Smart Refractory

7/25/2019 Smart Refractory

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AOI[3]: Smart Refractory Sensor Systems forWireless Monitoring of Temperature, Health,

and Degradation of Slagging Gasifiers

PI Team:

Dr. Debangsu Bhattacharyya a

Mr. Jeffrey Bogan b

Dr. David Graham c

Dr. Vinod Kulathumani c

Dr. Edward M. Sabolsky d

a

Department of Chemical Engineering, WVUbHarbisonWalker International Technology CentercLane Department of Computer Science and Electrical Engineering, WVU

dDepartment of Mechanical and Aerospace Engineering, WVU


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4/27/20162

Researcher Team:

Post-doc

Rajalekshmi Pillai

Graduate Students

Qiao Huang

Gunes Yakaboylu

Steven Andryzcik

Priyashraba Misra

Undergraduate Students

Brian Armour

James Meyer

HWI Team Margaret Raughley

Joshua Sayre


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3

Acknowledgements:

We would like to thank U.S. Department of Energy (DOE) for

funding the project under contract DE-FE0012383.

Dr. Maria Reidpath, U. S. Department of Energy, is greatlyappreciated for her insight and valuable guidance.

We also would like to acknowledge WVU Shared Facilities.

Thanks to HarbisonWalker International for the technical

staff.

Kindly acknowledge Faculty and staff of West Virginia

University for their support.

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Background- Gasifier Sensing Needs: Online monitoring sensors of refractory used in coal gasifiers under

extreme conditions including high temperature (>1300oC) and high

pressure (up to 1000 psi) for >20,000 hr.

Erosive and corrosive conditions (due to slag and high pressure, in

addition to various pO2 levels) causes degradation of refractory over

time.

Ability to monitor the integrity of the refractory materials during

gasifier operation would contribute significantly to improving the

overall operational performance and reliability of coal gasifiers. Temperature

Stress/strain within refractory liner

Spallation events

Refractory liner health

Monitoring interior thermochemical conditions allows for efficient

control of the gasification process.

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Technology Vision:

Item A represents the smart

refractory material.

Item B is an interconnection(alignment) pin.

Item Cis an interconnection brick,

which will permit transfer of the

signal to the exterior wall.

Item D is the sealed electrical

access port to connect to the

signal acquisition/processing units.

Item Eis low-power electronics

and wireless communication.

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1) Investigate chemical stability, thermomechanical properties, and electrical

properties of refractory ceramic composites at temperatures between 750-

1450C.

2) Define processes to pattern and embed the conductive ceramic composites

within refractory materials to incorporate temperature and strain/stress

sensors into refractory bricks.

3) Develop methods to interface the electrical sensing outputs from the smartrefractory with an embedded processor and to design a wireless sensor

network to efficiently collect the data at a processing unit for further data

analysis.

4) Develop algorithms for model-based estimation of temperature profile in the

refractory, slag penetration depth, spallation thickness, and resultant health

by using the data from the wireless sensor network.

Program Objectives:

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Task Assignments:

Task 2: Fabrication and Characterization of

Oxide-Silicide Composites.

Task 3 and Task 4: Sensor Patterning and

Embedding and Static and Dynamic Sensor

Testing.

Task 5: Data Ex-Filtration Using a Wireless

Sensor Network.

Task 6: Model-Based Estimation of Refractory

Degradation/Temperature.

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Task 2:

Fabrication and Characterization of

Oxide-Silicide Composites.

(Sabolsky)

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Task 2.0 Objectives:

Investigate chemical stability, thermomechanical

properties, and electrical properties of refractory

silicide-oxide composites at temperatures between

750-1450C.

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10

Silicide/Oxide Stability (XRD):

Al2O3 Y2O3 ZrO2 Cr2O3

MoSi2MoSi2, Al2O3, Mo5Si3,

SiO2

MoSi2, Y2O3, SiO2,

Y5Mo2O12, Mo3Si, Mo3OMoSi2, ZrO2, Mo5Si3

MoSi2, Cr2O3,

Cr3Mo, SiO2

WSi2 WSi2, Al2O3, W5Si3 WSi2, Y2SiO5, WO2, SiO2 WSi2, ZrO2, W5Si3 WSi2, Cr2O3, SiO2, W3O

