1. ERA-NET ROAD ASCAM Asset Service Condition Assessment Methodology
Project results
ASCAM team, English version

2. DoRN (D): ”Framework for optimised asset management”
ERANET ROAD transnational research program “effective asset management meeting future challenges”
DoRN (D): ”Framework for optimised asset management”
Project: Asset Service Condition Assessment Methodology (ASCAM)
This project/programme was initiated by ERA-NET ROAD, a project funded by the European Commission
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3. Partners in ASCAM
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4. How to use this presentation
These 70 slides present all Work Packages of the ASCAM project
Background information can be found in the ASCAM reports
Before presenting, an appropriate subset for the specific occasion and aidience must be made and prepared.
Good luck!
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5. Aim of ASCAM Framework From measure to network performance
Performance from a ”user perspective”
Connected to exisiting knowledge, tools, practices, etc.
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6. Project result Example: “proof of principle”
Including but not limited to:
Foundation, pavement, joint, bridge
Periodical inspection, repair, traffic management measure
Cost including risk, cost of queues, environmental issue (e.g. CO2)
Open to input from other software
NOT
Translation from e.g. CO2 to Euros (political issue) => assumptions
Automated software tool
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7. Project organisation
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8. Framework principals Measures
Improving conditions (performance indicators)
Value (user perspective, EUSL)
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9. Performance indicators
Definitions
Performance indicators
Physical characteristics indicating the condition
End Users
Stakeholders with a specific interest in the road network
EUSL (end user service level)
Characteristics indicating the interest(s) of specific End Users
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10. Bottom up P Pavement PI’s: Measurement possible Predictions available
evaluation of PI is performed according to national specifications,
the KPIs that are used by NRAs may be wholly different between countries,
PIARC’s recommendations for KPI’s may be implemented
Measurement possible
the measuring equipment is not standardized,
the measured values are mostly not comparable even for the same technical parameters and/or indices.
Predictions available
A pavement maintenance tool is used in most EU Countries - it differs from country to country, (national guidelines),
minimum levels for conditions – primarily safety and comfort - are set as trigger values,
predictions of material degradation are implemented for maintenance strategy,
parameters such as traffic density, environmental parameters (noise, small particles) are not explicitly considered in pavement management systems.
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11. Bottom up P Measures known Cost information available
maintenance measures depend on local tradition and construction techniques
Cost information available
database on direct costs of maintenance measures is avaialble (needs to be constantly updated),
indirect costs such as social costs (congestion, safety) are not usually implemented
direct relationships between pavement performance indicators and end user service levels have not yet been established.
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12. BMS
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13. BMS - Condition grading
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14. Different bridge condition rating in different countries
Austria
Croatia
Slovenia (MOST)
Norway
France
Grade
Condition
Class 1
Very good
No damage 5
Small damage
Good overall state 2
Good I
Smaller defects from construction period. 4
Medium damage
Minor structural damage. Non urgent maintenance needed 3
Satisfactory II
Smaller defects from exploitation period.
Large damage 2E
Minor structural damage. Urgent maintenance needed.
Faulty
III
Defects that in long term decrease durability
Bad
Critical damage
Structure deterioration. Non urgent maintenance needed IV
Defects that in foreseeable future can decrease reliability
Critical
Defects are categorized by using the following system of letters and numbers and combined with the above classes: M=Environment, B=Load capacity, T=Traffic safety, V=Maintenance cost. 3U
Serious structure deterioration. Urgent maintenance needed. V
Defects that present serious danger to safety of traffic
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15. Different bridge condition rating in different countries
Austria
Croatia
Slovenia (MOST)
Norway
France
No clear correlation between component (element) condition rating and object (structure as a whole) condition rating.
Structure level condition is not determined from the above classes but from the influence of each elements functionality on traffic safety, mechanical resistivity, stability, durability and general condition of element. Structural level is then determined by combining maximum elements level grades.
Bridge condition is calculated as a sum of individual elements damage rating.
The element condition is related to the number of years before maintenance is needed, and the condition rating is not levelled. The structure condition is quantified by calculating a character using condition from the element condition.
For the structure level condition rating number of levels and categories are the same as for element level: 5 levels, 1, 2, 2E, 3 and 3U, and the structure level is the maximum of all element levels.
PREDICTION OF BRIDGE AGEING
Probabilistic (details given in Task 1 report).
None
Probabilistic in nature (Poisson’s function is used)
Grades/Classes and conditions are not comparable between themselves for different countries in this table.

