251.24

262.77

47.38%

0.50%

0.50%

20

48.08%

251.79

262.72

48.85%

-1.61%

21

45.13%

252.99

265.18

39.52%

12.42%

Mean

44.22%

45.44%

-3.87%

1.04%

Std Dev

7.69%

7.27%

11.28%

4.06%

-4.50%

4.30%

1

Page

1

Note: Only Trial #6, #15, #18, and #19 are selected because these settings can drive down T enter to -10 degrees C.

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 28 of 29

Table 4-3: Comparisons of time and energy consumption of a typical freezer and AFPS Packages. Equipment Types

Refrigerant Compressor (of Freezer)

AFPS Package & VT (of an AFPS Appliance)

Power Input To Compressed Air Available Efficiency (%) Of the Equipment Power Input Refrigerating the Equipment (W) Capacity (W)

100

NA

No of Unit

Unit Freezing Time (s)

17.38

17.38%

1

4,320

1.29

4,051

2,026

120.31

50.00%

22

4,051

2,026

120.31

50.00%

21

4,051

2,026

120.31

50.00%

4,051

2,026

120.31

4,051

2,026

4,051

Total Freezing Total Energy % of Freezer Time (s) Consumption (J) Time (from 20 Consumption to -10 deg C)

4,320

75,083

% of Freezer Energy Consumption

100%

100%

28.49

115,426

0.66%

154%

1.29

27.20

110,183

0.63%

147%

20

1.29

25.90

104,940

0.60%

140%

50.00%

19

1.29

24.61

99,697

0.57%

133%

120.31

50.00%

14

1.29

18.14

73,483

0.42%

98%

2,026

120.31

50.00%

13

1.29

16.85

68,240

0.39%

91%

4,051

2,026

120.31

50.00%

12

1.29

15.55

62,997

0.36%

84%

4,051

2,026

120.31

50.00%

11

1.29

14.26

57,754

0.33%

77%

4,051

2,026

120.31

50.00%

7

1.29

9.08

36,782

0.21%

49%

4,051

2,026

120.31

50.00%

6

1.29

17.79

31,540

0.18%

42%

4,051

2,026

120.31

50.00%

5

1.29

6.49

26,297

0.15%

35%

4,051

2,026

120.31

50.00%

2

1.29

2.61

10,568

0.06%

14%

4,051

2,026

120.31

50.00%

1

1.29

1.31

5,325

0.03%

7%

Andrew Tsang, K.C. Yung (For the International Journal of Refrigeration)

Jan 2017

Page 29 of 29