Mixed Gas Refrigeration TechnologyMixed Gas Refrigeration Technology

66thth Annual Annual Industrial Refrigeration ConsortiumIndustrial Refrigeration ConsortiumResearch and Technology ForumResearch and Technology Forum

January 20, 2006January 20, 2006

Gregory Nellis, Sanford Klein, John PfotenhauerGregory Nellis, Sanford Klein, John Pfotenhauer

FlorianFlorian KepplerKeppler, Cory Hughes, Kylie Fredrickson, and John , Cory Hughes, Kylie Fredrickson, and John PettittPettitt

University of WisconsinUniversity of WisconsinSolar Energy LaboratorySolar Energy Laboratory

Presentation OutlinePresentation Outline

• Overview of cryogenic cycles– Recuperative cryogenic cycles– Mixed gas Joule-Thomson cryogenic cycles

• Current UW Research Efforts in MGR– Optimization of gas mixture composition– Measurement of heat transfer coefficients

• Other MGR research projects at the UW– Cryosurgical probes (ASHRAE)– Cooling high temperature superconducting electronics (ONR)– MEMS cryosurgical devices (NIH/Univ. of Michigan)

• Industrial application potential

Low Temperature ApplicationsLow Temperature Applications

from Radebaugh (2000)

MGRLNGAir Lq

HTS Power

Cryopumping

Food Freezing

Cryosurgery

IR

vario

us L

TS a

pp.

HTS Electronics

SMESFusion

detectors

Conventional Refrigeration TechnologyConventional Refrigeration Technology

from Timm (2003)

Multi-stage Vapor Compression Cascade Cycle

Conventional Refrigeration TechnologyConventional Refrigeration Technology

from Radebaugh (2000)

MGRLNGAir Lq

HTS Power

Cryopumping

Food Freezing

Cryosurgery

IR

vario

us L

TS a

pp.

HTS Electronics

SMESFusion

detectors

Cas

cade

&

Mul

ti-st

age

VC

Cryogenic Refrigeration TechnologyCryogenic Refrigeration Technology

regenerator

piston

Regenerative

loadQ

rejQ

rejQ

compressor

recuperator

Recuperative

loadQ

rejQ

Regenerative CryocoolersRegenerative Cryocoolers

Regenerative Cryogenic RefrigeratorsRegenerative Cryogenic Refrigerators

from Radebaugh (2000)

MGRLNGAir Lq

HTS Power

Cryopumping

Food Freezing

Cryosurgery

IR

vario

us L

TS a

pp.

HTS Electronics

SMESFusion

detectors

Cas

cade

&

Mul

ti-st

age

VCSt

irlin

g

Stirling-typePulse tube

GM

GM-type Pulse tube

Recuperative CyclesRecuperative Cycles

work-extracting expander

Reverse-Brayton

loadQ

rejQ

isenthalpicvalve

Joule-Thomson

loadQ

rejQ

Recuperative Heat ExchangersRecuperative Heat Exchangers

PraxAir Air Separation Plant, from Timm (2003)

Chart Industries

Cryoprobe

Work Extracting DeviceWork Extracting Device

http://www.astec.ac.uk/Seminars/bobbatecryogenics.pdf

Creare’s NICMOS Cryocooler

ReverseReverse--BraytonBrayton RefrigeratorsRefrigerators

from Radebaugh (2000)

MGRLNGAir Lq

HTS Power

Cryopumping

Food Freezing

Cryosurgery

IR

vario

us L

TS a

pp.

HTS Electronics

SMESFusion

detectors

Cas

cade

&

Mul

ti-st

age

VC

Regenerative

Reverse-Brayton

Reverse-Brayton

JouleJoule--Thomson Thomson CryocoolersCryocoolers

from Timm (2003)

from Nova, Science Now, April 2005

Mixed Gas JMixed Gas J--T RefrigeratorsT Refrigerators

from Radebaugh (2000)

MGRLNGAir Lq

HTS Power

Cryopumping

Food Freezing

Cryosurgery

IR

vario

us L

TS a

pp.

