Structural design of road pavement

 

Designing efficient and durable roads starts with understanding one key factor: traffic. Traffic analysis provides engineers with essential data that directly influences decisions about road width, pavement thickness, and overall design. In this blog, we’ll walk through the fundamental steps of traffic analysis, from traffic surveys to axle load studies, and how each component contributes to building roads that last. watch the full course from here

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1. Traffic Analysis

The amount and type of traffic a road will carry play a crucial role in pavement design. Roads with heavier traffic flows require not only wider carriageways but also thicker pavements to withstand the higher load repetitions. To estimate how much load a road will bear over its design life, engineers need to conduct a traffic survey. This survey helps assess current traffic volumes and project future trends, giving us a clearer picture of what the pavement needs to endure.

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1.1 Traffic Surveys: Gathering the Right Data

Traffic surveys involve collecting information on the number and type of vehicles using a road. By analyzing current traffic and historical data, engineers can forecast traffic growth and estimate future traffic volumes. This is vital for determining pavement thickness and ensuring long-term performance.

One essential part of this process is Classified Volume Count, which categorizes vehicles based on their size and load impact. According to the Federal Highway Administration (FHWA), vehicles are classified into 13 types—from motorcycles to multi-axle trailers. Heavy vehicles such as trucks and buses impose significantly greater stress on pavements, making their accurate identification critical.

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1.2 Traffic Counting Methods

Traffic counts measure the number of vehicles using a road over a specific period. This data helps calculate the Average Annual Daily Traffic (AADT), which is used in pavement design calculations like Equivalent Single Axle Load (ESAL).

Manual Counting

• Suitable for roads with fewer than 2,000 vehicles per day.
• Cost-effective but prone to human error and weather impacts.

Automatic Counting

• Ideal for high-volume or multi-lane roads.
• Devices include pneumatic tubes, inductive loops, weigh-in-motion (WIM) sensors, and video cameras.
• Can measure vehicle count, speed, axle load, and length.

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1.3 Key Factors for Accurate Traffic Counts

For reliable data, traffic counting should be:

• Conducted on flat, straight road sections with uniform characteristics.
• Away from intersections, pedestrian zones, or heavy turning areas.
• Scheduled for 12, 16, or 24 hours over at least 7 consecutive days.

Manual counts can be converted to 24-hour totals using adjustment factors:

• 12-hour count (6 AM–6 PM) → divide by 0.80
• 16-hour count (6 AM–10 PM) → divide by 0.90

However, direct 24-hour counts are preferred for accuracy, especially when calculating AADT.

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1.4 Quick Example: Calculating AADT

Let’s say you counted 300 vehicles in a 12-hour window. To estimate 24-hour traffic:

300/0.80 = 375 vehicles/day

Do this for seven days, total the daily estimates, and divide by 7:

ADT = Total Vehicles in 7 Days/7

This gives the Average Daily Traffic (ADT), which feeds directly into pavement design models.

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1.5 Axle Load Survey

While counting vehicles is essential, knowing how much load each vehicle carries is just as important. This is where Axle Load Surveys come in.

Axle load surveys determine the load transferred to pavements by different axle configurations. This data is crucial for calculating:

• Truck Factors (TF)
• Equivalent Axle Load Factors (EALF)
• ESAL, which represents the cumulative pavement damage over time

Vehicles to Include

• Exclude light vehicles (<5 tonnes) since they cause minimal damage.
• Include all heavy vehicles, especially those with seating capacity >40 or multiple axles.
• Survey both directions separately, as traffic loads can differ significantly.

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1.6 Conducting a Reliable Axle Load Survey

Key points to ensure accuracy:

• Flat, level surfaces for weighing to avoid under/overestimating weights.
• All wheels must be on the same level.
• Include empty and loaded vehicles for a complete picture.
• Survey duration: 7 consecutive days, 24 hours/day (or matching station operational hours).

Equipment Used

• Permanent/portable weigh pads
• Weigh-in-motion (WIM) systems to record axle weights while vehicles are in motion

1.7  Design Life of Pavement

Determining the design life of a pavement is a fundamental step in the pavement design process. The design life refers to the period during which the pavement is expected to function without the need for major rehabilitation. It directly influences the thickness and structural capacity of the pavement—longer design lives mean higher cumulative loads and, consequently, thicker pavements.

Government agencies typically specify the design life based on several factors, including construction costs, maintenance strategies, and traffic importance. For instance, vital highways may require a longer design life to minimize future traffic disruptions, while secondary roads might be designed with a shorter lifespan to reduce initial construction costs.

In general:

• Flexible pavements are often designed for a life span of 20 years.
• Rigid pavements typically have a design life of 30 years.

The longer the design period, the greater the number of truckloads and traffic repetitions the pavement must endure. This increase in load cycles leads to higher stress and potential damage, which necessitates thicker pavement layers to maintain durability.

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1.8 Vehicle Classification

Roads serve a diverse range of vehicles, from motorcycles and passenger cars to heavy trucks and multi-axle trailers. Each vehicle differs in terms of:

• Axle configuration (number and spacing of axles),
• Number and type of tires,
• Load magnitude, and
• Frequency of road usage.

