Pavement-related research at the MIT Concrete Sustainability Hub

Transcription

1 Pavement-related research at the MIT Concrete Sustainability Hub Jeremy Gregory Iowa Concrete Paving Association 51 st Annual Concrete Paving Workshop February 4-6, 2015

2 MIT Concrete Sustainability Hub Mission: Develop breakthroughs that will lead to more sustainable and durable infrastructure, buildings and homes This will be accomplished by: Increasing performance Reducing environmental impacts Reducing cost Slide 2

3 CSHub approach is holistic and multidisciplinary Science Engineering Economics Environment Slide 3

4 CSHub research supports pavement decisions LCA (life-cycle assessment) Environmental Impact Factors in decisions Cost LCCA (life-cycle cost analysis) Performance Pavement design process Slide 4

5 LCA Life-cycle assessment: Method for quantifying environmental impact Process inventory Raw Materials Life-cycle impact Energy Processing Chemicals Process Releases to Land Air Emissions Water Effluents Disposal / Recycling Materials Production Use Manufacture Product Slide 5

6 LCCA Life-cycle cost analysis: Method for evaluating total costs of ownership Transform individual pavement expenditures over time into total life-cycle cost Real Cost Life-Cycle Cost Slide 6

7 The life-cycle perspective frames CSHub work There are multiple mechanisms for reducing environmental impact and cost across a structure s life Materials Production Use recycled materials Reduce energy use Improve material performance Design & Construction Use less (i.e., stronger) material Create longerlasting designs Use Reduce vehicle fuel consumption Reduce heat island effects End-of-Life Enable material recovery Prioritizing mechanisms requires a trade-off analysis of performance and life-cycle environmental impacts and costs Slide 7

8 CSHub Pavement LCA & LCCA Goals 1. Drive the pervasive use of life-cycle costing and life-cycle assessment for: Pavement design Pavement type selection Maintenance decisions Asset management 2. Improve the robustness of pavementrelated decision-making Slide 8

9 Motivation: Pavement design is iterative; Accelerated feedback more testing, more improvement Design Proposal & Context Layers Traffic Climate 10.0 JPCP w/ 1.25 Dia Dowels 6.0 Agg Subbse Subgrade N Analyze Using ME Design Principles Adequate Performance Y Final Design 8.0 JPCP w/ 1.25 Dia Dowels 6.0 Agg Subbse Subgrade Develop Lifecycle Bill of Activities Evaluate LCCA / LCA Slide 9

10 Motivation: Pavement design is iterative; Accelerated feedback more testing, more improvement Design Proposal & Context Layers Traffic Climate 10.0 JPCP w/ 1.25 Dia Dowels 6.0 Agg Subbse Subgrade Analyze Using ME Design Principles Final Design 8.0 JPCP w/ 1.25 Dia Dowels 6.0 Agg Subbse Subgrade Develop Lifecycle Bill of Activities MIT research aims to integrate these activities Evaluate LCCA / LCA N Adequate Performance Y Slide 10

11 LIFE-CYCLE COST: Key accomplishments Key findings Slide 11

12 CSHub created linkage between design tools and evaluation Pavement has associated activities; activities translate to cost & impact Cash flows 7.0 JPCP w/ 1.25 Dia Dowels 6.0 Agg Subbse Subgrade Pavement Design & Context MEPDG Pavement Performance Performanceto-activity modeling Bill of activities Material quantities Construction activities Maintenance timing Logistics LCCA Model LCA Model Magnitude Timing Life-cycle inventory Material & energy inflows Emissions outflows Slide 12

13 CSHub created probabilistic cost estimates for entire life-cycle 1) Unit price of inputs 2) Quantity of inputs Cash Flow 1) Quantity of inputs 2) Future construction prices 3) Maintenance timing Construction Operati on Slide 13

14 CSHub created effective long-term, probabilistic price projections 140 Price projections are created and validated using historical data Real Price of Cement (1998 $) Effective price projections: Must be built from significant sets of data Must be viewed as probabilistic in nature Source: USGS Slide 14

15 CSHub conducted LCCAs for a wide range of scenarios 4 Locations 3 Traffic Levels CO: Dry freeze Rural local street/highway Rural state highway Urban interstate AZ: Dry no freeze MO: Wet freeze Several framing conditions Pavement designs Maintenance schedules FL: Wet no freeze Design life Analysis period Slide 15

16 LIFE-CYCLE COST: Key accomplishments Key findings Slide 16

17 Key findings from CSHub LCCA research Life cycle matters Context matters The future is worth considering Risk matters Slide 17