ZrSi2 ZrSi2, Al2O3, ZrO2, SiO2 ZrSi2, Y2O3, Y2Si2O7, SiO2 ZrSi2, ZrO2, SiO2ZrSi2, Cr2O3, ZrSiO4,

Cr3O, SiO2

TaSi2TaSi2, Al2O3, Ta5Si3,

Ta3Si, SiO2

TaSi2, Y2SiO5, Ta2O5,

Y10Ta4O25 TaSi2, ZrO2, Ta5Si3, SiO2TaSi2, Cr2O3, CrTaO4,

Ta2O5, TaO2

NbSi2 NbSi2, Al2O3, Nb5Si3NbSi2, Y2O3, Y2SiO5,

Nb5Si3, SiO2NbSi2, ZrO2, Nb5Si3, SiO2

NbSi2, Cr2O3, Nb5Si3,

CrNbO4, CrNbSi, SiO2

TiSi2 TiSi2, Al2O3, Ti5Si3, SiO2TiSi2, Y2O3, Y2Si2O7,

TiO2, SiO2TiSi2, ZrO2, TiO2, SiO2

(Cr0.88Ti0.12)2O3,

Cr3Si, SiO2

CrSi2 CrSi2, Al2O3, Cr5Si3 CrSi2, Y2O3, Y2SiO5 CrSi2, ZrO2 CrSi2, Cr2O3, Cr3Si, SiO2

Metal silicides show high stability in Al2O3 and ZrO2 matrix only with formation of different type

of silicides (Mo5Si3, W5Si3, Ta5Si3, Nb5Si3, Cr5Si3) and SiO2 (highlighted).

They partially react with Y2O3 and Cr2O3 to form undesired secondary phases.

* Prepared via mixed oxide route followed by sintering in Argon atmosphere at 1400-1600C.

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Silicide/Oxide Microstructure (SEM):(60-40) vol% MoSi2-Al2O3

(60-40) vol% WSi2-Al2O3

20 m

(60-40) vol% MoSi2-Y2O3

10 m

(60-40) vol% WSi2-Y2O3

10 m

(60-40) vol% MoSi2-ZrO2

3 m

(60-40) vol% WSi2-ZrO2

3 m

1 m Chemically etched in 1:1:1 HCl:HNO3:H2O

Secondary Phase

20 m

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0 100 200 300 400 500 600 700 800 900 100010

0

101

102

103

104

Conduc

tivity(S/cm)

Temperature (C)

(20-80) vol% MoSi2-Al

2O

3


2O

3

(60-40) vol% MoSi2-ZrO

2


2

12

Silicide/Oxide Properties:

CTE (100-1000C)

20 30 40 50 60 70 807.5

8.0

8.5

9.0

9.5

10.0

10.5

11.0

11.5

12.0

Alpha

(10-6K-1)

Volume Percentage of MoSi2

~ 9.65x10-6K-1

MoSi2-Al2O3 composites

20 30 40 50 60 70 807.5

8.0

8.5

9.0

9.5

10.0

10.5

11.0

11.5

12.0

Alpha(10-6K-1)

Volume Percentage of WSi2(%)

WSi2-Al2O3 composites

~ 9.41x10-6

K-1

4-point DC Conductivity (100-1000C)

Key Parameters: (1) metal silicide type and fraction, (2) mixedness or level of homogeneity, (3)

relative density, and (4) particle size of the metal silicide and refractory oxide.

0 100 200 300 400 500 600 700 800 900 100010

0

101

102

103

104

Conduc

tivity(S/cm)

Temperature (C)


2O

3

(60-40) vol% WSi2-Al

2O

3

(60-40) vol% TaSi2-Al

2O

3

(60-40) vol% TiSi2-Al

2O

3

0 100 200 300 400 500 600 700 800 900 1000

101

102

103

104

C

onductivity(S/cm)

Temperature (C)

MoSi2-Al

2O

3

WSi2-Al

2O

3

MoSi2-coarseAl

2O

3

TaSi2-Al

2O

3

TiSi2-Al

2O

3

MoSi2-ZrO

2

WSi2-ZrO

2

CrSi2-Cr

2O

3

MoSi2-based composites Silicide/Al2O3 composites

60/40 vol%

at ~ 1000C

(S/cm)

MoSi2-Al2O3 43.6

WSi2-Al2O3 26.7

WSi2-ZrO2 20.7

MoSi2-c.Al2O3 20.5

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Long-Term Stability of the Composites:

20 30 40 50 60 70 80 90

0

3000

6000

9000

12000

15000

18000

21000

24000

27000

30000

:

Mo5Si

3:Al2O3: MoSi2

Intensity(a.u.)

