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[email protected] , [email protected] -- *Research Associate, School of Civil and Industrial Engineering, Sapienza Università di Roma Via Eudossiana 18 - 00184 Rome (ITALY) tel. +39-06-44585072 StroNGER S.r.l., Co-founder and Director Via Giacomo Peroni 442-444, Tecnopolo Tiburtino, 00131 Rome (ITALY) -- Informal Meeting on RESILIENCE Rome, 2-3 July 2014 School of Civil and Industrial Engineering University of Rome La Sapienza StroNGER StroNGER Structures of the Next Generation – Energy harvesting and Resilience C. Crosti, S. Arangio, F. Petrini *, K. Gkoumas, F. Bontempi www.stronger2012.com
34

StroNGER for Resilience in Rome

Aug 19, 2014

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Engineering

StroNGER2012

Presentation at the Resilience in Rome Meeting, July 2-3, 2014
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Page 1: StroNGER for Resilience in Rome

[email protected] , [email protected]

--

*Research Associate,

School of Civil and Industrial Engineering, Sapienza Università di RomaVia Eudossiana 18 - 00184 Rome (ITALY)tel. +39-06-44585072

StroNGER S.r.l., Co-founder and DirectorVia Giacomo Peroni 442-444, Tecnopolo Tiburtino, 00131 Rome (ITALY)--

Informal Meeting on RESILIENCE

Rome, 2-3 July 2014

School of Civil and Industrial Engineering

University of Rome La Sapienza

StroNGERStroNGERStructures of the Next Generation – Energy harvesting and Resilience

C. Crosti, S. Arangio, F. Petrini *, K. Gkoumas, F. Bontempi

www.stronger2012.com

Page 2: StroNGER for Resilience in Rome

What is StroNGER

Francesco Petrini. [email protected]

Page 3: StroNGER for Resilience in Rome

A spin-off research Company

Founded in November 2012

Operating in the civil and environmental engineering industry

Page 4: StroNGER for Resilience in Rome

Stro N

GERwww.stronger2012.com

From

No

vem

be

r 20

12

The research group of structural analysis and design at Sapienza Univ.

Page 5: StroNGER for Resilience in Rome

StroNGER – who we are

Franco Bontempi, PhDStroNGER srl, Scientific Advisor

Prof. of Structural Analysis and DesignSapienza University of Rome

Expertise:-Fire Safety Engineering

-Forensic Engineering

Expertise:-Structural Safety-Structural Identification

Expertise:-Wind Engineering-Performance Based Design

Chiara Crosti, PhDStroNGER srl, CEO

Francesco Petrini, PhDStroNGER srl, Vice Director

Stefania Arangio, PhDStroNGER srl, Director

Konstantinos Gkoumas, PhDStroNGER srl, Partner

Expertise:-Energy Harvesting-Dependability

Francesco Petrini. Co-founder and Director

[email protected]

Page 6: StroNGER for Resilience in Rome

Stro N

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Academic research Industry research R&D

University courses Professional courses

Big group Small group

Design consultant activityResearch experience in structural analysis

CONVERSION: StroNG points

Page 7: StroNGER for Resilience in Rome

StroNGER S.r.l.

a Spin-off Company (Small Medium Enterprise)

that operates in the Civil Engineering industry.

High-profile tools and methodologies that lead to structures that fulfill required

performances under a resilience and sustainability point of view.

StroNGER expertise: •Design and rehabilitation of Civil structures and infrastructures with regard to wind, earthquakes, waves, landslides, fire and explosions. •Disaster resilience assessment. •Advanced numerical modeling of Civil structures and infrastructures. •Forensic engineering.•Sustainability and Energy Harvesting in Civil structures and infrastructures.

StroNGER has been recently awarded by the European Space Agency with the space technology transfer permanent award

StroNGER S.r.l. was founded in 2012 by researchers from the academic world working in the civil engineering field, each one having more than 10 years of experience in the field

www.stronger2012.com [email protected]

Phone: +39 0644585070

Structures of the Next Generation – Energy harvesting and Resilience

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Energy Harvesting

Francesco Petrini. [email protected]

StroNGER forStructures of the Next Generation – Energy harvesting and Resilience

Page 9: StroNGER for Resilience in Rome

Energy Harvesting (EH) can be defined as the sum of all those processes that allow to capture the freely available energy in the environment and convert it in (electric) energy that can be used or stored.

