Design of Heat-Transfer Media Components for Retail Food

Subscriber access provided by INDIANA UNIV PURDUE UNIV AT IN

Article

Design of heat transfer media components for retail food refrigeration Apurva Samudra, and Nikolaos Sahinidis Ind. Eng. Chem. Res., Just Accepted Manuscript • DOI: 10.1021/ie303611v • Publication Date (Web): 31 May 2013 Downloaded from http://pubs.acs.org on June 13, 2013

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a free service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are accessible to all readers and citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Industrial & Engineering Chemistry Research is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Industrial & Engineering Chemistry Research

Design of heat transfer media components for retail food refrigeration Apurva Samudra and Nikolaos V. Sahinidis∗ Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA E-mail: [email protected]

Abstract High levels of emissions of ozone-depleting substances and greenhouse gases from supermarkets around the world can be attributed to leakage of hydroflurocarbons (HFCs) and generation of electric power required for retail food refrigeration. Indirect refrigeration loops are ideally suited for reductions mandated by regulation standards as they reduce leakage and can lead to significantly lower total energy consumption. Hence, the design and identification of fluids that boost refrigeration performance while meeting safety and environmental guidelines is of considerable interest. Using a recently developed molecular design methodology 1 as our starting point, in this work, we develop a model and search technique for identifying ideal secondary refrigerants. Accurate property models that predict characteristic refrigerant properties guide the search for molecules. We also include environmental and safety metrics (biodegradability and lethal concentration (LC50 )), along with performance criteria for heat transfer efficiency to analyze the candidate molecules. We identify a number of novel molecules as well as known compounds that have not been used as secondary refrigerants. ∗

To whom correspondence should be addressed

1 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

1 Introduction Retail food stores (supermarkets) are defined as stores that offer a wide variety of groceries, meats, and produce with annual sales greater than $2 million. There are over 36,000 such stores in the USA alone. Supermarkets stock numerous perishable products in easy-to-access shelves and display cases. Large refrigeration loads are required to maintain the products at a safe temperature. The energy required for refrigeration makes up about half of the total supermarket power consumption 2 while emissions related to their power consumption sum up to 85% of the total global warming effect of supermarkets. 3 An average US supermarket leaks about 875 pounds of refrigerant per year, equivalent to 1,556 metric tons of CO2 . Apart from these direct emissions, average supermarket electricity consumption leads to 1,383 metric tons of CO2 eq emissions annually. 4 Due to the increasing size of supermarkets in US and Europe along with increasing proliferation of hypermarkets in the rest of the world, 5 their greenhouse gas emissions have become a major concern. In response, the Environmental Protection Agency (EPA) has created a voluntary partnership with the supermarket industry known as the Green Chill Advanced Refrigeration Partnership 6 to foster technology and practices that lower emissions of ozone-depleting substances (ODSs) and greenhouse gases (GHGs). The direct expansion (DX) loop is the dominant technology in retail refrigeration and used in around 70% stores in USA. In a DX system, a two-phase refrigerant cycle is used to cool display cases and chillers in the sales area. Indirect refrigeration schemes or secondary refrigeration loops (SLs) consist of a primary two-phase refrigerant that chills a heat transfer fluid which, in turn, is circulated to cool the display cases. SL systems have been identified as the least emission alternative for DX loops, even with HFC refrigerants in their primary loop. 7 Wang et al. present a detailed review of SL systems, including mechanical design aspects and particulars of primary refrigeration cycles. 8 A variety of fluids have been employed as single-phase heat transfer media, 9–11 along with a few natural refrigerants like R-744 (CO2 ) and R-717 (NH3 ) that are used especially in Europe. 12,13 SLs provide better control over the display case temperatures, a feature highly desirable due to stringent regulations on food temperatures. Many North American supermarket chains have 2 ACS Paragon Plus Environment

Page 2 of 28

Page 3 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


adopted indirect systems as future alternatives. 14 Naturally, development of secondary refrigerant schemes to boost efficiency of retail food refrigeration and curtail its environmental impact has been identified as an important research objective. 15,16 Computer-aided molecular design (CAMD) has been previously employed to identify refrigerants and heat transfer fluids 17–30 and specifically secondary heat transfer fluids. 31 These works employ enumeration algorithms or mixed-integer nonlinear programming (MINLP) models to solve the CAMD problem. In contrast, we employ mixed-integer linear programming (MILP) techniques over smaller subproblems in a decomposition framework. As a result, we are able to obtain solutions far more efficiently and consequently explore much larger search spaces. Also in contrast to prior work, in the current paper, we explicitly model biodegradability and toxicity of candidate heat transfer fluids. We formulate the problem of finding ideal secondary refrigerants as the problem of matching a set of property targets. These targets are based on safety and efficiency criteria for refrigeration cycles in supermarkets. We also set targets to minimize the environmental impact of possible fluids. A variety of families of heat transfer fluids are identified by the proposed approach, including industrial fluids and novel molecules. The primary contributions of the present work are two fold. First, we develop a novel optimization model for designing secondary refrigerants in a way that accounts for thermal and environmental properties. Second, thanks to the unprecedented speed of the proposed algorithmic framework for the solution of the optimization model, we identify a large number of potential new secondary refrigerants. The remainder of this paper is structured as follows. In Section 2, we present the details of indirect refrigeration loops, their features, and their advantages. The formulation of the design problem as property targets based on process constraints and environmental factors is presented in Section 3. We describe our general framework for molecular design in Section 4. In Section 5, we tailor this framework to the problem of designing heat transfer fluids by specifying appropriate property prediction methods, performance and environmental criteria. We discuss the results and observed trends in Section 6. Finally, in Section 7, we provide conclusions from this work.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

