2016 CESTiCC Summer Workshop Impacts of a Pervious Concrete System - - PowerPoint PPT Presentation

Department of Civil and Environmental Engineering

2016 CESTiCC Summer Workshop

Impacts of a Pervious Concrete System on Neighboring Clay Soils in Warm-Dry Months Presented by: Mina Yekkalar

Summer 2016

Contents

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results

• Graphical Analysis
• Statistical Analysis: Available for further discussion

Analysis and Discussion Conclusion Future Goals References

Applications of Underground Retention Permeable Pavements

Pervious concrete can be used for many applications including:

• Parking lots,
• sidewalks,
• low volume roads, and
• there is interest in using pervious concrete systems on roadway shoulders to control the roadway runoff.

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Source: http://www.youtube.com/watch?v=A5v9btvX2H0

Benefits of Underground Retention Permeable Pavements

These pavements offer many benefits with respect to stormwater management such as:

• Groundwater recharging,
• Waterway pollution prevention,
• Lessening the peak flow as well as flooding risk
• Eliminating/lessening the need for stormwater management facilities/land as an alternative to retention pond
• Recycling the rainwater for non-potable water supplies such as irrigation

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Structure of Underground Retention Permeable Pavements as Highway Shoulders

A below pavement water storage system is typically comprised of: 1) a pervious concrete as its surface layer to let water infiltrate into the storage bed to either detain, or retain within the storage bed, or discharge into a stormwater system via underdrains, 2) an open graded aggregate base layer which is deep enough to provide additional structural support, space for water storage, and also to decrease the risk of freezing of the water layer in cold climate.

Source of photo: http://www.ephenryecocenter.com

Traditional Pavement as mainline Permeable Pavement Shoulder Natural Soil Open Graded Aggregate Bed Compacted Soil An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Underground Retention Permeable Pavements as Highway Shoulders under Dry-Warm Condition

• The fluctuations in thermal related properties of the different layers under a neighboring

pavement system which might have negative results in service quality and durability of a road by the impacts of: 1) the diurnal temperature variations on the top neighboring soil layer 2) the seasonal temperature variations on the deeper soil layers

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Literature Review: The impact of temperature on soil properties

The impact of temperature on soil properties:

• The lubricant effects play a determining role in the properties of soils without bearing skeletons such as

clayey soil whose high surface area makes it sensitive to temperature and moisture changes.

• A rise in temperature can lead to a decrease in the internal friction of the liquid phase resulting in an

increase in pore-water pressure and evaporation rate.

• At constant total water content of the soil that occurs in dry seasons, an increase in temperature leads to

an decrease in the strength of soil structure due to a drop in the interaction between soil elements.

• The mentioned mechanisms can be more complex under high temperatures leading to dispersion or

flocculation effects on the soil structure.

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Literature Review: Thermal Behaviour of Pervious Concrete in Dry-Warm Weather

Thermal Behaviour of Pervious Concrete in Dry-Warm Weather:

• In direct sunlight, the top surface of pervious concrete is hotter than traditional concrete.
• In spite of the higher surface temperature in pervious concrete than the surrounding ambient temperature

during sunlight hours, the overall heat stored in the pervious concrete system is equal to or cooler than a neighboring conventional concrete pavement system.

• The porous pavement group had a higher average gradient than the conventional pavement group

indicating that porous pavements released the stored energy in them faster than the conventional pavements.

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Research Gaps in Literature Reviews

Issues related to belowground storage pavements as shoulders to provide better understanding applicable to the design considerations in dry-warm climate Enhancement of soil temperature predictions of the roadway designs from the viewpoint of thermal regime fluctuations of base soils which then might affect the pavement more than the axle load in a summer thermal regime.