2 ()

Thermal Stability (1400C)

Sintered

24 hrs

48 hrs

20 30 40 50 60 70 80 90

0

3000

6000

9000

12000

15000

18000

21000

24000

27000

30000

: Mo5Si3: ZrO2: MoSi2

Intensity

(a.u.)

2 ()

Sintered

24 hrs

48 hrs

Grain Growth Kinetics (1400-1600C)

2

4

6

8

10

12

14

16

18

20

After Annealing

(1400C - 24h)

After Sintering

(1600C - 2h)

MoSi2GrainSize(

m)

Pure MoSi2

(60-40) vol% MoSi2-Al2O3

(60-40) vol% MoSi2-coarseAl

2O

3


2

Precursor

MoSi2Powder

MoSi2-Al2O3 composite

MoSi2-ZrO2 composite

Silicide/Al2O3 and silicide/ZrO2 composites are highly

stable at 1400C (up to 48 hrs).

Refractory oxides successfully retard the grain growth.

5 m 1 m

Pure MoSi2 MoSi2-Al2O3

Afterannealing

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Task 2 Conclusions and Future Work:

14

Metal silicides show high stability in Al2O3 and ZrO2 matrix(with occasional formation of sub-silicides).

Electrical conductivity of composites characterized with

various silicide content consistent performance transferredto sensor design and fabrication task.

Alternative materials and designs (layered structure) willbe investigated to prevent the reaction between

silicide/oxide composites and Cr2O3.

Process parameters will be optimized by correlating the

degree of distribution (D index) with the physicalproperties of the composites (conductivity) at high

temperatures.

Future Work:

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Task 3: Sensor Patterning and

Embedding.(Sabolsky/HWI)

15

Task 4: Static and Dynamic Sensor Testingof Smart Refractory Specimens.

(Sabolsky/HWI)

*US Provisional Patent Number 61/941,159

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Task 3 Objectives:

To develop methods for patterning technology the ceramic

composites within the refractory matrix.

16

To test the electrical performance of the smart refractory

brick (with embedded thermocouple or thermistor sensors). To investigate corrosion/erosion kinetics in static and

dynamic tests on smaller prototype and full-size smart cups

and bricks (at WVU and HWI).

To implement and test methods for data collection on initialprototypes.

Task 4 Objectives:

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Examples of Sensor Preforms

General Smart Refractory Processing Method

Smart Refractory Fabrication:

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High-Temperature Thermocouple

Performance:

The thermocouple with composition MoSi2 //TiSi2 exhibited 34 mV at 1400 C

9

90 vol% silicide and 10 vol% oxide

Various thermocouplecompositions studied

at 1500 C

0 400 800 1200 1600

0

8

16

24

32

ThermoelectricVol

tage(mV)

Temperature (C)

WSi2// TaSi2

MoSi2// WSi2

MoSi2// NbSi

2MoSi2// TiSi3

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Long Thermocouple Preforms:

Long Thermocouple: [75-25] Vol% MoSi2-Al2O3//[75-25] Vol% WSi2-Al2O3laminated between alumina substrates and sintered at 1500 C, 2h in argon

and tested isothermally at 1350 C for 2 cycles in argon atmosphere

30 33 36 39 42 45 48 51 54 57 60 63 66

-1

0

1

2

3

4

5

6

7

8

9

10

0 3 6 9 12 15 18 21 24 27

0

150

300

450

600

750

900

1050

1200

1350

1500

Temperatu

re(C)

Time (hours)

Thermoelec

tricVoltage(mV)

5 h 10 h

1st

cycle 2nd

cycle

1350 C1350 C8.3 mV 8.43 mV

8

TC: [75-25] Vol% MoSi2-

Al2O3// WSi2-Al2O3

Temp. C Experiment Hold Time, h EMF, mV

1350 Cycle # 1 5 8.3

1350 Cycle # 2 10 8.43

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Sensor embedded

Cr2O3 refractory

brick

Monoliths of sensors were fabricated via tape casting, laminated and sintered

at 1500 C. These laminates were embedded in the Cr2O3 brick while slip

casting and co-sintered at 1500 C in Argon atmosphere.