2 Indirect refrigeration system

Figure 1: Supermarket cooling system with direct expansion refrigeration

The schematics of a simple DX loop are shown in Figure 1. At each fixture, i.e., display case or cooler, the evaporating refrigerant creates the cooling effect. The refrigerant is then pumped back to the machine room for compression and condensation. Typical DX loop refrigerants are the hydrofluorocarbons (HFCs) R404, R-502, and R-422. As the fluid is pumped throughout the store, the refrigerant charge, i.e., amount of refrigerant in active circulation, is high for the DX cycle. The high number of two-phase components and connections in the loop are responsible for typical leakage rates of 15% to 35% per year. These high leakage rates coupled with large total charge of hydrofluorocarbon refrigerants lead to heavy emissions of refrigerant from the DX system. The need to replace retail food refrigerants by efficient and environmentally friendly fluids has been a priority in recent years. 15 Indirect refrigeration eliminates the need to pump HFC refrigerant throughout the store by circulating a heat transfer medium between the display cases and a primary refrigeration cycle. In 4 ACS Paragon Plus Environment

Page 4 of 28

Page 5 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 2: Supermarket cooling system with secondary heat transfer loop

the SL scheme, refrigeration is split into a primary and a secondary loop as shown in Figure 2. The primary loop consists of a typical two-phase refrigeration cycle housed in a central machine room. The heat transfer fluid, also known as secondary refrigerant or secondary working fluid, is cooled by the primary cycle. It is then pumped throughout the store to cool the display cases. We summarize the advantages of secondary refrigeration loops over DX systems below: 7,32 • reduction in primary refrigerant charge by 50% to 90% • reduction in HFC emissions by 44% to 99% • lower leakage rates due to removal of two-phase connections in the store • difficult-to-handle but effective primary refrigerants, such as ammonia and HCs can be used • simplified piping, fewer components, and easy maintenance • higher efficiency via compartmentalization • better temperature control in display cases due to single phase operation 5 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

• shorter supply and return lines. Despite such benefits, the adoption of SL in supermarkets has been limited. Increase in the capital costs by 10% to 25% for the implementation of new secondary loops or retrofits of primary loops have been prohibitive. The market penetration of secondary loop systems ranges from 3% to 5% of the total number of stores. Previously used secondary fluids include propylene glycol or ethylene glycol with water, potassium formate or acetate brine, calcium chloride brines, ethanol, methanol, glycerol, liquid CO2 , hydrofluroethers, straight and branched alkanes, cyclohexene and cyclohexane, diethylbenzene, and polydimethylsiloxane. Many industrial formulations involve emulsions of these individual components with water. Very few of these fluids can meet target environmental criteria for indirect loops and provide high process efficiency simultaneously. 11 The low cost of R744 provides low operating expenses but natural refrigerants still suffer from challenges like high operating pressures, accumulation hazards, and much higher capital expenditure leading to their limited success as secondary fluids. Another major hurdle in widespread application of indirect refrigeration is the increased power consumption for pumping the heat transfer media, especially at lower temperatures. The pumping power required for current secondary fluids translates to higher energy consumption and leads to high GHG emissions (0.65 kg CO2 per kWh). Energy consumption of advanced secondary loop systems can be reduced by up to 15%, compared to a similar DX system, by employing features such as secondary fluid defrosters and redesigned display shelves. However, the choice of secondary fluid is still the most critical factor in the power demands of refrigeration. A specially designed secondary refrigerant can significantly improve the efficiency of retail food refrigeration. An ideal secondary refrigerant must possess excellent heat transfer ability characterized by its specific heat and thermal conductivity. It must also be liquid over a large operating range, while facilitating safe and stable operation of the refrigeration cycle. The coolant must not be an ozone-depleting substance according to the Montreal protocol and it must have low global warming potential according to the Kyoto protocol. In the next section, we formulate these requirements as a series of property targets.