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

This study (funded by the Washington State Department of Ecology and the USDOT University Transportation Center; The Center for Environmentally Sustainable Transportation in Cold Climates |CESTiCC) focuses on:

Soil Water and Temperature Sensor Installation

Method: To achieve the objectives of the study, several soil moisture and temperature sensors are installed in slow draining soils next to a retention system located in a pervious concrete sidewalk on the Pullman Campus of Washington State University (with clayey soil) with no underdrains

First set of GPR targets Second set of GPR targets

6 in 6 in 2 ft 6 in 3 ft 3 ft 8 ft 5 ft 6 in 3 ft 3 ft

N

Profile of aggregate storage bed at Community Hall An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Existing Traditional Concrete Existing Traditional Concrete New Pervious Concrete

Dam

OW 1

OW: Observation Well MS: Moisture Sensor Array

Zone A Zone B Zone C

OW 2 Data logger M.S.A2 M.S.A1 M.S.B2 M.S.B1 M.S.C2 M.S.C1

N

Sensor (MS) plan Zones A, B and C at Community Hall Sensor depths Zones A, B and C at Community Hall (four sensors circled found to be non-operational)

Methods of Analysis

Graphical Analysis:  Graphical study on June, July, and August which are considered as warm-dry conditions in eastern Washington with very high ambient temperatures and negligible precipitation (any changes in soil water content is a result of irrigation

• r artificial flooding, evaporation, and water transport)

Detailed graphical study on a time frame from June 1 to July 7 (with longer days) called the heating period  Detailed graphical study on a time frame from July 7 to August 31 (with short days) called the cooling period. Statistical Analysis for Statistical Validation of the Observations (Available for further discussion):  Statistically evaluations on the relative differences (the values of average and standard deviations of the temperatures at the middle depth are within the precision of the sensors) in maximum and the minimum temperatures from the first day of each period on a daily basis in the heating and cooling periods by pre-programmed spreadsheets  Comparing the readings for the sensors of the same depth between the near and the far rows by one-tailed F-Tests to figure out the applicable type of T-Test (T-Tests either with equal variance or unequal variance)  Conducting a series of one-tailed on different paired sensors to figure out if there is a statistical difference between the sensors closer to the pervious concrete sidewalk as compared to the ones farther away at the same depth and in the same zone

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Results: Pervious Concrete Pavement and Weather Temperature

Observation: Similar to traditional pavements, the top layer of pervious concrete tends to be hotter than ambient weather temperature under warm and dry conditions.

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

15 20 25 30 35 40 45 50 5/26/15 5/29/15 6/1/15 6/4/15 6/7/15 6/10/15 6/13/15 6/16/15 6/19/15 6/22/15 6/25/15 6/28/15 7/1/15 7/4/15 7/7/15 7/10/15 7/13/15 7/16/15 7/19/15 7/22/15 7/25/15 7/28/15 7/31/15 8/3/15 8/6/15 8/9/15 8/12/15 8/15/15 8/18/15 8/21/15 8/24/15 8/27/15 8/30/15 9/2/15 9/5/15

Maximum Temperature (oC)

Ambient Pervious Concrete B11 B21

Note: There is around ±1°C variability in the readings from the various sensors, so that the graphs are not necessarily the exact temperature, but represent values close to the exact temperature and are indicative of true temperature variability.

Results: Maximum Daily Soil Temperature Data

17 19 21 23 25 27 29 Temperature at the Shallow Depth (°C)

A11 A21 B11 B21 C21

17 19 21 23 25 27 29

Temperature at the Middle Depth (°C)

A12 A22 B12 B22 C12 17 19 21 23 25 27 29

5/26/15 5/29/15 6/1/15 6/4/15 6/7/15 6/10/15 6/13/15 6/16/15 6/19/15 6/22/15 6/25/15 6/28/15 7/1/15 7/4/15 7/7/15 7/10/15 7/13/15 7/16/15 7/19/15 7/22/15 7/25/15 7/28/15 7/31/15 8/3/15 8/6/15 8/9/15 8/12/15 8/15/15 8/18/15 8/21/15 8/24/15 8/27/15 8/30/15 9/2/15 9/5/15 Temperature at the Deep Depth (°C)

A23 B13 B23 C23

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Results: Daily Soil Temperature Data

Observations:  During the heating period, the proximity of the storage bed seems to slightly increase the temperature of the nearest sensors as compared to sensors farther away at the shallow and middle depths where this is most evident in the top sensors.  During the cooling period, the reverse of this occurred under many conditions, implying the potential existence of a cooling mechanisms in the nearby aggregate storage bed might due to the possibility of conductive gaseous phase heat transfer through the voids in the aggregate bed and the pervious concrete layer as well as the radiation from the pervious concrete pavement on the shallow neighboring soils during the hot hours

• f the day while the deeper depths are fairly well buffered from this variability.