Harvesting ConversionUse

Storage

Energy harvesting - Overview

Francesco Petrini. Co-founder and Director

[email protected]

Resources

Sun

Water

Wind

Temperature differential

Mechanical vibrations

Acoustic waves

Magnetic fields

Extraction systems

Magnetic Induction

Electrostatic

Piezoelectric

Photovoltaic

Thermal Energy

Radiofrequency

Radiant Energy

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Applications for the energy sustainabilityEH in buildings – a premise

10

• EH devices are used for powering remote monitoring sensors (e.g. temperature sensors, air quality sensors), also those placed inside heating, ventilation, and air conditioning (HVAC) ducts.

• These sensors are very important for the minimization of energy consumption in large buildings

Image courtesy of enocean-alliance®

http://www.enocean-alliance.org

Francesco Petrini. Co-founder and Director

[email protected]

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Page 11: StroNGER for Resilience in Rome

Francesco Petrini. Co-founder and Director

[email protected]

a. Steel plate (support)

b. Sensor transmitter module

c. Piezoelectric bender

d. Fin

e. Temperature probe

f. Tip mass

Proposal of space technology transfer for the design, testing, production and commercialization of a self-powered piezoelectric temperature and humidity sensor (PiezoTSensor), for the optimum energy management in building HVAC (Heating, Ventilation and Air Condition) systems.

PiezoTSensor ©

HVAC upper wall

HVAC lower wallHVAC lower wall

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Francesco Petrini. Co-founder and Director

[email protected]

PiezoTSensor ©R

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Air flow

Page 13: StroNGER for Resilience in Rome

Applications for the energy sustainabilityEnergy Harvesting for monitoring HVACs operating conditions

Currently:

•Power is provided by batteries or EH devices based on thermal or RF methods

•Sensors work intermittently (to consume less power ~ 100µW)

An EH sensor based on piezoelectric material has several advantages being capable to provide up to 10-15 times more power than currently used devices leading to additional applications or

longer operation time.

Image courtesy of enocean-alliance®

http://www.enocean-alliance.org

Francesco Petrini. Co-founder and Director

[email protected]

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Francesco Petrini. Co-founder and Director

[email protected]

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Vibration EH devices

Flow-induced EH devices

Applications for infrastructures

Page 15: StroNGER for Resilience in Rome

Resilience

Francesco Petrini. [email protected]

StroNGER forStructures of the Next Generation – Energy harvesting and Resilience

Page 16: StroNGER for Resilience in Rome

Francesco Petrini. Co-founder and Director

[email protected]

RISE – Concept resume

MCEER (Multidisciplinary Center for Earthquake Engineering Research), (2006). “MCEER’s Resilience Framework”.

-- = ordinary node

= critical node in case of emergency---

= principal link (e.g. road)

HOSPITAL

HOUSE AGGRGATE

MALL

SHOPPING CENTEROFFICE

HOUSE AGGRGATE

FIRE DEPARTMENT

NUCLEAR PLANT

HOSPITAL

HOUSE AGGRGATE

MALL

SHOPPING CENTEROFFICE

HOUSE AGGRGATE

FIRE DEPARTMENT

NUCLEARPLANT

= earthquake action

= blast action= fire action

Representation of a large infrastructure as a network of nodes and links

Nodes: relevant premises of the infrastructure Links: local and access roads, pipelines and supply system

Initial losses

Recovery time:• Resourcefulness• Rapidity

Disaster strikes

A

L0

(dQ/dt)0

LOCAL- LEVEL:Contribute of the single premise (e.g. hospital, by considering the interrelations with proximity elements)

NETWORK- LEVEL:- Convolution of the local-level contributes

dLi

Quantitative definition of Resilience (MCEER) R.I.S.E. Multiscale philosophy

Disaster strikes --> Hazard scenario

Page 17: StroNGER for Resilience in Rome

Francesco Petrini. Co-founder and Director

[email protected]