Smart Refractory Microstructure:

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Embedded Thermocouple: Smart Chromia Brick

Long TC embedded Chromia Refractory Brick

Interfaced Smart Brick

Testing Smart Refractory Brick

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Thin Embedded TC Sensor

Sensor preform embeddedHWI high-chromia

formulation.

Sensor embedded belowopening to insert slag

composition for corrosion

testing.


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The temperature sensor (thermistor) with composition (60-40) vol%

MoSi2-Al2O3 embedded within the Cr2O3 refractory exhibited stable

behavior for more than 250 hours at 1350 Cin argon atmosphere.

Embedded Thermistor: Smart Chromia Brick

1.0

1.5

2.0

2.5

3.0

3.5

4.0

-10 30 70 110 150 190 230 270

Resistance(

)

Time (Hours)

1350 C

Thermistor embedded smart brick in the

testing furnace

Performance of thermistor [60-40] vol% MoSi2-Al2O3

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4/27/2016

Lignite CoalSintered sensor preform

Biscuit fired coal samples

(a)

Brick loaded with coal

(c)(b)

Various steps involved in the testing of smart refractory brick embedded

with [90-10] MoSi2-Al2O3thermistor and tested at 1350 C , 2h in Argon

23

Static and Dynamic Corrosion Tests:

(Currently On-going)

Lignite Coal Slag

44.3SiO2-5.26Fe2O3-17.5CaO-6.64MgO


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Loss of electrical connection to bricks during testing.

Metal lead delamination due to wetting limitations.

Phase oxide formation in locations that are not embedded causingdrift in response.

Current Issue: Brick Interconnection

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K-Type Thermocouple

Ag wire leads

Smart brick

Efforts are focusing on better understanding the issue and

developing the proper ceramic and/or metal connections.


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Task 3 and 4 Conclusions and Future Work:

Optimize method to interconnect to embedded sensors (in

order to stabilize sensor signal and sensor long-term response).

Investigate the corrosion/erosion kinetics of sensor embedded

refractory bricks in static and dynamic mode with slag.

Scale-up all sensor preforms and smart refractory brick for

FULL-TECHNOLOGY DEMO IN TASK 7.

25

All-ceramic thermocouple and thermistor preforms were

fabricated and successfully tested.

Smart high-chromia bricks were fabricated in collaboration

with HWI (both thermistors and thermocouples), and currentlygoing under test.

Future Work:

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Task 5:Data Ex-Filtration Using a Wireless

Sensor Network.

(Graham/Kulathumani)

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Task 5 Objectives:

To develop methods to interface the electrical

sensing outputs from the smart refractory with an

embedded processor To design a wireless sensor network to efficiently

collect the data at a processing unit for further data

analysis

27

SensorInterface

Circuit

WSN

Mote

Base

Station

Radio

Energy

Harvester

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Aim: To reliably collect data from the sensors embedded withinthe smart bricks and interface them to wireless sensor nodes forcommunication

Approach:

(i) Iterative approach to sensor interface circuitry in parallel withthe sensor development

a) Initial sensor interface circuitry using off-the-shelf circuitry

b) Move to integrated circuits for lower-power and more compactsolutions

(ii) Investigate energy harvesting using thermoelectric devices to

help power the sensor motes and interface circuitry

Electronics interfacing Approach:

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Custom Integrated Circuit:1. Cold-Junction Compensator

2. Thermocouple Amplifier

3. Capacitive Sensor

4. Thermocouple Amplifier V2

5. Wheat-Stone Bridge

12

3

45

20 30 40 50 60 70 80 90 100 110 120

20

30

40

50

60

70

80

90

100

110

120

Bridge Circuit Temperature vs Actual Temperature

Temperature(C)

Temperature(C)

Measured

Ideal

Within 2% accuracyResistance-Based Sensor

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Circuits for Thermocouple-Based Sensors:

Compensates for measurementerror at thermocouple coldjunction

Adds offset to thermocoupleinput to allow for the correcttemperature measurement

Greatly improves accuracy overa large range of temperaturevalues

0 500 1000 15000

500

1000

1500

TC Amplifier with CJC Offset

Temperature(C)

T

emperature(C)

Measured

Ideal

700 800 900 1000 1100 1200 1300 1400 1500-5

-4

-3

-2

-1

0

1

2

3

4

5Percent Error vs Temperature

Temperature(C)

Error(%)

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Circuits for Energy Harvesting:

Leverages COTS-based DC/DC convertercircuit (LTC3108)

Start-up Sequence shows the output ofThermoelectric Generator, LDO Regulator,

Storage Buffer, and VOUT. The Mote Experiment was done using a

TelosB. The results shown are 10 minutesinto the test. Once a minute, the TelosBturned on and was powered by the energyharvesting system for a 5 second radiotransmission.

