Property Data for Low-GWP Refrigerants: What Do We Know and What Don t We Know?

Transcription

1 Property Data for Low-GWP Refrigerants: What Do We Know and What Don t We Know? Mark O. McLinden Thermophysical Properties Division National Institute of Standards and Technology Boulder, Colorado USA ASHRAE Winter Meeting, Las Vegas, NV Seminar 6 Removing Barriers for Low-GWP Refrigerants January 30, 2011

2 Removing Barriers to Low-GWP Refrigerants Learning Objectives Describe the climate change issue associated with high-gwp refrigerants and the leading low-gwp options available today Explain the refrigerant thermophysical property requirements needed for new low-gwp refrigerants and how property data may be used Be able to explain the challenges with measuring the flammability properties of refrigerants that are only marginally flammable and options to make these measurements Explain the development history of hydrofluoroolefin low-gwp refrigerants such as HFO-1234yf and why this new class of compounds has unique properties Describe the codes and regulations in the U.S., Europe, and Japan that govern the use of low-gwp refrigerants, such as CO 2, ammonia, hydrocarbons, and HFOs, and the barriers in current standards for their potential use Apply learnings from seminar to begin selecting low-gwp refrigerants for specific applications and begin designing new HVAC&R systems with these refrigerants

3 Outline What data do we need? What are the candidate fluids? Assessment of the data How are the new fluids different?

4 What Data Do We Need on a Refrigerant? Safety toxicity (acute and chronic) flammability Environmental ozone depletion potential (ODP) green house warming potential (GWP) atmospheric life (impacts ODP & GWP) Materials compatibility with metals, seals, etc. lubricant stability (hydrolysis, polymerization, etc.) Performance thermodynamic properties transport properties

5 What Counts as Low-GWP? R134a: GWP = 1430 (relative to CO 2 w/ 100-year time horizon) must have GWP << 1430 EU regulation for automotive A/C: GWP < 150 (takes effect 2011 for new models) North American Proposal to Montreal Protocol: 85 % phase-down by 2033 ( = 215)

6 Low-GWP Options (Current Fluids) Fluid NBP ( C) GWP [CO 2 = 1] ASHRAE class (tox/flam) HFC N/A (flam) A2L N/A (flam) 134a A1 152a A2 HCFC B1 HC 290 (propane) A3 600a (isobutane) A3 600 (butane) A3 CO A1 NH (ammonia) 33.3 <1 B2L H 2 O 718 (water) <1 A1 Ether E A3

7 Low-GWP Refrigerants New Possibilities Hydro-Fluoro-Olefin (HFO) C=C double bond fluorine-containing hydrogen-containing Fluid NBP ( C) GWP [CO 2 = 1] ASHRAE class (tox/flam) HFO 1234yf A2L 1234ze(E) L(pending)

8 Additional HFOs Under Development Announced in talks and conference papers but not identified Many (most?) are in patent or chemical literature molecules themselves are not patentable (production processes are patentable) Blends w/ HFOs also being developed azeotropic blends are patentable zeotropic blends may be patentable??? This is the major What We Don t Know

9 Low-GWP Refrigerants Additional Possibilities Interest in fluorinated ethers in 1990s Examples among specialty solvents and heat-transfer fluids: fluorinated ethers especially segregated ethers (all H on a single carbon) fluorinated ketones non-flammable low(ish) GWP commercially available (but boiling points higher than typical refrigerants)

10 Property Data and Equations of State

11 Fluid Properties Why Should ASHRAE Care? Cycle analysis IS properties 3 Condenser 2 Pressure 3 4 Enthalpy 1 2 Expansion Valve 4 q = 0 T3 = Tcond P3 = Psat(Tcond) h4 = h3 P4 = P1 Evaporator S2 = S1 P2 = P3 Compressor 1 q = 1 T1 = Tevap P1 = Psat(Tevap) COP R = h h 1 4 = f( T evap,t cond, properties) h 2 h 1

12 Equation of State (Thermodynamic Properties)

13 Equation of State Helmholtz Energy Form A thermodynamically consistent representation of the properties of a fluid = A RT = ideal + N i ti d k i ( ) + N j t j d j exp a j l j j + N k tk dk exp a k k k ( ) l k Gaussian terms (critical region) traditional terms exp k k ( ) m k where : = crit, = T crit T All other properties by differentiation: p = RT 1 + r, C V = R 2 2 2