18 Life cycle matters Future costs can be significant Total life-cycle costs for a state highway in Florida Future maintenance and rehabilitation costs 53% Initial construction costs 47% Flexible pavement design developed by Applied Research Associates (ARA), Inc,: AADTT 1k/day; 4 lanes; Wet-no-freeze-FL; FDOT-based rehabilitation schedule; Analysis period = 50 years. Slide 18

19 Context matters Costs vary with location, traffic level, & pavement design Interstate, rigid design Rehab costs 2% Initial costs 98% Rehab costs 11% Local highway, rigid design Initial costs 89% Interstate, flexible design State highway, flexible design Rehab costs 21% Initial costs 79% Rehab costs 53% Initial costs 47% Slide 19

20 The future is worth considering Effective price projections are plausible Concrete (Constituent Based) Asphalt (Constituent Based) Real Price Index Real Price Index Slide 20

21 CSHub forecasts have been shown to be more effective than current assumptions Testing the effectiveness of the model for the state of Colorado Average Error of Forecast 60% 40% 20% 0% Real price projections outperform conventional assumptions of no real price change Current Practice CSHub Forecasting Model Years into the future Slide 21 Increasing Performance

22 LIFE-CYCLE ENVIRONMENTAL PERFORMANCE: Key accomplishments Key findings Slide 22

23 CSHub created probabilistic life-cycle assessment model including use phase Scope includes all effects attributable to the pavement design. Extraction and production Transportation Materials Onsite equipment Construction Pavement-Vehicle Interaction Roughness Deflection Albedo Carbonation Lighting Use Maintenance Incorporating use phase is a recent development Excavation Landfilling Recycling Transportation End-of-Life/ Rehabilitation Materials Construction Slide 23

24 CSHub implemented model-based assessment of PVI using new deflection model Pavement Deflection Pavement Roughness MIT Model MEPDG+HDM4 Structure and Material Calculation Method: Deflection & Roughness Excess Fuel Consumption Environmental Impact Slide 24

25 CSHub conducted LCAs for a wide range of scenarios 4 Locations 3 Traffic Levels CO: Dry freeze Rural local street/highway Rural state highway Urban interstate AZ: Dry no freeze MO: Wet freeze Several framing conditions Pavement designs Maintenance schedules FL: Wet no freeze Design life Analysis period Slide 25

26 LIFE-CYCLE ENVIRONMENTAL PERFORMANCE: Key accomplishments Key findings Slide 26

27 Key findings from CSHub LCA research Life cycle matters Pavement-vehicle interaction (PVI) matters Context matters Large opportunities to improve exist Slide 27

28 Life-cycle matters Use phase can be a significant fraction of pavement environmental impact M&R 7% End-of-Life 6% Construction 29% Example: Life-cycle GHG (greenhouse gas) emissions of an urban interstate pavement in Missouri Use 58% Flexible pavement design developed by Applied Research Associates (ARA), Inc,: AADTT 8k/day; 6 lanes; Wet-freeze-MO; MEPDG-based rehabilitation schedule. Slide 28

29 PVI matters Excess fuel consumption from PVI is significant Estimate of extra fuel consumption from PVI in US pavement test sections Million Gallons per Year Total of ~700 million gallons of excess fuel per year Urban Other Arterial Urban Freeways Urban Interstate Rural Other Arterial Rural Interstate 0 Slide 29

30 Deflection matters In some contexts, deflection causes the majority of fuel lost to PVI Use Other* 7% Example: Use-phase GHG emissions by source for an urban interstate pavement in Missouri Fuel loss: deflection 53% Fuel loss: roughness 40% *Other: carbonation & lighting Slide 30

31 Roughness matters In some contexts, however, roughness causes most of the fuel lost to PVI Use Other* 8% Example: Use-phase GHG emissions by source for an urban interstate pavement in Colorado Fuel loss: deflection 31% Fuel loss: roughness 61% *Other: carbonation & lighting Slide 31

32 PVI matters PVI data can be used in network pavement management Excess fuel consumption due to PVI for cars & trucks on interstates in Virginia in 2013 Fuel Consumption (gallon/mile) Assumed speed= 100 km/h=62.6 mph; assumed temperature= 16 C/61 F Slide 32

33 Context matters Burdens vary with location, traffic level, & pavement design EoL 7% Rehab 0% Use 57% Interstate, rigid design Initial 36% EoL 11% Rehab 1% Use 31% Local highway, rigid design Initial 57% Initial = Initial construction Rehab = Maintenance & rehabilitation EoL = end-of-life EoL 8% Rehab 16% Use 42% Interstate, flexible design Initial 34% EoL 8% Rehab 25% Use 35% State highway, flexible design Slide 33 Initial 32%

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