TEM analysis of gas turbine and diesel particles

Randy Vander Wal4, Madhu Singh4, Jeff Stevens2, Richard Frazee5,

Mary Forde1, Bob Giannelli2, Robert Howard1, John Kinsey2, and David Kittelson3

1U. S. Air Force, Arnold Engineering Development Complex (AEDC)2U. S. Environmental Protection Agency

3University of Minnesota4Penn State University5Singularity Scientific

Combustion Aerosol Conference 2019The Aerosol Society

26 – 28 June, Cambridge UniversityCambridge, England

Acknowledgements

• This work is part of a large series of studies “Variable Response In Aircraft non-volatile PM (nvPM) Testing (VARIAnT) 1 through 4 with many participants

• Today’s presentation is based in part on “Variable Response In Aircraft nvPM Testing (VARIAnT): VARIAnT 3 and 4 Updates,” presented at SAE International E-31P Committee, Saclay, France, June 2019

• Special thanks to:• Randy Vander Wal and Madhu Singh who did the TEM analysis and • Jeff Stevens and Richard Frazee who loaded and collected the TEM grids

• We thank the USEPA for their generous support

Primary Objectives of VARIAnT 3 program

• Assess the response of selected black carbon (BC) mass measurement instruments to various diffusion flame combustion aerosol sources (DFCASs)

• Provide data to assess whether improvements can be made to any of the selected mass instruments that will make them more applicable to a wider range of source types

• Additional measurements to understand the influence of physical and chemical structure of particles on the response of these instruments• Solid/Total fraction – with/without catalytic stripper (CS)

• EC/OC fraction

• Particle size, size distribution with conventional sizing instruments• SMPS

• EEPS

• DMS500

• Particle size dependent density

• Teflon filter elemental analysis

• Particle morphology from TEM analysis – the focus of this presentation

Diffusion flame combustion sources for TEM analysis

• Gas turbines• J-85-GE-5 turbojet engine

• Libby Welding Company (AiResearch) LGT-60 gas turbine APU (start cart)

• Diesel engines• 2013 Cummins Model ISX15 heavy duty diesel engine - a modern engine but without usual

exhaust aftertreatment

• ISUZU 4LE2T diesel engine generator set – an old technology engine

• Fuels• Jet-A (LGT-60 and J-85)

• 50% HDRD/Jet-A blend (LGT-60)

• 45% Camelina/Jet-A blend (LGT-60 and J-85)

• 70% Camelina/Jet-A blend (J-85)

• Certification diesel fuel (Cummins ISX15)

• 100% Hydrogenation-Derived Renewable Diesel (HDRD) fuel (ISUZU 4LE2T)

Methods

• Particles were sampled onto TEM grids with an electrostatic precipitator (Naneos TEM sampler) • Approximately 120 TEM grids were collected, 25 of these were analyzed for

morphology and size

• On each grid 60-70 randomly selected aggregates and 100 – 120 primary particles were measured

• Particle mobility size distributions were measured with SMPSs

• In some cases, particles were sampled downstream of a catalytic stripper (CS) designed to remove semi-volatile material

Range of particle sizes studied - SMPS

TEM Images: Cummins Diesel Fuel: Certification Fuel; with Catalytic Stripper

1500 rpm 0% torque 1200 rpm 20% torque 900 rpm 60% torque

50 nm 50 nm

50 nm50 nm20 nm

100 nm

• 1500 rpm @ 0% torque

• Mainly large aggregates spanning up to ~150-200 nm with varied morphology.

• Relatively consistent in aggregate morphology, showing elongated aggregates.

• 1200 rpm @ 20% torque

• Aggregates spanning ~ 50-100 nm with varied morphologies

• Most aggregates have significant particle-particle overlap.

• 900 rpm @ 60% torque

• Aggregates spanning ~ 50-100 nm with varied morphologies

• Some graphitic nanostructure is observed.

• High overlap between primary particles is evident for all conditions.

TEM Images: LGT-60 gas turbine APUFuels: Jet A, 50% HDRD, 70% Camelina

No Load - 50% HDRD fuel: Smaller aggregates than Jet A - most generally dendritic.

No Load - Jet A: Relatively large aggregates compared to the other LGT-60 samples with blended fuels.

No Load - 70% Camelina Fuel: Smallest aggregate and primary particle size. Large variation in aggregate morphology.

with Catalytic Stripper with Catalytic Stripper

50 nm

without Catalytic Stripper

50 nm

50 nm

100 nm 100 nm 100 nm

T2.15

CSBox 4 Sample E

T2.4 CS Box 4 Sample BT2.1 CS Box 4 Sample A

TEM Images: J-85 Fuel: Jet A; with Catalytic Stripper

PLA 15: Small aggregates, few primary particles per aggregate. Individual (singlet) primary particles observed.

PLA 40: Mostly small aggregates with few primary particles per aggregate. A few large dendritic particles observed.

PLA 90: Mixture of compact and branching aggregates with a pseudo-spherule morphology.

Aggregate size and number of primary particles per aggregate increases with increasing engine power.

20 nm 50 nm50 nm200 nm 100 nm 100 nm

T3.1 No CS Box 3 Sample A T4.2 No CS Box 3 Sample E T3.5 No CS Box 3 Sample B

TEM Images: J-85Camelina/Jet A Blend Fuels; without Catalytic Stripper

PLA 10 - 45% blend: Largest variation in morphology: compact to dendritic.