 The sensors located closer to the pervious pavement at the shallow depth show more variations and higher maximum temperatures might due to the diurnal temperature changes on top layers and more heat absorbed near the top of the pervious concrete pavement, similar to other pavement types.  The sensors at the deepest depths (below the depth of the aggregate bed) show little variation whether they are closer or farther away from the aggregate storage bed maybe as a result of the insulating capabilities of the void structure in the aggregate storage bed.

Note: The maximum temperature differences between closer and farther locations are less than 2°C.

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Results: Daily Soil Moisture Data

Precipitation Data Irrigation Data June Very Light Rain at 6/1/2015 from 19:15 to 20:14 19 Days Irrigation with 0.80 cm Averaged Applied Depth July ______________________ 22 Days Irrigation with 1.00 cm Averaged Applied Depth August Artificial at 8/17/2015 started at 09:00 23 Days Irrigation with 0.80 cm Averaged Applied Depth

Observations:  There is no considerable rain event that might affect the VWC of the soil layers.  It is predicted that the possible reasons for either increase or decrease in volumetric water content (VWC) of the soil may be irrigation/artificial raining or evaporation mechanism, respectively. Note: That data from artificial raining will be used for another purpose in future studies.

Supplementary Data from the Meteorology and Irrigation Stations in WSU

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Results: Daily Soil Moisture Data

0.1 0.2 0.3 0.4 0.5 VWC- Shallow Sensors A11 A21 B11 B21 C21 0.1 0.2 0.3 0.4 0.5 VWC- Middle Sensors A12 A22 B12 B22 C12 0.1 0.2 0.3 0.4 0.5

5/26/2015 5/31/2015 6/5/2015 6/10/2015 6/15/2015 6/20/2015 6/25/2015 6/30/2015 7/5/2015 7/10/2015 7/15/2015 7/20/2015 7/25/2015 7/30/2015 8/4/2015 8/9/2015 8/14/2015 8/19/2015 8/24/2015 8/29/2015 9/3/2015 9/8/2015

VWC - Deep Sensors A23 B13 B23 C23

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Results: Daily Soil Moisture Data

Observations:

There are some slight trends in VWC during the heating and cooling periods in Zone B in which the close soil at the shallow and middle depths wet slower and dry faster than the farther soil during the heating and cooling periods, respectively.

The shallow depths: soil moisture has been kept fairly consistent throughout the warm-dry period in Zones B and C, most likely due to consistent irrigation schedule as well as effective irrigation depth which is shallow enough that the irrigation waters rarely travel this far down.  The middle depths: their peaks tend to correspond to days when the lawn area above the sensors and upslope from the pervious concrete were heavily irrigated.  The deep depths: are quite consistent except for one case in Zone C during artificial flooding

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Note: There is some variability in the readings from the various sensors about ±0.03 m3/m3 (±3% VWC) by using Topp equation. Note: VWC readings from the middle sensor located in Zone C shows more variability by introducing a significant runon from the upslope soils into the soil of in Zone C as well as the pervious concrete storage bed Note: Since the sensor installed at the middle depth of the farther soil in Zone C is not operational, the impact of the pervious concrete storage bed on VWC of the near soil cannot be investigated with certainty.

Analyses and Discussion: Statistical Validation

Statistical Analysis Findings: During the heating period, the shallow soils close to the pervious concrete pavements appear to heat faster (higher maximum temperature) and cool slower (higher minimum temperature) than the top soils farther away in Zone B. During the cooling period, the shallow and middle soils near the pervious concrete system in both Zones A and B heat slower (lower maximum temperature) and cool faster (lower minimum temperature).

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Conclusion

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Precipitation, artificial flooding, or irrigation may affect the soil close to the pervious concrete system with respect to the VWC of the soil more than the farther soil at the middle depth probably as a result

• f water introduction into the aggregate storage bed providing additional moisture to these soils.

It appears that a pervious concrete system may benefit the neighboring soils by allowing more cooling later in the day during the latter part of a summer, even without the addition of water to the system.