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RIS

E –

Fram

ew

ork

Load

Network Model for resilience

Multi-hazard Scenarios

Local Level

NetworkLevel

Local resilience indicators Network resilience indicatorsA

SSES

SMEN

T a

nd

MIT

IGAT

ION

(A

na

lysi

s fo

r ea

ch n

od

e a

nd

lin

k)

Scenario output before mitigation

Scenario output after mitigation

ResIStframework for resilience assessment

Structure performanceA

B Recovery

E.g. Repair time

Damage

Action

Damage/Disservice

% of rescued

Action values

IM

A

IM

100 %

People safetyB

Quality

Indicator

Status of nodes and links(no interaction)

A

Quality

Indicator

Interactions effects (quality drop)B

L0i TR

i

Quality (network level)

Combination of local indicators

Indicator

L0 TR

Resilience ∞ 1 /A

C

Local resilience indicators are evaluated for each node and Link and for each scenario

Network resilience indicators are evaluated for each scenario

---- = Output

---- = comment

Qua

lity

L0 = initial lossesTR = recovery time

Infrastructure representation

Hazard Analysis

Protection analysis

Performance analysis

Resilience Assessment

Network Level

1

2 System Recovery functionD

** Picture taken from:

Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.

Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282

Recovery analysis

**

3

RISE framework for resilience assessment

Page 18: StroNGER for Resilience in Rome

Francesco Petrini. [email protected]

Real application of the resilience conceptA strategic infrastructure for water supply (serving about 1,300,000 people)

Page 19: StroNGER for Resilience in Rome

19Francesco Petrini. Co-founder and Director

[email protected]

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Real application of the resilience conceptA strategic infrastructure for water supply (serving about 1,300,000 people)

Page 20: StroNGER for Resilience in Rome

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Seismic ActionFrancesco Petrini. Co-founder and Director

[email protected]

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Critical Node

Francesco Petrini. Co-founder and Director

[email protected]

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Page 22: StroNGER for Resilience in Rome

Energy and water supply infrastructure: representation

WU

WDHY

CBCR

CU

RETAINING WALL UP (WU) RETAINING WALL DOWN (WD) HYDROELECTRIC POWER STATION (HY)

CONDUIT UP (CU) CONDUIT ROSALBA

CONDUIT PAVONCELLI BIS

1

2

34

5

6

7

1 2 3

4 5 6

7

HYDRAULIC JUNCTION

ELECTRICITY

WATER

Infrastructure plan view Individuation of the system/network components Representation of the system

Outputs

Network Model for resilience

Multi-hazard Scenarios

NetworkLevel

Infrastructure representation

Hazard Analysis

1 Load

Network Model for resilience

Multi-hazard Scenarios

Local Level

NetworkLevel

Local resilience indicators Network resilience indicators

ASS

ESS

MEN

T a

nd

MIT

IGAT

ION

(A

nal

ysis

for

ea

ch n

ode

and

link

)

Scenario output before mitigation

Scenario output after mitigation

ResIStframework for resilience assessment

Structure performanceA

B Recovery

E.g. Repair time

Damage

Action

Damage/Disservice

% of rescued

Action values

IM

A

IM

100 %

People safetyB

Quality

Indicator

Status of nodes and links(no interaction)

A

Quality

Indicator

Interactions effects (quality drop)B

L0i TR

i

Quality (network level)

Combination of local indicators

Indicator

L0 TR

Resilience ∞ 1 /A

C

Local resilience indicators are evaluated for each node and Link and for each scenario

Network resilience indicators are evaluated for each scenario

---- = Output

---- = comment

Qu

alit

y

L0 = initial lossesTR = recovery time

Infrastructure representation

Hazard Analysis

Protection analysis

Performance analysis

Resilience Assessment

Network Level

1

2 System Recovery functionD

** Picture taken from:

Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.

Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282

Recovery analysis

**

3

RISE framework for resilience assessment

Francesco Petrini. Co-founder and Director

[email protected]

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Page 23: StroNGER for Resilience in Rome

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System with Elements connected in Parallel

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Damage at Local Level

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Damage at Element Level

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Damage at Structure Level

Page 27: StroNGER for Resilience in Rome

Energy and water supply infrastructure: scenarios

FLOW REDUCTION (U)FLOW REDUCTION (R)

ELECTRIC POWER INTERRUPTIONTOTAL FLOW INTERRUPTION (R+U)

Co

nse

qu

en

ce s

cen

ario

sNetwork Model for

resilience

Multi-hazard Scenarios

NetworkLevel

Infrastructure representation

Hazard Analysis

1 Load

Network Model for resilience

Multi-hazard Scenarios

Local Level

NetworkLevel

Local resilience indicators Network resilience indicators

ASS

ESS

MEN

T a

nd

MIT

IGAT

ION

(A

nal

ysis

for

ea

ch n

ode

and

link

)

Scenario output before mitigation

Scenario output after mitigation

ResIStframework for resilience assessment

Structure performanceA

B Recovery

E.g. Repair time

Damage

Action

Damage/Disservice

% of rescued

Action values

IM

A

IM

100 %

People safetyB

Quality

Indicator

Status of nodes and links(no interaction)

A

Quality

Indicator

Interactions effects (quality drop)B

L0i TR

i

Quality (network level)

Combination of local indicators

Indicator

L0 TR

Resilience ∞ 1 /A

C

Local resilience indicators are evaluated for each node and Link and for each scenario

Network resilience indicators are evaluated for each scenario

---- = Output

---- = comment

Qu

alit

y

L0 = initial lossesTR = recovery time

Infrastructure representation

Hazard Analysis

Protection analysis

Performance analysis

Resilience Assessment

Network Level

1

2 System Recovery functionD

** Picture taken from:

Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.

Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282

Recovery analysis

**

3

RISE framework for resilience assessment

Francesco Petrini. Co-founder and Director

[email protected]

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Page 28: StroNGER for Resilience in Rome

WU FAIL

HY FAIL?

CU FAIL?

Y

WU + WD +HY+ CU

TOTAL FLOW

TOTAL FLOW

TOTAL FLOW

NO R + E

CRFAIL?

WU

WU + WD

WU + WD + HY

WD FAIL?

N

N

N

Y

Y

N

N

N

N

CRFAIL?

CRFAIL?

CRFAIL?

NO R

NO R

NO U + E

NO U+ E + R

N

N

N

N

Y

Y

Y

Y

Fau

lt-T

ree

an

alys

is

Cri

tica

l se

rie

s o

f co

mp

on

en

ts

WU

WDHY

CBCR

CU

Energy and water supply infrastructure: scenarios

Network Model for resilience

Multi-hazard Scenarios

NetworkLevel

Infrastructure representation

Hazard Analysis

1 Load

Network Model for resilience

Multi-hazard Scenarios

Local Level

NetworkLevel

Local resilience indicators Network resilience indicators

ASS

ESS

MEN

T a

nd

MIT

IGAT

ION

(A

nal

ysis

for

ea

ch n

ode

and

link

)

Scenario output before mitigation

Scenario output after mitigation

ResIStframework for resilience assessment

Structure performanceA

B Recovery

E.g. Repair time

Damage

Action

Damage/Disservice

% of rescued

Action values

IM

A

IM

100 %

People safetyB

Quality

Indicator

Status of nodes and links(no interaction)

A

Quality

Indicator

Interactions effects (quality drop)B

L0i TR

i

Quality (network level)

Combination of local indicators

Indicator

L0 TR

Resilience ∞ 1 /A

C

Local resilience indicators are evaluated for each node and Link and for each scenario

Network resilience indicators are evaluated for each scenario

---- = Output

---- = comment

Qu

alit

y

L0 = initial lossesTR = recovery time

Infrastructure representation

Hazard Analysis

Protection analysis

Performance analysis

Resilience Assessment

Network Level

1

2 System Recovery functionD

** Picture taken from:

Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.

Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282

Recovery analysis

**

3

RISE framework for resilience assessment

Francesco Petrini. Co-founder and Director

[email protected]

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Page 29: StroNGER for Resilience in Rome

Load

Network Model for resilience

Multi-hazard Scenarios

Local Level

NetworkLevel

Local resilience indicators Network resilience indicators

ASS

ESS

MEN

T a

nd

MIT

IGAT

ION

(A

nal

ysis

for

ea

ch n

ode

and

link

)

Scenario output before mitigation

Scenario output after mitigation

ResIStframework for resilience assessment

Structure performanceA

B Recovery

E.g. Repair time

Damage

Action

Damage/Disservice

% of rescued

Action values

IM

A

IM

100 %

People safetyB

Quality

Indicator

Status of nodes and links(no interaction)

A

Quality

Indicator

Interactions effects (quality drop)B

L0i TR

i

Quality (network level)

Combination of local indicators

Indicator

L0 TR

Resilience ∞ 1 /A

C

Local resilience indicators are evaluated for each node and Link and for each scenario

Network resilience indicators are evaluated for each scenario

---- = Output

---- = comment

Qu

alit

y

L0 = initial lossesTR = recovery time

Infrastructure representation

Hazard Analysis

Protection analysis

Performance analysis

Resilience Assessment

Network Level

1

2 System Recovery functionD

** Picture taken from:

Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.

Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282

Recovery analysis

**

3

RISE framework for resilience assessment

Load

Local Level

ASS

ESSM

ENT

an

d M

ITIG

ATI

ON

(A

na

lysi

s fo

r ea

ch n

od

e a

nd

lin

k)

Structure performanceA

B Recovery

E.g. Repair time

Damage

Action

Damage/Disservice

% of rescued

Action values

IM

A

IM

100 %

People safetyB

Protection analysis

Performance analysis

2

Critical series of components: retaining walls

WU

WDHY

CBCR

CU

(0,0) (92,0)

(92,29)(0,29)

(0,54)

(0,62) (28.5,62)

(53,56)

(63,45)

(92,32)

(92,34)

Critical series of components

FE model

Page 30: StroNGER for Resilience in Rome

Interactions on seismic fragility

Load

Network Model for resilience

Multi-hazard Scenarios

Local Level

NetworkLevel

Local resilience indicators Network resilience indicators

ASS

ESS

MEN

T a

nd

MIT

IGAT

ION

(A

nal

ysis

for

ea

ch n

ode

and

link

)

Scenario output before mitigation

Scenario output after mitigation

ResIStframework for resilience assessment

Structure performanceA

B Recovery

E.g. Repair time

Damage

Action

Damage/Disservice

% of rescued

Action values

IM

A

IM

100 %

People safetyB

Quality

Indicator

Status of nodes and links(no interaction)

A

Quality

Indicator

Interactions effects (quality drop)B

L0i TR

i

Quality (network level)

Combination of local indicators

Indicator

L0 TR

Resilience ∞ 1 /A

C

Local resilience indicators are evaluated for each node and Link and for each scenario

Network resilience indicators are evaluated for each scenario

---- = Output

---- = comment

Qu

alit

y

L0 = initial lossesTR = recovery time

Infrastructure representation

Hazard Analysis

Protection analysis

Performance analysis

Resilience Assessment

Network Level

1

2 System Recovery functionD

** Picture taken from:

Decò A., Bocchini P., Frangopol D.M.. A probabilistic approach for the prediction of seismic resilience of bridges.

Earthquake Engineering and Structural Dynamics, Wiley, DOI: 10.1002/eqe.2282

Recovery analysis

**

3

RISE framework for resilience assessment

Local resilience indicators

Quality

Indicator

Status of nodes and links(no interaction)

A

Quality

Indicator

Interactions effects (quality drop)B

L0i TR

i

Local resilience indicators are evaluated for each node and Link and for each scenario

IM (g)

P(E

DP

|IM

)

WUWU WDWD++

Francesco Petrini. Co-founder and Director

[email protected]

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(0,0) (92,0)

(92,29)(0,29)

(0,54)

(0,62) (28.5,62)

(53,56)

(63,45)

(92,32)

(92,34)

WUWU

WDWD

Page 31: StroNGER for Resilience in Rome

Francesco Petrini. [email protected]

ONGOING: Real application of the resilience conceptStructural analysis of sea port defence structures for durability and robustness

Page 32: StroNGER for Resilience in Rome

ONGOING: Real application of the resilience conceptStructural analysis of sea port defence structures for durability and robustness

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ONGOING: Real application of the resilience conceptStructural analysis of sea port defence structures for durability and robustness

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“…. to provide, through innovation, advanced products and services for a sustainable and safe world.”

StroNGER – VisionR

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