PLA 60 - 45% blend: Irregularly shaped agglomerates with varied primary particle sizes.

PLA 10 - 70% blend: Many small (few primary particles) aggregates. Generally smaller compared to 45% blend.

200 nm

200 nm200 nm 50 nm 50 nm

50 nm

TEM Images for Isuzu Diesel Engine with and without Catalytic Stripper

D13.1 | No load | 100% HDRD | CS

D13.2 | No load | 100% HDRD | No CS

No significant differences in morphology with and without the catalytic stripper for the 60 images analyzed

Influence of Catalytic Stripper on size distribution (bimodal fit): nucleation mode removed, accumulation mode unchanged

Sizing of complex particles

• Deq aggregate projected area equivalent diameter – diameter of a circle with same projected area as aggregate being examined

• DGN or GMD, geometric mean diameter of particles measure by SMPS, size descriptor appropriate for lognormal distribution

• AMD, arithmetic mean diameter of particles measured by SMPS, size descriptor appropriate for normal distributions

• DAS, diameter of average surface, diameter of spherical particle having the same surface area per particle as measured by the SMPS

𝐷𝐴𝑆 = (𝑆𝑡𝑜𝑡𝑎𝑙/(𝑝𝑖 ∗ 𝑁𝑡𝑜𝑡𝑎𝑙))0.5

• For spherical particles deposited on a surface

𝐷𝐴𝑆 = 𝐷𝑒𝑞

SMPS equivalent diameters vary more than TEM equivalent aggregate diameters, Deq. As shown in figure lower right, DAS matches Deq most closely.

Projected area equivalent diameter, DAS, plotted against equivalent aggregate diameters, Deq

Linear trendlines shown

Comparison of primary particle and aggregate size

• J-85 Turbojet engine

• Cummins and Isuzu Diesel engines

• LGT-60 Gas turbine APU (Start Cart)

• Diesel shows a larger spread across conditions, followed by Jet and LGT shows the least spread and more of a cluster of points.

Aggregate size vs. Primary Particle sizeJ-85 Turbojet engine

Aggregate size vs. Primary Particle sizeDiesel engines

Aggregate size vs. Primary Particle sizeLGT-60 gas turbine APU (Start Cart)

Primary Particle vs. Aggregate diametersAverage for engine type and fuel

• The multiple points per engine are averaged values for the different fuels

• Diesel• Cummins with Cert Fuel • Isuzu with HDRD Fuel

• LGT-60• Jet A Fuel• Fuel Blend, Jet A with 50% HDRD• Fuel Blend, Jet A with 70% Camelina

• J-85 Turbojet• Jet A Fuel• Fuel Blend, Jet A with 45% Camelina• Fuel Blend, Jet A with 70% Camelina

Summary of Preliminary TEM Observations

Differences among sources and fuels:

• Cummins and Isuzu Diesels• For both engines, primary size depends on load; aggregate and mobility size largely independent (esp. Cummins

engine).

• 100% HDRD fuel yielded smaller aggregates in older Isuzu engine compared to newer Cummins engine with certification fuel.

• J-85 turbojet• Influence of biofuel content (Camelina) - Primary particle, aggregate and mobility sizes (and mass

concentration) decrease with increasing amount of Camelina in fuel.

• Influence of engine power - Significant increase in primary particle and mobility size with power; less for aggregates. Aggregate morphology (fractal dimension) changes significantly with increasing power level from compact clusters to complex aggregates

• LGT-60 gas turbine APU (Start Cart)• Influence of biofuel content (Camelina) – A general decrease in primary particle, aggregate, and mobility sizes

with increasing biofuel content. Significant run to run variation, especially with Jet A.

Summary of Preliminary TEM Observations (cont’d)

General Observations:• Effect of catalytic stripper usage on particles:

• No visible coating on particles, no liquid-like droplets, no discernable difference between aggregate morphology or size with or without stripper.

• SMPS data show no influence on accumulation mode but removal of semi-volatile nucleation mode (when present)

• Difference between J-85 samples and diesel samples is visually apparent, statistically significant, and smaller aggregate mean size.

• Additionally, the J-85 aggregates exhibit higher dendritic morphology compared to diesel PM.

Ongoing work• Bringing different measurements together

• Composition from filters and TEM

• Relating TEM 2-d fractal dimensions to measured mass mobility coefficient

• Analysis of similar work under VARIAnT 4 with considerably smaller particles

• How does all this relate to under response of some mass instruments to very small particles?

Thank you - questions

Extra slides

GMD/Deq AMD/Deq DAS/Deq

J-85 0.81 0.90 1.00

LGT-60 0.85 0.95 1.07

Diesel 0.62 0.73 0.83

All 0.77 0.86 0.97

J-85 Turbojet

Diesel

LGT-60 gas turbine APU

SMPS equivalent diameters all vary somewhat more than TEM equivalent aggregate diameters, Deq. As shown in the table below, DAS follows Deq most closely.

Do these size distributions appear more normal (right) or lognormal (left)?

Typical aggregate size, primary particle size, morphology, & fractal nature

Cummins Diesel

Cert FuelIsuzu Diesel

100% HDRD

LGT-60

Jet AJ-85

Jet A