HTS Electronics

SMESFusion

detectors

Cas

cade

&

Mul

ti-st

age

VC

Regenerative

Reverse-Brayton

Reverse-Brayton

MGR

MGR

loadQ

( )lowm h P ,T⋅

( )highm h P ,T T⋅ + ΔexpW

( ) ( )load exp low highQ W m h P ,T h P ,T T⎡ ⎤= + ⋅ − + Δ⎣ ⎦

energy transferredas expander work

enthalpy flux

ReverseReverse--BraytonBrayton CycleCycle

loadQ

( )lowm h P ,T⋅

( )highm h P ,T T⋅ + Δ

( ) ( )load low highQ m h P ,T h P ,T T⎡ ⎤= ⋅ − + Δ⎣ ⎦

energy transferredas enthalpy flux

JouleJoule--Thomson CycleThomson Cycle

Typical Working FluidsTypical Working Fluids

• Pure components– Nitrogen– Argon– Hydrocarbons

• Mixtures– Combinations of pure components

(hydrocarbons, halocarbons, inert gases)• Nitrogen+pentane+ethane+…

PP--h Diagram for Nitrogenh Diagram for Nitrogen

loadQ

( )lowm h P ,T⋅

( )highm h P ,T T⋅ + Δ

( ) ( )load low highQ m h P ,T h P ,T T⎡ ⎤= ⋅ − + Δ⎣ ⎦

( ) ( )loadlow high load rej

max

Q min h P ,T h P ,T for T T Tm

⎛ ⎞ ⎡ ⎤= − < <⎜ ⎟ ⎣ ⎦⎝ ⎠

• at pinch-point for perfect HX, ΔT = 0

Maximum Refrigeration PotentialMaximum Refrigeration Potential

Pres

sure

(kPa

)

Enthalpy (kJ/kg)

@ 80 K@ 100 K

@ 125 K @ 200 K

JouleJoule--Thomson Effect for Pure NitrogenThomson Effect for Pure Nitrogen

Typical Operating Temperature

Range

⎛ ⎞≈⎜ ⎟

⎝ ⎠load

max

Q W2 m g/s

Enth

alpy

Diff

eren

ce (k

J/kg

)

Temperature (K)

“Good” Temp. Range

JouleJoule--Thomson Effect for Pure NitrogenThomson Effect for Pure Nitrogen

JouleJoule--Thomson Effect for Pure SubstancesThomson Effect for Pure Substances

Pre

ssur

e (k

Pa)

Enthalpy (kJ/kg)14% Nitrogen, 8% Methane, 78% Ethane

JouleJoule--Thomson Effect for Mixed GasThomson Effect for Mixed Gas

@ 125 K @ 175 K @ 250 K

Ent

halp

y D

iffer

ence

(kJ/

kg)

Temperature (K)

Operating Temp. Range

⎛ ⎞≈⎜ ⎟

⎝ ⎠load

max

Q W12 m g/s

JouleJoule--Thomson Effect for Mixed GasThomson Effect for Mixed Gas

Importance of Careful Mixture OptimizationImportance of Careful Mixture Optimization

Optimization ModelOptimization Model

load,coldQ

rejQcompW

• Heat exchanger broken into small segments, each with a distributed load

• Each segment treated using modified ε-NTU equation

• Freezing point computed using linear average

• Properties computed using NIST 4 • NIST 4 verified against NIST 23• Synthetic refrigerants added to NIST 4

• Model can be used to:• optimize composition (maximize

performance subject to some constraints)

• design heat exchanger (consider specific geometry via specific correlations or data for heat transfer coefficient, and friction factor)

• Conventional optimization algorithms (e.g., Direct Search and Quadratic Approximation Techniques) were found to be unreliable

• tended to locate “local” maxima• would get “stuck” on sharp discontinuities• could not handle optimization constraints efficiently

• Genetic Algorithm• robust scheme designed to reliably find global optimal in “poorly”

behaved environment (local optima, discontinuities)• mimics biological evolution• entire variable space is populated• populations bred based on their “fitness”

Genetic Optimization AlgorithmGenetic Optimization Algorithm

Mole fraction of methane

Mol

e fra

ctio

n of

isob

utan

e

Freezing Zone

true, constrained optimum

sharp discontinuitiescontours of loadQ

m

Optimization of 3Optimization of 3--Component MixtureComponent Mixture

* balance of mixture is N2

Direct Search Optimization AlgorithmsDirect Search Optimization Algorithms

Direct Search Optimization AlgorithmsDirect Search Optimization Algorithms

Genetic Optimization AlgorithmGenetic Optimization Algorithm

Optimization ResultsOptimization Results

300.6 KIsopentane, C5H12

263.0 KIsobutane, C4H10

231.2 KPropane, C3H8

184.5 KEthane, C2H6

169.1 KAcetylene, C2H4

145.0 KR14, CF4

111.7 KMethane, CH4

87.3 KArgon, Ar77.2 KNitrogen, N2

Normal Boiling Point

Component

Group I components (hydrocarbons*)