Page 6 of 28

Page 7 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


3 Problem formulation Improvements in mechanical design of coolers, display cases, and piping layouts can increase the efficiency of refrigeration cycles but the choice of heat transfer media greatly affects the overall efficiency. Properties of the working fluid that affect the safe, stable, and efficient operation of the secondary refrigeration loop are crucial to the application of the fluid. Thus, a systematic approach to pick effective refrigerants needs to address the following factors: • Performance: Efficiency, total equivalent warming impact (TEWI), capital costs • Safety: Toxicity, flammability, corrosivity • Impact: Global warming potential, ozone depletion, bioconcentration, and biodegradation. Single-phase secondary loops operate over a large temperature range. The heat exchanger in the primary loop operates in the range -40◦ C to -30◦ C. Thus, the fluid must be liquid below 40◦ C. Typical temperatures observed in supermarket display cases and coolers range from -20◦ C to 0◦ C. Using the secondary fluid to subcool the primary refrigerant and defrost display cases boosts efficiency of the cycle. The display case defrosting temperature ranges from 20 to 30◦ C. Thus, the fluid must have a boiling point over 50◦ C for safe operations. The fluid should possess low viscosity in order to achieve low power requirements. If the viscosity of the fluid is not favorable, high pumping power is required to circulate the fluid throughout the store, leading to high costs. Viscosity is a strong function of temperature and special attention must be paid to low temperature rheology. High thermal conductivity leads to high heat transfer rates in display cases, which can be designed to reduce the total operating cost of secondary loops. Another characteristic of the fluid affecting performance is the volumetric heat capacity (VHT), i.e., the product of density of fluid and its specific heat: VHT = M −1 ρ clp



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Higher volumetric heat capacity reduces the amount of coolant needed for the same refrigeration load. Apart from the process targets, it is necessary for the fluid to have low corrosivity and low flammability due to its large-scale application in supermarkets. As the supermarkets are distributed within residential communities, the replacement fluid should also be environmentally acceptable, non-toxic, and biodegradable. The final property targets used in our model are as follows:

Viscosity at 300 K

η

≤ 10 mPa.s

Melting point

Tm

≤ 233 K

Boiling point

Tb

≥ 325 K

Heat capacity

VHT

Thermal conductivity

k

≥ 1.5 Jcc−1 K−1 ≥ 0.1 Wm−1 K−1

It should be noted that we use volumetric heat capacity and flash point estimates to rank the solutions rather than limit the feasible space. There exist trade-offs between the heat transfer characteristics and viscosity requirements of secondary refrigerants. The higher level of interactions at the molecular level that result in high heat capacity and thermal conductivity, also result in high viscosity. As a result, the search for a fluid that balances these requirements is a challenging problem.

4 A framework for computer-aided molecular design Computer-aided molecular design (CAMD) tools search the chemical composition space using property estimation techniques to provide a set of feasible molecules with desired properties. 33–41 Such an approach avoids the need for performing trial-and-error experiments for product development. Group contribution methods are widely used as property estimation models and are well suited for the CAMD approach. They use small chemical subgroups to quantify the molecular structure. In this section, we present a brief overview of the optimization-based molecular de8 ACS Paragon Plus Environment

Page 8 of 28

Page 9 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


sign framework that we developed previously 1 and will use in the next section for designing heat transfer fluids. The framework employs structural and property-based decomposition to solve a series of simpler subproblems. Under the structural decomposition scheme, the molecules are determined in stages with increasing resolution of the structure throughout the process. Property-based decomposition is implemented via property models based on the available resolution of molecules at each stage. Figure 3 presents an overview of the framework. The CAMD steps are automated and bundled into easy to use software, AMODEO (Automated MOlecular DEsign using Optimization), which is applicable to a variety of design problems. We briefly describe the components, features, and merits of the framework below.

Figure 3: Overview of CAMD framework



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 10 of 28

4.1 Characterization of the molecule The molecule is described as a collection of groups. A node in a connected molecular graph represents each occurrence of the groups. The composition is defined by the frequency of the groups, and structure is modeled by the edges between nodes. The search space for candidate molecules is comprised of various combinations of groups. 4.1.1 GC+ property model The GC+ model is a comprehensive group contribution method. 42,43 Its groups are divided in firstorder and higher-order groups. The first-order groups are typical non-overlapping chemical subgroups. The higher-order groups are combinations of first-order groups and capture proximity effects of functional groups, thus providing corrections to the first-order estimates. Each property is assumed to be a function of the additive contributions of the individual groups. The function is chosen to match the experimental data as closely as possible. The original GC+ model was developed for a number of standard and critical physical properties, 42 and was later extended to heat capacity and viscosity among other properties. 43–48 We use the GC+ model groups to describe the molecule and estimate its properties.

4.2 Composition design In the composition design stage, only the frequency of the groups in the molecules is investigated. We seek a diverse candidate set with favorable properties. The GC+ method groups are used as the elementary units of the molecule and first-order estimates for all GC+ properties are calculated. Using the property bounds, the nonlinear property model is transformed to a linear one in the function space. As an example, consider the property targets placed on normal boiling point:

273K ≤ Tb ≤ 450K.