Start-up Sequence

Mote Experiment: Testing Results

VOUT System Output

Storage Buffer Energy Storage Output

LDO Regulator Internal Regulator Output

TEG Thermoelectric Generator Output

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Base Station

Desktop/Laptop

Sensor1

Sensor2

Sensor3

Sensor4

MasterMote

Data In

CommandOut

Wireless sensor network overview:

Collect refractory sensor data over wireless medium

(data ex-filtration)

Enable remote configuration of parameters

(over-the-air programming)

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Assembled complete signal chain:

Smart bricks with embedded sensors were interfaced with

a wireless mote yielding a complete signal chain

comprising

the smart brick, resistance measurement / amplifier circuit,

and wireless data transmission.

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Verified wireless signal chain performance:

Wireless Sensor Network (WSN) data collected from smart

bricks by measuring voltage from ICs [bottom figure]

Resistance measured directly on Labview by connecting an

ADC probe [top figure]

Figures show similar trend, thus verifying correctness of

the wireless network based data collection

0 5 10 15 20 250

1

2

3

x 105

Time(h)

Resistance()

LabView Full Run

0 5 10 15 20 250

1

2

3

Time(h)

Output(V)

WSN Full Run

0 2 4 6 8 10 120

50

100

150

200

Time(h)

Resistance()

LabView Half Run

0 2 4 6 8 10 120

50

100

150

200

Time(h)

Resistance()

WSN Half Run

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Results on increasing scale of network:

Tested ability of sensor network protocol to handle largernetwork sizes

Evaluated sizes from 40-200 using a ns-3, a network

simulator

Customized collection tree protocol to periodic datacollection scenario

100% data reliability

Latency and message size grow linearly with network size

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The end to end signal chain for data collection system has beenimplemented and tested using actual smart brick prototypes

Sensors are interfaced with microcontroller + radio (motes)

Data collection protocol has been implemented

Visualization and sensor control interfaces have been

implemented

Scalability of network protocol was evaluated

Refinements to interface circuits to suit updated sensors

Model based data reduction techniques are being explored

This can help reduce data rate without compromising with

information required for analyzing system characteristics.


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Task 6.0:

Model-Based Estimation ofTemperature Profile and Extent of

Refractory Degradation.

(Bhattacharyya, Huang)

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Task 6 Objectives:

To develop algorithms for model-based estimation of

temperature profile in the refractory, slagpenetration depth, spallation thickness, and

resultant health by using the data from the wireless

sensor network

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Motivation:

Typical correlation based approaches are inadequate

Stiff temperature gradient along the refractoryresulting in a large temperature change along the

sensor length

Change in thermal and electrical properties over time

due to slag penetration

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Property Models:

In order to build the model of smart refractory , severaltemperature-dependent property models for refractoryor sensor material are needed:

Specific heat

Emissivity

Thermal conductivity

Electrical conductivity

Thermal expansion

Dielectric constant

Youngs modulus

Poissons ratio

*Hensler J R, Henry E C. Electrical Resistance of Some Refractory Oxides and Their Mixtures in the

Temperature Range 600 to 1500 C[J].Journal of the American Ceramic Society, 1953, 36(3): 76-83

The electrical resistivity model for refractory*

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Property Models for Composite:

The properties of refractory will change as the slagpenetrates into the wall. These models can be usedto predict the effective properties of a special kind of

composite(slag and the refractory).

Specific heat

Thermal conductivityDielectric constant

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Thermal Model of a Gasifier Wall:

2-D heat conduct equation was used:

1

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Slag Penetration Model:Velocity of capillary flow through the horizontal pores (Washburn, 1921)

Corrected by porosity and tortuosity of the refractory pore system.

(Williford et al., 2008)

Velocity of slag penetration

decreases quickly

Temperature gradient

Williford, R. E.; Johnson, K. I.; Sundaram, S. K.; Pilli, S. Effective diffusivity and spalling models

for slagging coal gasifiers. J. Am. Ceram. Soc. 2008b, 91, 4016-4022.