Future Goals

 It was assumed that the proportion of these phases remained fairly constant due to little change in the soil moisture under these dry-warm weather conditions, as a result of regular irrigation while the existence of all three phases in the soil structure and the pervious concrete aggregate bed makes the analysis more complicated.  There was some variability in the data especially at the shallow depths which could be the result of variability in the installation of the geotextiles around the pervious concrete system, irregularities in the irrigation distribution, and variability in the soils themselves, including the compaction during installation of the pervious concrete system and the sensors, the lack of grass over the first row of sensors (nearest) in Zone B as compared to the other sensor locations  The effect of temperature on soil water systems was determined at constant water content. If change in temperature is associated with a change in moisture content then the total effect is the sum, or the difference, as the case may be, of both temperature and moisture change effects and it is recommended to develop a model with the coupling of moisture

• n heat transfer.

 In spite of the mentioned restrictions, the data presented herein can be used as boundary conditions in the future model development to predict the nearby soil temperature and soil moisture under a variety of weather conditions.  The study of the performance of the system during the winter is the next part of the study. Although the acceptable performance of the system during the whole of a year including summer time is the final goal in the design of the system, there is a higher demand for the evaluation of this system under winter condition as the consequent part of the

• verall performance of the permeable pavement shoulders.

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

References

Boyer, M. (2011). Preliminary analysis of summertime heat storage in traditional versus pervious concrete systems. Master thesis. Washington State University, Pullman, WA. Decagon Devices Inc. (2015). “Accuracy and Specifications of 5TM Soil Moisture & Temperature Sensor.” <http://www.decagon.com/en/soils/volumetric- water-content-sensors/5tm-vwc-temp/> (Mar. 25, 2016). Devore, J. (2010). Probability and Statistics for Engineering and the Sciences. Eight Edition. Brooks/Cole, Cengage Learning. Boston, MA. Farouki, O. T. (1982). “Thermal properties of soils.” Report Number: CRREL Monograph 81-1, U.S. Army Cold Regions Research and Engineering Laboratory, Hanover, New Hampshire. Haselbach, L. (2016). “Low Impact Development Feasibility Project on the WSU Pullman Campus and Phase I of the Stormwater-Pavement Interface in Cold Climates.” Report to the WA State Department of Ecology. Unpublished. Haselbach, L., Boyer, M., Kevern, J. T., and Schaefer, V. R. (2011). “Cyclic Heat Island Impacts in Traditional versus Pervious Concrete Systems.” Transportation Research Board, 2240, 107-11. Haselbach, L., and Gaither, A. (2008). “Preliminary Field Testing: Urban Heat Island Impacts and Pervious Concrete.” Proc., NRMCA, 2008 Concrete Technology Forum: Focus on Sustainable Development, Denver Co., May 20-22. Hugh, D. Y., and Roger, A. F. (2004). University Physics. 11th edition. Benjamin-Cummings Pub Co., San Francisco. Kevern, J., Haselbach, L., and Schaefer, V. (2012). “Hot Weather Comparative Heat Balances in Pervious Concrete and Impervious Concrete Pavement Systems.” Journal of Heat Island Institute International, 7(2). Kevern, J. T., Schaefer, V. R., and Wang, K. (2009). “Temperature Behavior of Pervious Concrete Systems.” Journal of the Transportation Research Board, 2098, 94–101. DOI: 10.3141/2098-10. NERC (2011). “Temperature and Thermal Properties (Detailed).” Natural Environmental Research Council, British Geological Survey report No: GR_999999/1, 1-7. Nwankwo, C., and Ogagarue, D. (2012). “An Investigation of Temperature Variation at Soil Depths in Parts of Southern Nigeria.” American Journal of Environmental Engineering, 2(5): 142-147 DOI: 10.5923/j.ajee.20120205.05. Winterkorn, H. F., and Fang, H. Y. (1972). “Effect of temperature and moisture on the strength of soil-pavement systems.” Fritz Laboratory Reports. <http://preserve.lehigh.edu/engr-civil-environmental-fritz-lab-reports/1975> (Mar. 25, 2016).

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Tha hank Yo You for for Yo Your Atten ttendance an and d Atte ttenti tion!

