MIT CSHub : Improving Decision-Making for Infrastructure Decisions

1. MIT CSHub: Improving Decision-Making for Infrastructure Decisions Randolph Kirchain CRMCA 2013 Fall Workshop November 14, 2013

2. CSHub by the numbers • History: Founded in 2009, Phase I is 5 yrs • Supported by: • People: • 11 principal investigators from 6 departments • 12 graduate students and postdoctoral researchers Ready Mixed Concrete Research & Education Foundation

3. CSHub Mission: Develop breakthroughs that will achieve sustainable and durable homes, buildings, and infrastructure Increase performance Reduce environmental impact Reduce cost

4. CSHub approach is holistic and multidisciplinary Research areas: Target audiences: Cement & concrete industries Designers & decision-makers

5. Infrastructure landscape is changing…CSHub research is enabling new perspectives…New perspectives create new opportunities.

6. Infrastructure landscape is changingNeed is critical and clear Global Infrastructure Quality America’s GPA: D+ $1.6 T CURRENT TREND $2.7 T FUTURENEED World Economic Forum 2013

7. Infrastructure landscape is changingCrises highlight need for new solutions

8. Infrastructure landscape is changingCrises highlight need for new solutions Climate change pumps up risk of severe storms Doyle Rice, USA TODAY 9:44 a.m. EDT September 24, 2013

9. Infrastructure landscape is changingNew issues influencing the debate Obama Outlines Ambitious Plan to Cut Greenhouse GasesBy MARK LANDLER and JOHN M. BRODER Published: June 25, 2013

10. Infrastructure landscape is changing…CSHub research is enabling new perspectives…New perspectives create new opportunities.

11. Seizing opportunities requires changing perspectives CSHub research is driving new perspectives

13. Lower initial costs often take precedence over lower future costs Roads Homes Automobiles Lower initial costs, but… • …higher maintenance costs • …higher recovery costs • …higher use costs

14. Why is life cycle thinking a low priority? There is a chasm between life cycle research and practice Life cycle analysis literature and tools Designers, consumers, policy-makers Typical reasons for not applying life cycle thinking: It is too hard/expensive There is limited demand This means it is a low priority

15. State DOTs have expressed concerns about LCCA Rangajaru et al. 2008, GAO 2013

16. Why is life cycle thinking a low priority? There is a chasm between life cycle research and practice Life cycle analysis literature and tools Designers, consumers, policy-makers Typical reasons for not applying life cycle thinking: It is too hard/expensive There is limited demand This means it is a low priority

17. CSHub Research is tackling both sides of this challenge Low Demand High cost Simplified tools Integration with existing design tools Case work with individual states to map into their existing processes • Case studies to show value • Communications to translate effective life-cycle management to successful financial risk management • Model of overall infrastructure savings potential

18. Uncertainty is pervasive in pavement LCCA Decisions long before construction Uncertainty & Risk Long life-cycle Uncertainty in unit construction costs Uncertainty in material price evolution Cash Flow Construction Operation Uncertainty in timing of M&R activities

19. CSHub LCCA research aims to leverage and extend • Leverage existing tools: • FHWA’s LCCA Technical Bulletin • FHWA’sRealCost tool • Extend existing methods: • Quantify sources of risk in infrastructure investment • Characterize drivers and trends around those risks • Strengthen link between design and LCCA tools

20. Effective long-term projections are plausible Price projections are created and validated using historical data Source: USGS • Effective Price Projections • Must be built from significant sets of data • Must be viewed as probabilistic in nature

21. Real Price Forecasting Models Concrete (Constituent Based) Asphalt (Constituent Based)

22. Probabilistic analysis provides insight on relative risks What is the risk of exceeding a specific life cycle cost? 1% 23% Average Difference 10%

24. Life Cycle Assessment:A tool for quantifying environmental impact • Quantify inflows and outflows • Characterize how inflows & outflows “change the world” Raw Materials Life Cycle Releases to Land Energy Air Emissions Processing Chemicals Water Effluents Product