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Sensor Models:

Five different types of sensors:

Interdigital capacitor (IDC)

Strain gauge

Resistive circuit

Thermistor

thermocouple

Strain

gauge

Resistive

circuit

sensor

Thermistor or

thermocouple

Interdigital

capacitor

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Interdigital Capacitor (IDC) Sensor Model:

* Igreja R, Dias C J. Analytical evaluation of the interdigital electrodes capacitance for a

multi-layered structure[J]. Sensors and Actuators A: Physical, 2004, 112(2): 291-301.

Sensitivity to slag penetration

Composite property

model

Slag can only fill the

pores

4.00E-12

4.20E-12

4.40E-12

4.60E-12

4.80E-12

5.00E-12

0 0.005 0.01 0.015 0.02

Capacitance(F)

Distance (m)

0 vol% slag

5 vol% slag

10 vol% slag

15 vol% slag20 vol% slag

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Estimation:

Methods: Traditional Kalman Filter (TKF)

Linear process model

Computationally cheap Less accuracy for highly nonlinear process

Extended Kalman Filter (EKF)

Nonlinear process linearized at every time step

Computationally costlier than TKF

Higher accuracy than TKF for nonlinear process

Unscented Kalman Filter (UKF)

Nonlinear process Computationally expensive

Superior accuracy

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Filt Al ith


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Filter Algorithm:

Differential Algebraic Equations System

Nonlinear differential algebraic equations (DAE) system: ,

0 ,

Developed approach for handling the DAE System:

Linearized process model:

0

Augmented form:

0

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f


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Estimation of Temperature Using EKF:

Temperature Estimation for Different

Extent of Slag Penetration are completed

Assume five IDC sensors are embedded

diagonally in the refractory brick.

Estimation of capacitance

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E ti ti f T t U i UKF


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Estimations of Temperature Using UKF:

Assuming five IDCsensors are embedded

diagonally in the

refractory brick

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Estimations of Extent of Slag Penetration


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Estimations of Extent of Slag Penetration

Using UKF: Temperature is assumed

to be under the normal

operating conditions

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51


Nonlinear filtering algorithms have been developed

to estimate temperature and the extent of slag

penetration. The filters have been tested by using thedata from the model of gasifier wall.

Future work will focus on validation and testing ofdeveloped models and filtering algorithms using

experimental data.

4/27/2016

Products:


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52

1. Edward M. Sabolsky, R. Chockalingam, K. Sabolsky, G. A. Yakaboylu, O. Ozmena, B. Armour,

A. Teter, D. Bhattacharyya , David Graham , Vinod Kulathumani, Close Timothy and MarcPalmisiano, Refractory Ceramic Sensors for Process and Health Monitoring of Slagging

Gasifiers, 227th ECS Meeting- Chicago, Illinois, USA, May 28th, (2015).

2. Edward M. Sabolsky , R. Chockalingam, K. Sabolsky, G. A. Yakaboylu, O. Ozmen, B. Armour,

A. Teter, D. Bhattacharyya, David Graham, Vinod Kulathumani, Close Timothy and Marc

Palmisiano, Conductive Ceramic Composites Used to Fabricate Embedded Sensors for

Monitoring the Temperature and Health of Refractory Brick in Slagging Gasifiers, XIVthInternational Conference European Ceramic Society- Toledo, Espana 24th June, 2015

3. R. C. Pillai, E. Sabolsky, K. Sabolsky, G. Yakaboylu, B. Armour, J. Mayer, J. Bogan, M.

Raughley and J. Sayre Performance of high temperature ceramic-ceramic thermocouples

embedded within chromia refractory bricks to monitor the health and stability of industrial

gasifiers Materials Science and technology MS&T2015, Oct 4-8, 2015, Greater ColumbusConventional Center, Columbus, Ohio, USA.

4. G. Yakaboylu, R. C. Pillai, B. Armour, K. Sabolsky, E. Sabolsky,Development of Refractory

Oxide/Metal Silicide Composites for High Temperature Harsh-Environment Sensor

Applications,Materials Science and technology MS&T2015, Oct 4-8, 2015, Greater Columbus

Conventional Center, Columbus, Ohio, USA.