Page 11 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Thus, the property constraint on boiling point using the GC+ estimation model 42 is given by:

273 ≤ Tb0 ln

∑ cini

≤ 450,

where ci is the contribution of group i to the property, and ni is the frequency of group i in the molecule. Tb0 is a model specific constant with value 222.543 K. The summation extends over all first-order groups present in the molecule. Because of the monotonicity of the logarithmic function, we can transform the above constraint into the following equivalent linear constraint exp(273/Tb0) ≤ ∑ ci ni ≤ exp(450/Tb0 ), i.e., 3.4101 ≤ ∑ ci ni ≤ 7.5540. In order to explore this linearity, nonlinear property relationships are used as part of the evaluation process only in a subsequent stage of the algorithm. These nonlinear relationships are discussed in the next section. Structural constraints are also added at this stage to ensure acyclic tree conditions. We allow for rings or multiring clusters by treating them as fictitious nodes in the acyclic tree. Thus, we enforce tree structure only in the space of acyclic bonds by allowing exactly V − 1 acyclic bonds between V groups, rings, and multiring clusters. The total number of open acyclic connections of all groups in the molecule is set to be twice the number of acyclic bonds (V − 1). Thanks to the integer linear nature of the resulting formulation, fast multiple solutions can easily be obtained with BARON 49,50 within GAMS. Solving the composition design problem using relaxed property targets yields a set of feasible compositions along with first-order estimates of all GC+ properties. These compositions are further analyzed in a subsequent stage of the design process.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 12 of 28

4.3 Structure generation Each solution composition obtained in the first phase, may correspond to a number of distinct isomers. The structures of candidate isomers are required in order to predict GC+ properties with better accuracy. Developing complete structures rather than just compositions also facilitates detailed analysis of the results. In order to systematically identify all the structures, we treat each isomer as a planar graph with each instance of groups as a node and chemical bonds as edges. The structure generation problem is equivalent to the problem of identifying all trees with a given degree sequence. All the structures are generated by solving an optimization model with bonds between nodes as binary variables. These variables represent the entries of the adjacency matrix of the molecular graph. The constraints for the feasible structures include node degree satisfaction, symmetry of the adjacency matrix, and connectivity of the graph. We use special tree and cycle constraints to cut down on the exponential number of connectivity constraints. Redundancy in the molecular space is also handled efficiently by using the logarithm of prime numbers as weights for each group in a cut that is generated for each isomer to avoid its redundant structure variations. We solve an MILP optimization problem repeatedly, adding cuts to obtain unique and feasible isomers. Each feasible solution to the MILP represents an isomer. We then refine the solution pool of the isomers using higher-order corrections to GC+ properties and retain a set of molecular structures with accurate property estimates. The molecules are also converted to simplified molecular-input line-entry specification (SMILES) notation 51 that facilitates the analysis of structures via external computational chemistry toolkits. The conversion also facilitates the use of other property estimation tools.

4.4 Extended design Most CAMD applications require screening based on properties not estimated by group contribution methods. The proposed approach accounts for such properties in the extended design stage by estimating their values using a variety of suitable methods. As the complete structure of iso12 ACS Paragon Plus Environment

Page 13 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


mers and their SMILES strings is available, many property models as well as external black-box property estimation tools can be employed at this stage. This utility allows the framework to be easily adaptable and widely applicable. Depending upon the application, arithmetic correlations like equations of state, complex metrics like process efficiency or simulation-based estimates for properties like reactivity are used.

5 Property models and performance criteria In this section, we formulate the molecular design problem to identify heat transfer fluids for retail food refrigeration by 1) defining design targets for GC+ properties, 2) selecting key refrigerant properties, their targets, and their estimation methods, 3) specifying performance criteria to judge the candidates, and 4) defining restrictions on types of molecules considered.

5.1 Phase 1 property models The following properties related to the refrigerant design problem are included in the GC+ model described in the previous section: melting point (Tm ), boiling point (Tb ), critical temperature (Tc ), critical pressure (Pc ), standard enthalpy of vaporization at 298 K (Hv ), molar liquid heat capacity (clp ), and viscosity at 300 K (η ).

5.2 External property models In Phase 3, the flash point is estimated using the Catoire and Naudet correlation: 52

Tf = 1.477 Tb0.79686 Hv0.16845 nC−0.05948 , where Hv is the standard heat of vaporization, Tb is the normal boiling point, and nC is the number of carbon atoms in the molecule. The heat conductivity is calculated at 298 K using the Sato-Reidel



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

298 correlation by defining Tr =

Tc

, Tbr =

k=

Tb Tc

Page 14 of 28

: 53 

2 3



1.1053  3 + 20(1 − Tr )    M 0.5 3 + 20(1 − Tbr ) 23

We extend the design problem to include biodegradability by exporting solutions to the BIOWIN software available through the EPI suite developed by the EPA. 54 BIOWIN estimates the probability of rapid aerobic and anaerobic biodegradation of an organic compound in the presence of mixed populations of environmental microorganisms as a continuous measure. A chemical is classified as “readily degradable” if the predicted probability is greater than 0.5. In Phase 3, we estimate the probability of biodegradation by using Model 2 in BIOWIN. LC50 values are estimated by using the Toxicity Estimation Software Tool developed by the EPA. 55 The tool includes groupcontribution methods for LC50 estimation. 56 The solution molecules are exported to the estimation tools via SMILES strings. Even though no specific constraints are placed on biodegradability and toxicity, estimates of the two properties allow us to screen the candidate solutions effectively. In the extended design phase, volumetric heat capacity is calculated by using the density estimates from the Gunn-Yumada correlation i h 2/7 −1 , ρ = M Vc (0.29056 − 0.08775ω )(1−T/Tc ) by employing the accentric factor (ω ) determined with Ambrose and Walton coefficient: 53