* except R14, N2, and Ar

246.8 KR134a, C2H2F4

224.7 KR125, C2HF5

221.2 KR32, CH2F2

194.7 KR116, C2F6

190.0 KR23, CHF3

145.0 KR14, CF4

87.3 KArgon, Ar77.2 KNitrogen, N2

Normal Boiling Point

Component

Group II components (halogenated hydrocarbons**)

** except N2, and Ar

Optimized Refrigeration CapacityOptimized Refrigeration CapacityCombinations from Group I at 90 K

Optimized Refrigeration CapacityOptimized Refrigeration CapacityCombinations from Group II at 90 K

Heat Transfer Coefficient MeasurementsHeat Transfer Coefficient Measurements

• Test section is fed with controlled mass flow rate, pressure, and temperature of a mixed gas with measured composition

• Heat addition and the inlet, exit, and surface temperatures are measured and used to infer the heat transfer coefficient.

s lmq htc A T= Δ ( ) ( )1 2

1

2

ln

w wlm

w

w

T T T TT

T TT T

− − −Δ =

⎛ ⎞−⎜ ⎟−⎝ ⎠

T1 T2Tw

q

G. F. Nellis, C. B. Hughes, and J. M. Pfotenhauer, "Heat transfer coefficient measurements for mixed gas working fluids at cryogenic temperatures", Cryogenics, Vol. 45, pp. 546-556, (2005).

Heat addition via nichrome wire

Test section tube

Wall surface temperature measurement

Test SectionTest Section

G-10 Plug

PRT

G-10 plug

Fluid FlowFluid flow

Test FacilityTest Facility

Vacuum space

Test Section

Recuperator

GM cryocooler

T,PT

Gas control system

Gas chromatograph

T

T

Flow meter

q

ΔP

Regulator

Cryomech AL-60 GM cryocooler

Cryocooler heat exchanger

Recuperative heat exchanger

Test section

Dewar lid

Cryocooler cold head

Temperature measurements

Test FacilityTest Facility

Experimental MeasurementsExperimental Measurements

Experimental MeasurementsExperimental Measurements

single-phase liquid

single-phase vapor

TwoTwo--Phase MeasurementsPhase Measurements

Run A

MGR Projects at the UWMGR Projects at the UW• Cryosurgery

– sponsored by ASHRAE– objective is to optimize cryoprobe design for cryosurgery– focus on choice of gas mixture composition

• Cooling for High Temperature Superconducting Electronics– primarily focused on cooling the signal and power leads– optimization for distributed load related to axial conduction and

ohmic dissipation– measurement of heat transfer coefficients

• MEMS Cooling– sponsored by NIH– objective is to evaluate MEMS techniques for cryosurgical probes

MGR in Food Processing?MGR in Food Processing?• Freeze drying or flash freezing applications

• Cascade cycles– Multiple refrigerant circuits– different working fluids in each circuit– Compressors required for each circuit– Can achieve very low temperature operation

• MGR– Uses a mixture of refrigerants in a single circuit– Can utilize a single compressor– Mixtures exhibit large glide from bubble point to dew point– Can achieve very low temperature operation

MGR MGR ““IssuesIssues””

• More complex than single component• Predicting flow regime in heat exchangers is important• Need property data over very wide temperature range,

including interaction parameters• Need to know when fluids and mixtures will freeze• Need to avoid unexpected pinch points within heat

exchangers• Need to avoid heat leaks at walls, valves, etc.• Can be important to dampen vibration induced by turbulent

flow or boiling (see Hill, Longsworth 1997)• Benefit: can fine tune mixture in the field to address

problems if they occur

Source: M. Timm 2003

ConclusionsConclusions

• MGR is a technology currently being used for low temperature refrigeration applications

• Opportunities exist for extending its application to food processing but requires– seeking mixtures that are not flammable– applications with low temperature demands– system designs are more complex

• MGR continues to be a rapidly developing technology

Source: M. Timm 2003