16. Slovenian case study
Degradation curves on the diagram were developed through Slovenian case study

17. Croatian case study
Maintenance costs curve was shown on diagram was developed through Croatian case study. It shows rise of costs through time with only regular maintenance performed through the years

18. Key performance indicators
Some of possible applicable single key performance indicators for bridges which effect the end users where developed in ASCAM and are presented in the following table
SINGLE KEY PERFORMANCE INDICATORS FOR BRIDGES WHICH EFFECT ON THE END USER
(TECHNICAL AND NON-TECHNICAL PERFORMANCE INDICATORS)
SERVICE LEVEL KPIs
ENVIRONMENTAL KPIs
SOCIO AND ECONOMIC KPIs
Everything that causes any kind of distress for the end user
Everything that effects the environment
Everything that has social and economic influence on the end user
MEASURABLE PARAMETERS
VIBRATION
NOISE
DEGRADATION OF CONCRETE
AIR QUALITY
VIOLATION OF NATURAL SURROUNDINGS
ENERGY CONSUMPTION
Influence on the AADT – average annual daily traffic
ECONOMICAL DEVELOPMENT OF THE AREA
LIFE CYCLE COST
UNMEASURABLE PARAMETERS OR PARAMETERS THAT ARE DIFFICULT TO MEASURE
PSYCHOLOGICAL INDICATORS OF DISTRESS
VIOLATION OF FLORA AND FAUNA
EFFECT ON SURFACE AND GROUND WATER
EUTROPHICATION
RELEVANT TRAFFIC LOAD
TRANSPORT COST (direct)
LIFE OF TREATMENT
TRAVELLING TIME
INTENSIFYING OF INVESTMENTS IN MAINTAINING ROAD INFRASTRUCTURE
MIGRATION (goods, population)
INFLUENCE ON CULTURAL HERITAGE
PSYCHOLOGICAL INDICATORS OF INSECURITY
TRAFFIC SAFETY
REPAIR METHODS  TOTAL COSTS

19. Relationship between damage categories and three categories EUSL

20. Relationship between repair method for a certain damage category and three categories of EUSL

21. Conclusion
Condition assessment methodology is mainly still based on subjective observations of the person who has performed condition assessment
Experience from existing management practices (data about condition in relation to MR&R costs) is in majority not used for prediction of future performance (importance of credible and reliable data base)
Performance indicators (PIs) are not uniquely defined
Three categories of PIs structural safety (load-bearing capacity), serviceability (traffic safety) and durability.
Although optimization techniques may be on a high level (with probabilistic approach) but they are still relying on very subjective condition assessment data.
Relationships between maintenance measures, bridge condition and end-user service levels are not established in current practices and need to be further researched.