ω=

−θ lnPc + 5.9762θ − 1.2987θ −5.0336θ + 1.1150θ

1.5

1.5

+ 0.6039θ

− 5.4121θ

2.5

2.5

+ 1.0684θ

− 7.4668θ

5

5

,

Tb Tb and θ = 1 − are estimated using the GC+ estimates for boiling point and critical Tc Tc temperature.

where θ =


Page 15 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


5.3 Performance criteria We develop performance criteria to judge the efficiency of proposed molecules computationally. These criteria are used to assess the candidates rather than to eliminate them. In developing performance criteria we use the property models that model application regimes of secondary refrigerant fluids. Using the Dittus-Boulter correlation for turbulent flow, the heat transfer factor for a given liquid velocity and tube diameter can be defined as: 10

HTF = 0.023ρ 0.8 η −0.4

clp M

!0.4

k0.6 ,

where ρ is the density of the fluid, η the viscosity, clp is the molar liquid heat capacity, M is the molecular weight, and k is the heat conductivity of the liquid. Similarly, the performance of the secondary fluid can be assessed in terms of the pressure drop factor (PDF). The PDF captures the effect of fluid properties on pressure drop, which is directly related to the pumping costs. The pressure drop for a circular pipe is ∆P = f

L V2 ρ , D 2

where the friction factor ( f ) for smooth pipes and turbulent flow is defined by 0.092η 0.2

0.092 f=

Re0.2

=

ρ 0.2 D0.2V 0.2

.

For a given liquid velocity (V ), length of tube (L), and diameter (D), the pressure drop factor for the fluid is defined as: 10 PDF = 0.092η 0.2 . Secondary fluids can be judged on the HTF and PDF criteria. An ideal secondary fluid will have a high heat transfer factor and a low-pressure drop factor. In the SL literature, a similar performance criterion that combines both heat transfer factor and pressure drop factor has been



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 16 of 28

used to compare secondary fluids. The required pumping power can be correlated to the drop in fluid temperature along the cooling pipes. Efficiency of the coolant can be judged by comparing temperature drops for the same pressure drop or by calculating relative pumping power for constant temperature drop. For two fluids, A and B, the relative pumping power for identical geometry, cooling load, and temperature drop is given by: PA = PB

ρA ρB

1.6

ηA ηB

0.2

clpA MB clpB MA

!−2.8

We observe that this measure is highly sensitive to heat capacity values. Therefore, the presence of water in the industrial fluid affects the measure greatly.

5.4 Implementation details Our aim is to find a near drop-in replacement for current fluids. Non-functional groups (such as −CH3 and −CH2 −) are allowed to repeat at most 10 times each and the total size of the molecule is restricted to up to 10 groups. Our aim was to find safe and stable compounds. Thus, with the prior knowledge of flash point trends, we did not include olefins in the design. As mono- or bifunctional compounds are more prevalent, we only allowed up to two oxygen functional groups in the molecule. Historically, it has been shown that fluorine and chlorine substituted compounds are ideal refrigerants. However, their effect on the ozone layer and their global warming potential is high. Another issue reported with such fluids is the lack of biodegradation. Hence, we do not include any halogens in the design.

6 Results The Phase 1 composition design problem was solved in 21 seconds and produced 1614 feasible compositions. Each of these compositions was further analyzed by determining its structure in Phase 2 and calculating Phase 3 properties. These compositions generated 3912 structures. The


Page 17 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


average time required for each structure was 1.2 seconds on an Intel i7 3.4 GHz CPU. Overall, the average time required for generating structures was 4 seconds per composition. The isomers generated by AMODEO provide us with a list of possible secondary refrigerants. Out of the 3912 structures found, 1449 molecules are present in various databases. At this stage, we focus our attention on these compounds as we looked for drop-in replacement refrigerants. These solutions are discussed in this section. Figure 4 provides a plot of the heat transfer factor against the pressure drop factor for the solutions obtained. In addition, a few industrial fluids are plotted on this graph for comparison. The advantage of ethers and alkanes as heat transfer fluids can be inferred from the plot. Only industrial fluids with aromatics or silicone polymers provide low pressure drops but their environmental impact is worse than the biodegradable solutions identified by our approach. It can be seen in the graph that molecules we identified are capable of providing heat transfer factors equivalent to those of industrial fluids at lower pressure drop factors. In Figure 5, we plot relative pumping power against the flash points of the coolants. In the calculation of the relative pumping power for this figure, Syltherm 800 was chosen as the base fluid with which all other coolants were compared. All property values were evaluated at 298 K. For the designed molecules, we used experimental data for melting point, boiling point, viscosity, and density whenever they were available. In the figure, shaded symbols represent molecules with at least one of the above properties taken from databases. On the y-axis, we included the performance metrics of industrial fluids. A performance factor less than 1 indicates that the fluid is more efficient that Syltherm 800. For example, a performance metric of 0.1 indicates that the resultant fluid requires one tenth pumping power as compared to Syltherm 800. It is evident from the plot that flammable fluids have better performance and there exists a tradeoff between efficiency and safety. Glycol ethers form the most interesting sets of compounds identified. Ethylene and propylene glycols have been used a heat transfer fluids and we find that their alkyl ethers are attractive options for secondary coolants. 2-butoxyethanol, 2-ethoxyethanol, 2-propoxyethanol are all found as vi-