Mina Yekkalar: Ph.D. Student in Civil and Environmental Engineering, Washington State University E-mail: mina.yekkalar@wsu.edu

Statistical Validation

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

The null hypothesis were developed and tested based on the following predictions:  Under dry and warm conditions, the impact of the heat capacities of pervious concrete pavement on the top neighboring soils results in faster heating compared with the soil farther away (Note, that this phenomenon would be expected to occur for any heat absorbing pavement layer, regardless of type.) Under dry and warm conditions, the middle and deep depths are not affected by the system due to its insulating function as a result of its porous nature.  Under dry and warm conditions, the nearby neighboring soils both at the shallow and middle depths will cool faster due to the possibility of conductive gaseous phase heat transfer through the voids in the pervious concrete system, but not necessarily for the deep sensors since they are below the grade of the aggregate storage bed.

Note: Variables referred to as the maximum (minimum) temperature gradients were developed as the temperature difference between the highest maximum (lowest minimum) temperature in the period and the maximum (minimum) on the first day of that period. Note: In this study, if the null hypothesis is not proven at a probability value equal to 0.05 (α=0.05), there is a significant difference between that pair. Note: The deep depths are not statistically analyzed due to their unimportant differences.

Cooling and Heating Trends of the Soil Next to the Pervious Concrete System

• 10
• 8
• 6
• 4
• 2

2 4 6 8 30.5 61 91.5 Maximum Temperature Gradients (°C) Sensor Depth from Surface (cm) Near Sensor of Zone A in Heating Period Far Sensor of Zone A in Heating Period Near Sensor of Zone B in Heating Period Far Sensor of Zone B in Heating Period Near Sensor of Zone A in Cooling Period Far Sensor of Zone A in Cooling Period Near Sensor of Zone B in Cooling Period Far Sensor of Zone B in Cooling Period

• 8
• 6
• 4
• 2

2 4 6 8 30.5 61 91.5 Minimum Temperature Gradients (°C) Sensor Depth from Surface (cm) Near Sensor of Zone A in Heating Period Far Sensor of Zone A in Heating Period Near Sensor of Zone B in Heating Period Far Sensor of Zone B in Heating Period Near Sensor of Zone A in Cooling Period Far Sensor of Zone A in Cooling Period Near Sensor of Zone B in Cooling Period Far Sensor of Zone B in Cooling Period Cooling and heating trends in maximum temperature changes based on the sensor locations Cooling and heating trends in minimum temperature changes based the sensor locations An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Statistical Validation

Gradient of Maximum Temperatures (◦C) Gradient of Minimum Temperatures (◦C) Sensor Average Standard Deviation P(F<=f) One-tailed P(T<=t) One-tailed Average Standard Deviation P(F<=f) One-tailed P(T<=t) One-tailed A11 24.6 1.81 0.35 0.13 22.8 1.85 0.38 0.17 A21 24.5 1.53 22.8 1.58 B11 26.3 1.83 0.48 0.00 23.4 1.81 0.49 0.03 B21 24.4 1.61 23.1 1.61 A12 22.4 1.48 0.59 0.44 22.0 1.50 0.58 0.31 A22 22.0 1.35 21.8 1.37 B12 24.4 1.47 0.50 0.09 22.2 1.50 0.48 0.05 B22 21.5 1.31 21.2 1.33 Summary of the Statistical Tests on the Null Hypothesis about the Temperature Gradients for the Heating Period (34 days)

An Introduction The goal of the Study Materials and Methods

• Installation
• Analysis Methods

Results Analysis and Discussion

• Graphical Analysis
• Statistical Analysis

Conclusion Future Goals References

Gradient of Maximum Temperatures (◦C) Gradient of Minimum Temperatures (◦C) Sensor Average Standard Deviation P(F<=f) One-tailed P(T<=t) One-tailed Average Standard Deviation P(F<=f) One-tailed P(T<=t) One-tailed A11 24.0 1.45 0.50 0.24 22.5 1.34 0.33 0.12 A21 24.0 1.33 22.6 1.17 B11 24.8 1.75 0.09 0.00 22.3 1.52 0.23 0.04 B21 23.6 1.39 22.5 1.29 A12 23.3 0.81 0.25 0.05 23.0 0.80 0.28 0.01 A22 23.1 0.69 23.0 0.69 B12 23.1 0.87 0.14 0.00 22.7 0.89 0.10 0.00 B22 23.3 0.71 22.1 0.71 Summary of the Statistical Tests on the Null Hypothesis about the Temperature Gradients for the Cooling Period (55 days)