22. Road equipment Road markings Road studs Delineator posts Fixed signs
Variable message signs
Road lighting
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23. The usefulness of road equipment
Almost every type of road
equipment is used to clarify
the road environment.
Therefore, it is important that
the performance is satisfactory,
which most often means that it
must have or imply good visibility.
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24. The task of road equipment
The main task of road equipment is
to maintain an end-user service level
which leads to acceptable
traffic safety
accessibility
comfort
Unfortunately, these three concepts
may counteract.
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25. Effect of road equipment
Effect of/on
Traffic safety
Accessibility
Comfort
Road markings
+, ± or - +
Road studs
Delineator posts
± or -
Fixed signs
VMS
Road lighting
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26. Monitoring Road marking retroreflectivity
can be monitored using a mobile
physical measurement method.
Other types of road equipment, like
colour and retroreflectivity of road signs,
illumination from road lighting and
luminance of variable message signs,
can be monitored using hand-held
instruments. .
Mobile reflectometer
Colour meter
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27. Use of data
Generally, physical data is stored for later decision of future maintenance measure.
Most often, this decision is based on
subjective considerations and experience.
However, lately a statistical model used for prediction of road marking retroreflectivity has been developed.
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28. Road marking management system
AGE Age of the road marking
MTL Material (thermoplastic, sprayplastic or paint)
CTR Contractor who has applied the road marking
Development of
a statistical model
Data monitoring
Prediction of
future
performance
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29. Maintenance measures In most cases, maintenance means replacement
of the road equipment in question, which means
that EUSL is restored to its initial value.
Some types of expensive equipment, like
variable message signs, may be repaired.
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30. Costs The costs for maintenance of road equipment is almost impossible
to estimate, as it is strongly dependent
on the environment where it is used in.
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31. Framework Principles Network / part of Network Assets in network
Components of assets
Aspects of components
Conditions w.r.t. different aspects
Physical decompositions
Asset management systems
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32. Framework Principles Network / part of Network Performance of network
Assets in network
Components of assets
Aspects of components
Conditions w.r.t. different aspects
Performance of network
EUSLs involved
Aspects involved
Components involved
conditions
Diversity
Stakeholders dependent
Drivers, owners, politicians, inhabitants
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33. Framework Principles Network / part of Network Performance of network
Assets in network
Components of assets
Aspects of components
Conditions w.r.t. different aspects
Degradations
Traffic growth
Changes in user demand
Uncertainties
Performance of network
EUSLs involved
Aspects involved
Components involved
conditions
Evolutions in Time
Loss of conditions
Loss of EUSLs performance
Increase in societal costs
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34. Framework Principles Network / part of Network Measures
Optimized w.r.t. EUSLs
Proactive
Cross Asset
Uncertainties
Network / part of Network
Assets in network
Components of assets
Aspects of components
Conditions w.r.t. different aspects
Measures
Components
Triggered by aspect conditions
Agency and societal costs
Performance of network
EUSLs involved
Aspects involved
Components involved
conditions
Evolutions in Time
Decrease of conditions
Loss of EUSLs performance
Increase in societal costs
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35. Managerial as well as technical view Network and CROSS-ASSET
Framework Principles
EUSLs into focus
Managerial as well as technical view
Network and CROSS-ASSET
Pro-active maintenance
Predictive models
Societal costs versus budgets
Uncertainties and monitoring
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36. Demonstrator
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37. Example E2020 2 lane highway 40 years 50 million vehicles/y.
2% annual traffic growth
1% financial discount rate
10 intervention measures
0,5 km pavement
foundation
top layer
0,5 km bridge
columns,
girders
slabs
pavement (top layer)
Road equipment
road markings
road studs
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38. Demonstrator
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39. Demonstrator
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40. Demonstrator
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41. Network and CROSS-ASSET
Demonstrator
Network and CROSS-ASSET
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42. E2020 scenarios Scenario 1: condition based maintenance
interventions as condition below absolute minimal acceptable level.
Costs: extra costs for ‘unplanned’ measures
Scenario 2: preventive maintenance scenario
intervention years defined according to acceptable user defined condition values (estimated condition based).
Cost: ‘planned’ measures
Scenario 3: preventive maintenance scenario
interventions with fixed returning period (time based).
cost:‘planned’ measures
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43. Demonstrator