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Figure 4: Plot of heat transfer factor vs pressure drop factor


Page 18 of 28

Page 19 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 5: Pumping power relative to Syltherm 800 vs. flash point



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 20 of 28

able candidates. Their flash point also increases with their molecular weight. Their melting points are suppressed by the hydrogen bonding in the liquid phase. Thus, variations of these compounds offer promising prospects. Pentyl propanoate, hexyl acetate, and n-butyl acetate are some of the 158 simple esters that are part of the solution set. The esters in the range of C4-C9 meet almost every design specification. Lighter esters have lower flash points and heavier esters have melting points close to the desired range of operations. Many of these esters are used as solvents but they are flammable. Although flammable refrigerants are being used in industrial settings, their direct application in SL systems is not agreeable. However, water solubility of lower esters is favorable and they can be employed as aqueous mixtures. Ethanol and methanol have been previously used as heat transfer fluids but their toxicity hinders their use. Along with n-butanol, we identified these candidates. n-butanol has low toxicity and moderate fire hazard. It also shows low bioconcetration factor. Apart from the straight chain alcohols, branched-chain alcohols make up a sizeable part of the solutions. Diethyl carbonate, along with a few other carbonates, make up the remaining class of results. The biodegradability of esters, alcohols, and a few glycol ethers is much higher than HFCs and HCs. Finally, straight-chain and branched alkanes are identified as refrigerants by the proposed method. Their properties fit process conditions but they are not suitable due to their combustible nature. The heat transfer characteristics of branched alkanes are superior to other fluids. Thus, their application in other industrial cooling systems should be investigated. The comparison of fluids using heat capacity and other indices is the first step towards further analysis. The investigation of properties like global warming potential, ozone depletion potential, acute toxicity measures, and flammability limits would be the next stage of analysis for the resultant compounds. Aqueous mixtures used in industry benefit by the large heat capacity of water. Thus, the theoretical comparison of aqueous mixtures and single component fluids can be misleading. However, the performance of many designed molecules encourages analysis of mixture properties of candidate fluids and formulating blends as heat transfer media.


Page 21 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


7 Conclusions The paper presented a computer-aided molecular design approach to identify efficient refrigerant components for secondary cooling loops. As secondary loops reduce refrigerant leakage rates, an economical working fluid can lead to huge emissions reduction. We developed a computer-aided molecular design model to choose molecules that fit required criteria for a single-phase single component working fluid. The replacement secondary fluids were designed to meet process targets as drop-in replacements. We also included environmental and safety metrics (biodegradability and lethal concentration (LC50 )) by utilizing suitable EPA property prediction tools. Heat transfer efficiency and relative pressure drop were used to analyze the performance of the resulting solutions. The solutions that we obtained include a number of industrial fluids. A large number of biodegradable candidates ranging from homologues of current fluids to completely novel compounds include glycol ethers, aldehydes, alcohols, and simple ethers. Their comparison with current industrial formulations suggests that they represent promising directions for developing safe, biodegradable, low ODS, and low GWP coolants in retail food refrigeration. In addition, the molecules identified by the proposed approach have excellent heat transfer qualities, thus suggesting that their application to other cooling applications should be investigated.

Acknowledgements Portions of this work were performed in support of the National Energy Technology Laboratory’s research under the RDS Contract, along with financial support from the Dow Chemical Company.

References 1. Samudra, A.; Sahinidis, N. V. Optimization-based framework for computer-aided molecular design. AIChE Journal 2013, accepted. 2. Faramarzi, R. T.; Walker, D. H. Investigation of secondary loop supermarket refrigeration



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 22 of 28

systems; 2004; Available at http://www.energy.ca.gov/reports/2004-04-23_ 500-04-013.PDF. 3. Fairchild, P. D.; Fischer, S. K. Global warming and end-use efficiency implications of replacing CFCs; 1991; Available at http://www.osti.gov/bridge/servlets/purl/ 10119531-TjgUqr/webviewable/. 4. Profile of an average U.S. supermarket’s greenhouse gas impacts from refrigeration leaks compared to electricity consumption. Available at http://www.epa.gov/greenchill/ downloads/GC_AverageStoreProfile_FINAL_JUNE_2011_REVISED.pdf. 5. UNEP, 2006 Report of the Refrigeration, Air-Conditioning and Heat Pumps Technical Options Committee 2006 Assessment. United Nations Environment Programme (UNEP), Nairobi, Kenya, January 2007. Available at http://ozone.unep.org/teap/Reports/ RTOC/rtoc_assessment_report06.pdf. 6. GreenChill Partnership. Available at http://www.epa.gov/greenchill/. 7. ICF Consulting, Revised Draft Analysis of U.S. Commercial Supermarket Refrigeration Systems; 2005; Available at http://www.epa.gov/greenchill/downloads/ EPASupermarketReport_PUBLIC_30Nov05.pdf. 8. Wang, K.; Eisele, M.; Hwang, Y.; Radermacher, R. Review of secondary loop refrigeration systems. International Journal of Refrigeration 2010, 33, 212–234. 9. Walker, D. H. Development and demonstration of an advanced supermarket refrigeration/HVAC system; 2001; Available at http://www.ornl.gov/~webworks/cppr/ y2001/misc/116720.pdf. 10. Terrell, Jr., W. J.; Mao, Y.; Hrnjak, P. S. Evaluation of secondary fluids for use in low-temperature supermarket applications; 1999; Available at https://www.ideals. illinois.edu/bitstream/handle/2142/13198/CR015.pdf?sequence=2. 22 ACS Paragon Plus Environment