5. G.A. Yakaboylu, R. C. Pillai, B. Armour, K. Sabolsky and E. M. Sabolsky, ConductiveCeramic Composites for Fabricating High Temperature and Harsh Environment Sensors:

Thermal Processing, Stability and Properties, International Conference and Exposition on

Advanced Ceramics and Composites, January 24-29, 2016, Daytona Beach, Florida, USA.

Products:

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Products:


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6. R.C. Pillai, G.A. Yakaboylu, K. Sabolsky and E. M. Sabolsky,J. Bogan, J. Sayre,

Composite Ceramic Thermocouples for Harsh-Environment Temperature

Measurements,International Conference and Exposition on Advanced Ceramics and

Composites, January 24-29, 2016, Daytona Beach, Florida, USA.

7. E. M. Sabolsky, R. C. Pillai, K. Sabolsky, G. A. Yakaboylu, B. Armour, A. Teter, M.

Palmisiano and T. Close, Refractory Ceramic Sensors for Process and HealthMonitoring of Slagging Gasifiers,ECS Trans., Vol 66(37) pp 43-53 (2015).

8. B. Rumberg, D. Graham, S. Clites, B. Kelly, M. Navidi, A. Diello, V. Kulathumani,

RAMP: Accelerating Wireless Sensor Design with a Reconfigurable Analog/Mixed-

Signal Platform, Proceedings of the ACM/IEEE Conference on Information

Processing in Sensor Networks (ISPN15), pp. 47-58, Seattle, WA, April 13-16, 2015.

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Appendix:

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Thermocouple Microstructures:


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55

Thermocouple Microstructures:Microstructure of ceramic-ceramic thermocouples sintered at 1500 C in argon

The SEM micrographs clearly shows that the thermocouples are fully dense and hence

improves the conductivity

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Image Analysis for Distribution (SEM):


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56

g y f ( )Proposed Method: Determination of coefficient of variation as a measure of the degree of

distribution (D index) by measuring distances between all neighboring silicide grains.

Binary imageOriginal image

,

,

,

,

, , , ,

5 m0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

Dindex

Number of lines analyzed

(60-40) vol% WSi2-Y

2O

3

(60-40) vol% MoSi2-Al2O3

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Silicide Thermocouples:


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The emf generated between hot junction

J1 and cold junction J2 in material A

( ) ( )dTTdTTET

T

B

T

T

AAB +=2

1

1

2

Seebeck coefficients

Silicide Couples

Material S500(V/C) Reference

MoSi2 -3.0 T. Nonomura (2011)

WSi2 -0.3 T. Nonomura (2011)

TaSi2 14 Kenneth Kreider (1995)

TiSi2 20.8 Kenneth Kreider (1995)

Pt -3.3 Kenneth Kreider (1995)

0

5

10

15

20

25

30

35

0 500 1000 1500

Absolu

teThermoelectricV

oltage(mV)

Temperature Difference (

C)

Mo-Ti

W-Ti

Mo-Ta

W-Ta

Mo-W

(Mo or W)-Ti

(Mo or W)- Ta

Mo-W

Thermoelectric Voltage

B-Type = 8.96 mV at 1400 C

(Mo or W)- Ti silicide couples~ 30-34 mV at 1400 C

Mo-W silicide (most

oxidation resistant) resulting

only~ 4mV at 1400 C

CrSi2- based couples wouldperform nicely ( = 200

V/K) but melts at 1470 C

p

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Embedded Thermocouple Preform:


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Organic Binder Vehicle

Ultrasonic mixing

Screen printing

Curing at 50 C

Sintering at 1500 C for 2 h. in Ar. atmosphere

Composite

Powders

Dispersant

(Solvents and Dispersants)

Tape casted, laminated

and laser cut aluminagreen substrates

Embedded Thermocouple Preform:

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Ceramic Thermocouple Performance:


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TiSi2// WSi2 exhibited 20 mV at 800 C

Preforms and laminated forms of ceramic

thermocouples heated at 1500 C and

performance is evaluated at 1000 C.