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44. Demonstrator
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45. Network and CROSS-ASSET Pro-active maintenance Predictive models
Demonstrator
Network and CROSS-ASSET
Pro-active maintenance
Predictive models
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46. Demonstrator
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47. Demonstrator
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48. Managerial as well as technical view Network and CROSS-ASSET
Demonstrator
Managerial as well as technical view
Network and CROSS-ASSET
Pro-active maintenance
Predictive models
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49. Demonstrator
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50. Demonstrator
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51. Managerial as well as technical view Network and CROSS-ASSET
Demonstrator
Managerial as well as technical view
Network and CROSS-ASSET
Pro-active maintenance
Predictive models
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52. Demonstrator
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53. Demonstrator
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54. Managerial as well as technical view Network and CROSS-ASSET
Demonstrator
EUSLs into focus
Managerial as well as technical view
Network and CROSS-ASSET
Pro-active maintenance
Predictive models
Societal costs versus budgets
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55. Demonstrator
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56. Demonstrator
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57. Managerial as well as technical view Network and CROSS-ASSET
Demonstrator
EUSLs into focus
Managerial as well as technical view
Network and CROSS-ASSET
Pro-active maintenance
Predictive models
Societal costs versus budgets
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58. Demonstrator
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59. Demonstrator
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60. Managerial as well as technical view Network and CROSS-ASSET
Demonstrator
EUSLs into focus
Managerial as well as technical view
Network and CROSS-ASSET
Pro-active maintenance
Predictive models
Societal costs versus budgets
Uncertainties and monitoring
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61. Framework Framework main components: Asset decomposition
EUSL relevant ‘aspects’ = performance indicators
Condition and degradation description
List of measures, direct and indirect costs and the effect on the performance indicators
Relationship between the aspects (performance indicators) and the EUSL
A societal cost benefit model comprising the relevant EUSL.
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63. Top - Down EUSL: Accidents Hindrance (environment) Delay Air noise
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64. Bottom up P Pavement PI’s: Measurement possible Predictions available
transverse evenness
longitudinal evenness
macro-structure
cracking
surface defects
friction (skid resistance)
bearing capacity
Measurement possible
Predictions available
Measures known
Cost information available
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65. Bottom up B
Bridge
practical decomposition principals
systems to inspect and evaluate components and object
PI’s unclear, condition rating systems (very good – critical)
Measurements possible
Degradation curves available
Measures known
Cost information available
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66. Bottom up RE Road Equipment Inspection/monitoring/measure data stored
Measure: mostly replacement
Inspection techniques available
Life span predictions available
Rules and regulations available
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67. EUSL – PI’s Few relations are found so far,
First steps are being made and found feasible
In our opinion well-founded relations will inevitably become available:
Ongoing focus on functionality and end user perspective
Increase of data gathered through monitoring systems including improved registration
Leading to
Improved accessibility of such data
Research in this area
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68. Conclusions Framework is intrinsically:
Cross asset
Holistic
User perspective as the leading principal
Practical framework implementation possible:
Framework input available through existing MMS
Cross national “good practice” information exchange
PI – EUSL relations to be improved
Bridge functionality and PI’s to be further developed
Assessment of quality of input data with respect to practical decision support is needed
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69. Conclusions Change of mind set:
From “meeting technical criteria” to “negotiable decision support information”
Differentiation in minimal road condition requirements depending on EUSL (e.g. # of end users)
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70. Advantages Transparency of “political” choices in values (EUSL’s, €)
Long term risks included (expected values)
Cost – benefit analysis of (innovative) measures (monitoring, inspections, etc.) on a sound basis
Maintenance scenario comparison on a sound basis
Long term cost estimates, sound predictions of future consequences of current decisions
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71. Disadvantages Complexity Unknown relations, influencing the results
No clear rules, negotiable criteria, uncertainty clearly visible => consequences for decision making processes
Indirect cost estimates to be separately assessed
Explicit “policy factors” for EUSL’s (costs of delay, accidents, noise, air quality, etc.)
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