Page 23 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


11. Å. Melinder, Thermophysical properties of aqueous solutions used as secondary working fluids. Ph.D. thesis, Royal Institute of Technology, KTH, Stockholm, Sweden, 2007; Available at http://kth.diva-portal.org/smash/record.jsf;jsessionid= a0bdc9c491d94b4a85c3db3f463b?page=statistics&pid=diva2:12169. 12. Hinde, D. K.; Zha, S.; Lan, L. Carbon dioxide in North American supermarkets. ASHRAE Journal 2009, 51, 18–26. 13. Poland, J.; Groll, E. A.; Horton, W. T. Energy consumption and performance of supermarket refrigeration systems. International Refrigeration and Air Conditioning Conference 2010, Paper 1151, 2507–1–2507–6. 14. UNEP, 2010 Report of the Refrigeration, Air-Conditioning and Heat Pumps Technical Options Committee 2010 Assessment. United Nations Environment Programme (UNEP), Nairobi, Kenya, February 2011. Available at http://acdb-ext.gsfc.nasa.gov/ Documents/O3_Assessments/Docs/WMO_2010/2010assessment/RTOC_ 2010_Assessment_Report.pdf. 15. Baxter, V. D. IEA Annex 26: Advanced Supermarket Refrigeration/Heat Recovery Systems, Final Report Volume 1—Executive Summary; 2003; Available at http://www.ornl.gov/ ~webworks/cppr/y2003/rpt/117000.pdf. 16. Kruse, H. Refrigerant use in Europe. ASHRAE Journal 2004, 42, 16–24. 17. Joback, K. G. Designing molecules possessing desired physical property values. Ph.D. thesis, Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 1989. 18. Balaras, C. A.; Jeter, S. M. A methodology for selecting and screening novel refrigerants for use as alternative working fluids. Energy Conversion and Management 1991, 31, 389–398.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 28

19. Gani, R.; Nielsen, B.; Fredenslund, A. A group contribution approach to computer-aided molecular design. AIChE Journal 1991, 37, 1318–1332. 20. Duvedi, A. P.; Achenie, L. E. K. Designing environmentally safe refrigerants using mathematical programming. Chemical Engineering Science 1996, 51, 3727–3739. 21. Marcoulaki, E. C.; Kokossis, A. C. Molecular design synthesis using stochastic optimization as a tool for scoping and screening. Computers & Chemical Engineering 1998, 22, S11–S18. 22. Sahinidis, N. V.; Tawarmalani, M. Applications of global optimization to process and molecular design. Computers & Chemical Engineering 2000, 24, 2157–2169. 23. Apostolakou, A.; Adjiman, C. Refrigerant design case study. In L. E. K. Achenie, R. Gani and V. Venkatasubramanian (eds.), Computer Aided Molecular Design: Theory and Practice, Elsevier, Computer Aided Chemical Engineering, Volume 12 2002, 289–301. 24. Sahinidis, N. V.; Tawarmalani, M.; Yu, M. Design of alternative refrigerants via global optimization. AIChE Journal 2003, 49, 1761–1775. 25. Samudra, A.; Sahinidis, N. V. Design of secondary refrigerants: A combined optimizationenumeration approach. In M. M. El-Halwagi and A. A. Linninger (eds.), Proceedings of the Seventh International Conference on the Foundations of Computer-Aided Process Design, CRC Press 2009, 879–886. 26. Solvason, C. C.; Chemmangattuvalappil, N. G.; Eden, M. R. A systematic method for integrating product attributes within molecular synthesis. Computers & Chemical Engineering 2009, 33, 977–991. 27. Papadopoulos, A. I.; Stijepovic, M.; Linke, P. On the systematic design and selection of optimal working fluids for organic Rankine cycles. Applied Thermal Engineering 2010, 30, 760 –769.