(High-temperature measurements)

1. [90-10]WSi2-Al2O3//[90-10]TaSi2-Al2O32. [90-10WSi2-Al2O3//[90-10] MoSi2-Al2O3

3. [90-10]MoSi2-Al2O3//[90-10] ZrSi2-Al2O34. [90-10]WSi2-Al2O3// [90-10] ZrSi2-Al2O35. [90-10]NbSi2-Al2O3//[90-10] MoSi2-Al2O36. [90-10] TiSi2-Al2O3//[90-10] WSi2-Al2O3

0 200 400 600 800 1000

0

5

10

15

20

25

Thermoelectric

Voltage(mV)

Difference in Temperature (C)

WSi2// TaSi2

WSi2// MoSi2

MoSi2// ZrSi2

WSi2// ZrSi2

NbSi2// MoSi

2 TiSi2// WSi2

(Type B= 3.15 mV at 800C)

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Thermocouple Microstructures:


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4/27/2016 60

20 40 60 80 100 120

Angle 2 (Deg)

[90-10] MoSi2-Al2O3

Al2O

3MoSi

2

[90-10] NbSi2-Al2O3

[90-10] TaSi2-Al2O3

Intensity(A.U.)

[90-10] TiSi2-Al2O3

[90-10] WSi2-Al2O3

X-ray analysis of various ceramic-ceramic thermocouples sintered at 1500 C in Ar

Ceramic Testing Stress/Strain Sensors:


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Ceramic Testing Stress/Strain Sensors:

Introduce 10% oxygen flow into furnace during burnout of imbeddedsensors to eliminate carbon deposits

Texture substrates in the gripper area to prevent slipping during testing

Amend sensor design to increase Gauge Factor

Evaluate temperature effects on strain sensor

Initiate compressive testing of ceramic strain sensors

55.0

0mm

40.0

0mm

0.50 mm

0.50 mm

55.0

0mm

40.0

0mm

1.00 mm

1.00 mm

A B C(mm) (mm) (mm)

V3 40 1.0 1.0

V4 40 0.5 1.0

V5 40 0.5 0.5

V6 40 0.2 1.0

V7 40 0.2 0.5

Design ID

A Sensor length

B Spacing between legs

C Leg width Design: V3 Design: V5

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Embedded Thermocouples Performance:


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Thermocouple was embedded within the Cr2O3 refractory and was

tested from room temperature to 1200 C in argon atmosphere.

Demonstrated half of predicted voltage, indicating some reaction

or change in junction circuit.

Pt lead

TC embedded Cr2O3 refractory

brick

[90-10] vol% MoSi2-Al2O3 // TaSi2-Al2O3

0 300 600 900 1200

0

2

4

6

8

38-114-11 Thermo Couple[90-10] vol% MoSi2-Al2O3//TaSi2-Al2O3

Thermoelectric

Voltage(mV)

Temperature (C)

Thermocouple

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Thermistor Preforms:

M Si Al O b d ll th i t


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Addition of MoSi2 decreased the resistance of MoSi2-Al2O3composite thermistors[50-50] MoSi2-Al2O3exhibited 786.50 and [90-10] MoSi2-Al2O3exhibited 10.76

resistance at 1100 C respectively

MoSi2-Al2O3 based small thermistors

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Static Cup Corrosion Study of Smart Brick:L b Vi D WSN D t


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0

5

10

15

20

25

30

0

300

600

900

1200

1500

4 9 14 19

R

esistance,

k

Temperature,

C

Time, h

43-11 Brick # 10: [60-40] MoSi2-Al2O3 Empty Run11350 C

1100 C

1200 C 5h1h

1h

0

70

140

210

280

350

0

300

600

900

1200

1500

0 5 10 15 20 25 30

Resistance,

k

Temperature,

C

Time, h

43-11 Brick #10:[60-40] MoSi2-Al2O3 Sensor2: Slag Test

0

0.5

1

1.5

2

2.53

3.5

0 2 4 6 8 10 12 14 16 18 20 22 24Volts(ADC\Resistance)

Time, h

43-11 Brick#10:[60-40]MoSi2-Al2O3 Slag Test - WSN

Data Rail Out Points

Sensor hits the slag

0

1

2

3

4

4 6 8 10 12 14 16 18 20Volts(ADC\Resistance)

Time, h

43-11 Brick#10:[60-40]MoSi2-Al2O3Run 1 - WSN

Data Rail Out Points

The analytical test results (Lab View) of Brick #10: [60-40] MoSi2-Al2O3brick were correlated

with wireless data up to 1350 C isothermal hold and thereafter the data showed deviations.

This may be due to oxidation.

Lab View Data WSN Data

Sensor hits the slag

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Documents

Smart Refractory