14 Equation of State Mixture Form mix = Sum pure component contributions + excess (mixing) term ( ) [ ] x i 0 i (,)+ ln x i + x i r i, i + x i x j F ij N k i k j k i j=i+1 k i ( ) ideal solution terms (ideal gas & real gas ) excess contribution mixing function Evaluate at reduced T, (not mixture T, ) given by reducing parameters = T * T = * n T * crit = x i T i + x i x j 1 ij * = x i + x i x i ij i=1 n 1 i n j=i+1 n crit i=1 i n 1 i n j =i +1 Adjustable parameters,, F ij + mixing function give great flexibility in fitting mixtures with limited or extensive data

15 Data Needed to Establish Equation of State (Thermodynamic Properties) Critical parameters (T crit, p crit, crit ) Vapor pressure as f(t) Density (liquid, vapor, supercritical) Ideal-gas heat capacity [C p as p0] Caloric data (liquid): C p or C V or w

16 Recent R1234ze(E) Data p--t and vapor pressure data McLinden, et al., Int. Ref. Conf. Purdue (2010) 4.0 Temperature (K) filling 1 filling 2 filling 3 saturation Pressure (MPa) Density (kg m 3 ) Temperature (K) Liquid-phase speed of sound Lago, et al. (2010) Liquid-phase heat capacity Tanaka, et al., J. Chem. Eng. Data (2010) Critical region data, Higashi, et al., J. Chem. Eng. Data (2010) p = 10 MPa w (m/s) p = 2 MPa Temperature (K)

17 Equation of State Fitting Process (R1234ze(E) as Example) Non-linear in the parameters must start with initial guess for EOS propane equation with 14 terms Objective function: minimize sum of squares Fit numerical coefficients Fit exponents on temperature terms (0 ~ 5), max for R1234ze is 2.5 Fixed exponents on density terms integers 1 Highly iterative process (1000 s of iterations)

18 Equation of State Fitting Process (Constraints) Numerous further constraints e.g., shape of critical isotherm for < crit : p > 0; 2 p 2 < 0; 3 p 3 > 0; 4 p 4 < 0; for > crit : p > 0; 2 p 2 > 0; 3 p 3 > 0; 4 p 4 > 0; add exp p tosumof squares EOS with correct shape: small addition to sum of squares EOS with incorrect shape: large penalty to sum of squares Pressure (MPa) calculated points critical point saturated vapor Density (kg/m 3 ) T = T crit saturated liquid

19 Data Comparisons and Assessments

20 Data Comparisons EOS vs. p--t Data, R1234ze(E) ( exp EOS )/ EOS or 100 (p exp p EOS )/p EOS T crit Temperature (K) crit Density (kgm 3 ) Source (%) McLinden et al Tanaka Grebenkov (sat n) 0.22 Grebenkov (liquid) 0.52 Grebenkov (vapor) 1.31

21 Data Comparisons EOS vs. p sat Data, R1234ze(E) (p exp p EOS )/p EOS Source (%) McLinden et al Tanaka Grebenkov Temperature (K)

22 Data Comparisons EOS vs. C p and Sound Speed Data R1234ze(E) (X exp X EOS )/X EOS Source (%) Tanaka (C p ) Lago (w) Temperature (K)

23 Data Summary Fluid HFC HCFC HC CO 2 NH 3 H 2 O DME HFO a 152a (propane) 600a (isobutane) 600 (butane) (ammonia) 718 (water) E yf 1234ze(E) Eqn. of State Transport (thermo) (visc. & t.c.) good good good good fair (old form) good fair (old form) fair (visc) good (t.c.) excellent very good very good very good very good very good excellent very good fair (!)* good excellent excellent fair (limited data) fair (limited data) good (limited data) limited data good (limited data) limited data *new EOS under development

24 Thermo Data Summary Blends bubble line (liquid) Blend Class HFC 32/125/134a other HFC blends HFC + HC Data Assessment very good data and model numerous mixture pairs, but generally only VLE data (i.e., no (T,p,x)) limited pairs, generally only VLE data Pressure dew line (vapor) 0 1 Composition HFC + ethers HC blends virtually no data very good data and models (natural gas) 0.18 azeotrope HFO + HFC predictive model for refrigerant blends Arakawa et al. (2010): R32/1234yf* proprietary data (azeotropes disclosed) available, generally good, but dated (2001) Pressure *additional work in progress in Japan Composition

25 Refrigerant Molecules Are Getting More Complex CFC-12 HFC-134a HFO-1234yf NBP: ( 29.8 C) ( 26.1 C) ( 29.5 C) Pressure R12 R134a R1234yf Temperature R12 R134a R1234yf Enthalpy (mass basis) Entropy (mass basis) Increased complexity: changes fundamental shape of thermodynamic surface increased flash losses The cycle may need to be modified

26 Conclusions Adequate data for a range of traditional and new low-gwp fluids But much work remains: Additional candidates are proprietary Blend data w/ HFOs are very limited New fluids may require modified cycles

27 Questions?