Page 25 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


28. Eslick, J. C.; Shulda, S. M.; Spencer, P.; Camarda, K. V. Process Systems Engineering; WileyVCH Verlag GmbH & Co. KGaA, 2011; pp 173–193. 29. Warrier, P.; Sathyanarayana, A.; Patil, D. V.; France, S.; Joshi, Y.; Teja, A. S. Novel heat transfer fluids for direct immersion phase change cooling of electronic systems. International Journal of Heat and Mass Transfer 2012, 55, 3379–3385. 30. Warrier, P.; Sathyanarayana, A.; Bazdar, S.; Joshi, Y.; Teja, A. S. Selection and evaluation of organosilicon coolants for direct immersion cooling of electronic systems. Industrial & Engineering Chemistry Research 2012, 51, 10517–10523. 31. Nanda, G. Design of Efficient Secondary Refrigerants. M.Sc. thesis, Department of Chemical Engineering, University of Illinois, Urbana, IL, 2001. 32. Kazachki, G. S.; Hinde, D. K. Secondary coolant systems for supermarkets. ASHRAE Journal 2006, 46, 34–45. 33. Brignole, E. A.; Bottini, S. B.; Gani, R. A strategy for the design and selection of solvents for separation processes. Fluid Phase Equilibria 1986, 29, 125–132. 34. Joback, K. G.; Stephanopoulos, G. Designing molecules possessing desired physical property values. Proceedings of the 1989 Foundations of Computer-Aided Process Design Conference, Snowmass, CO, Elsevier, Amsterdam 1990, 195–230. 35. Harper, P. M.; Gani, R.; Kolar, P.; Ishikawa, T. Computer-aided molecular design with combined molecular modeling and group contribution. Fluid Phase Equilibria 1999, 158–160, 337–347. 36. Marcoulaki, E. C.; Kokossis, A. C. On the development of novel chemicals using a systematic optimisation approach. Part I. Optimisation framework. Chemical Engineering Science 2000, 55, 2529–2546.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 28

37. Achenie, L. E. K., Gani, R., Venkatasubramanian, V., Eds. Computer Aided Molecular Design Theory and Practice; 2002; Vol. 12. 38. Lehmann, A.; Maranas, C. D. Molecular design using quantum chemical calculations for property estimation. Industrial & Engineering Chemistry Research 2004, 43, 3419–3432. 39. Cismondi, M.; Brignole, E. A. Molecular design of solvents: An efficient search algorithm for branched molecules. Industrial & Engineering Chemistry Research 2004, 43, 784–790. 40. K. M. Ng, R. G., Dam-Johansen, K., Eds. Chemical Product Design: Toward a perspective through case studies; Computer Aided Chemical Engineering; Elsevier, 2007; Vol. 23. 41. Chávez-Islas, L. M.; Vasquez-Medrano, R.; Flores-Tlacuahuac, A. Optimal molecular design of ionic liquids for high-purity bioethanol production. Industrial & Engineering Chemistry Research 2011, 50, 5153–5168. 42. Marrero, J.; Gani, R. Group-contribution based estimation of pure component properties. Fluid Phase Equilibria 2001, 183–184, 183–208. 43. Gani, R.; Harper, P. M.; Hostrup, M. Automatic creation of missing groups through connectivity index for pure component property prediction. Industrial & Engineering Chemistry Research 2005, 44, 7262–7269. 44. Marrero, J.; Gani, R. Group-contribution-based estimation of octanol/water partition coefficient and aqueous solubility. Industrial & Engineering Chemistry Research 2002, 41, 6623– 6633. 45. Kolská, Z.; Ružiˇcka, V.; Gani, R. Estimation of the enthalpy of vaporization and the entropy of vaporization for pure organic compounds at 298.15 K and at normal boiling temperature by a group contribution method. Industrial & Engineering Chemistry Research 2005, 44, 8436– 8454.


Page 27 of 28

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


46. Kolská, Z.; Kukal, J.; Zábranský, M.; Ružiˇcka, V. Estimation of the heat capacity of organic liquids as a function of temperature by a three-level group contribution method. Industrial & Engineering Chemistry Research 2008, 47, 2075–2085. 47. González, H. E.; Abildskov, J.; Gani, R. Computer-aided framework for pure component properties and phase equilibria prediction for organic systems. Fluid Phase Equilibria 2007, 261, 199–204. 48. Conte, R.; Martinho, A.; Matos, H. A.; Gani, R. Combined group-contribution and atom connectivity index-based methods for estimation of surface tension and viscosity. Industrial & Engineering Chemistry Research 2008, 47, 7940–7954. 49. Sahinidis, N. V. BARON: A general purpose global optimization software package. Journal of Global Optimization 1996, 8, 201–205. 50. Tawarmalani, M.; Sahinidis, N. V. A polyhedral branch-and-cut approach to global optimization. Mathematical Programming 2005, 103, 225–249. 51. Weininger, D. SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. Journal of Chemical Information and Computer Sciences 1988, 28, 31–36. 52. Catoire, L.; Naudet, V. A unique equation to estimate flash points of selected pure liquids application to the correction of probably erroneous flash point values. Journal of Physical and Chemical Reference Data 2004, 33, 1083–1111. 53. Poling, B. E.; Prausnitz, J. M.; O’Connell, J. P. The properties of gases and liquids, 5th ed.; McGraw-Hill: New York, 2001. 54. Estimations Programs Interface (EPI Suite), EPA. Available at http://www.epa.gov/ oppt/exposure/pubs/episuitedl.htm.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 28 of 28

55. Toxicity Estimation Software Tool (TEST). Available at http://www.epa.gov/nrmrl/ std/qsar/qsar.html. 56. Martin, T. M.; Young, D. M. Prediction of the acute toxicity (96-h LC50) of organic compounds to the fathead minnow (Pimephales promelas) using a group contribution method. Chemical Research in Toxicology 2001, 14, 1378–1385.


Design of Heat-Transfer Media Components for Retail Food

Recommend Documents