25. Life cycle assessment of pavements Incorporating use phase in pavement LCA is a recent innovation • Pavement-Vehicle Interaction • Roughness • Deflection • Albedo • Carbonation • Lighting Scope includes all effects attributable to the pavement design. • Excavation • Landfilling • Recycling • Transportation • Extraction and production • Transportation Use • Onsite equipment Materials Construction End-of-Life/ Rehabilitation Maintenance • Materials • Construction

26. A life cycle perspective is vital for infrastructure decisions There are multiple mechanisms for reducing environmental impact across a structure’s life Prioritizing mechanisms requires a trade-off analysis of performance and life cycle environmental impacts and costs

27. Key drivers of Greenhouse Gas due to PVI PVI = Pavement Vehicle Interaction • Pavement Texture: Tire industry. Critical for Safety. Tire-Pavement contact area. • Roughness/Smoothness: • Absolute Value = Vehicle dependent/Suspension. • Evolutionin Time: Material Specific • Maintenance & Rehab by State Agencies • Deflection/Dissipation Induced PVI: • Critical Importance of Pavement Design Parameters: Stiffness, Thickness matters! • Speed and Temperature Dependent, specifically for inner-city pavement systems (Think LA!)

28. Extra fuel consumption from PVI is significant Estimate of US road network extra fuel consumption from PVI

29. Use phase can be a significant fraction of pavement environmental impact Example: Global warming potential of an urban interstate in Missouri Use Use phase drivers are highly dependent on pavement design and context *Other: carbonation, lighting, albedo

30. Our communities’ well-being exposed to the whims of physics? Key challenge: complexities of cities, systems approach

31. Resilience is a systems concept …but there is a need for quantitative methods to support resilience decisions at several scales (homes  communities) Structural Resistance Renschler, C. S., et al. "Developing the ‘PEOPLES’ Resilience Framework for defining and measuring disaster resilience at the community scale." Proceedings of the 9th US National and 10th Canadian Conference on Earthquake Engineering (9USN/10CCEE). 2010.

32. Quantitative Resilience: Addressing Complexity City Texture Akin to Molecular Complexity Top View of Cambridge via GIS Data Polycrystalline Material at Nanoscale Urban Physics: Use tools of molecular physics to capture complexity of cities

33. GLOBAL WARMING of CITIES WIND FLOW THROUGH CITIES Toward Quantitative Resilience CHICAGO (Crystal) Buildings NY (Glass) CHICAGO (Crystal) NY (Glass) LA (Liquid) The “windy” city Liquid trapping Each point represents a US City = Temperature difference between inner-city and outside CITY TEXTURE DRIVES MUCH OF LIQUID TRAPPING (Smog, Storm,…) CITY TEXTURE DRIVES MUCH OF HEAT TRAPPING

34. Incorporate the cost of damage due to hazards intolife cycle cost framework Quantitative resilience for Homes Repair due to Hazard Damage Cost Repair due to Typical Wear and Tear Cost Use Cost Construction Cost Life Cycle Structure Cost Combines probability of hazard with damage from hazard Use same approach for environmental impact Defines when investments in hazard resistance have net cost and environmental benefits (dependent on region)

35. CSHub research is driving new perspectives The science, engineering, and economics of quantitative sustainability is available to: • Evaluate complete, life-cycle infrastructure performance • To realize carbon benefits • Support standards and investments into resilience • To realize community benefits • Insist on long-term, risk-based evaluation of infrastructure • To manage future cost risk Changing these perspectives creates opportunity

36. Thank you

37. LCCA is already used to support some decisions …but there are gaps: • Practices are inconsistent • Characterizing initial and future cost data is a challenge • Maintenance schedules are not always tied to performance data • Uncertainty is rarely included

38. The CSHub is working on carrots (i.e., tools) Key Objectives • Improve scientific basis for models • Incorporate uncertainty and risk into analyses • Streamline processes • Integrate LCA & LCCA into design process Pavements Buildings Credibility Practicality