To standardize pavement design, these vehicles are grouped based on their axle configurations and load characteristics. This classification allows engineers to compute Equivalent Single Axle Loads (ESALs)—a key metric in pavement structural design.

Vehicle classification ensures accurate traffic loading predictions over the pavement's life. This helps in:

• Calculating the cumulative number of axle passes,
• Estimating truck factors (TF), and
• Computing the ESALs for pavement design.

Accurate ESAL estimation ensures durable, reliable pavements with fewer maintenance interventions.

The Federal Highway Administration (FHWA) categorizes vehicles into 13 distinct classes, ranging from motorcycles (Class 1) to multi-trailer trucks (Class 13). Unsurprisingly, larger vehicles with heavier axle loads inflict more damage on pavement—especially evident in the outer lanes of highways where heavy trucks frequently travel.

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 1.9 Axle Group Configuration

Axle configuration plays a critical role in how vehicle loads are transferred to pavement. Common configurations include:

1. Single axle with single tire (e.g., small cars)
2. Single axle with dual tires
3. Tandem axle with single tires (2 axles)
4. Tandem axle with dual tires
5. Tridem axle with dual tires (3 axles)
6. Quad axle with dual tires (4 axles)

Each configuration affects the pavement differently depending on the number of axles, the grouping of those axles, and the load per axle. For example, a tridem axle distributes load more efficiently than a single axle, even if the total weight is the same.

During traffic surveys, vehicles are categorized by axle configuration and load. This data enables engineers to calculate ESALs and design pavements that withstand expected traffic over the design period.

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1.10 Tire Pressure and Contact Stress

Tire pressure is another crucial factor in pavement loading. It determines the contact stress—the pressure applied from the tire to the pavement surface. This stress is calculated as:

q = P / A
Where:
q = Contact stress (kPa)
P = Tire load (kN)
A = Contact area (m²)

In practice, higher tire pressure results in a smaller contact area, which concentrates the load and increases contact stress. This leads to greater wear and tear on the pavement surface.

For design simplicity, the tire imprint is often assumed to be a rectangle with semicircular ends, though in reality, shapes may vary (e.g., circular, trapezoidal). Typical tire pressures for heavy trucks range from 500 to 1000 kPa, with 700 kPa being average.

1.11 Tire Imprint and Contact Stress

Let’s start with the basics. Tire load creates a stress on the pavement surface, and this stress depends on two things: the load applied and the contact area. When the contact area increases, the stress decreases—this is a simple inverse relationship:

The contact stress is equal to q=P/A

Where, q is the Contact stress in kPa (kilopascals)

 P  is the Applied load in kN (kilonewtons)

 A is the Area of contact, m2

so contact area is 𝝅∗(𝟎.𝟔𝑳)^𝟐/𝟒+𝟎.𝟒𝑳∗𝟎.𝟔𝑳.

where, L is the imprint area length

For simplification, the contact area of a tire is often modeled as a rectangle with two semicircular ends. This idealized shape makes it easier to calculate the imprint length (L), which is a critical value used later in determining ESWL.

Once the area is known, the relationship to the imprint length LL becomes:

so contact area is (𝐿𝑜𝑎𝑑 (𝑃))/(𝑇𝑖𝑟𝑒 𝑝𝑟𝑒𝑠𝑠𝑢𝑟𝑒 (𝑤))=0.5227∗𝐿^2.

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2. Wheel Configurations and Load Distribution

Wheel load distribution varies by axle configuration:

1. Single axle with single tire, 1 axle, 1 tire

2. Single axle with dual tires, 1 axle, two tires

3. Tandem axle with single tire, 2 axles, 1 tire

4. Tandem axle with dual tires, 2 axle, 2 tires

5. Tridem axle with dual tires, 3 axles, 2 tires

6. Quad axle with dual tires

As the number of tires and axles increases, the load per tire decreases—but the stress distribution becomes more complex.

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2.1 Understanding Equivalent Single Wheel Load (ESWL)

The ESWL is used to simplify complex wheel loads into a single equivalent wheel that produces the same stress or strain at a specific depth. This is particularly useful when designing flexible pavement using the CBR method.

Let’s look at two common configurations and how we determine ESWL using the graphical method.

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Case 1: Single Axle, Dual Tire

For this configuration:

• At shallow depths (< d/2), stress from a single wheel dominates.
• At greater depths (> d/2), stress zones from both tires overlap—requiring the use of ESWL.

To determine ESWL:

1. Calculate tire load:

Tire load=axle load/2

2. Create a graph with:

• X-axis: log(z), where z = pavement depth
• Y-axis: log(ESWL)

Key Plot Points:

• At log(z = 0) → log(P)
• At log(z = d/2) → log(P)
• At log(z = 2S) → log(2P)

Example:
Axle load = 445 kN
Tire pressure = 700 kPa
Tire spacing (s) = 56 cm
Pavement thickness = 31 cm

·         Tire Load P = 111.25 kN

·         Contact Area = 0.16 m²

·         L = 54 cm → d=23.6d = 23.6d=23.6 cm

Plot points and use the curve. At log(z = 1.5), log(ESWL) = 2.16 → ESWL ≈ 145 kN

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Case 2: Tandem Axle, Dual Tire

Here we have four tires per axle line, spaced both laterally and longitudinally. The key difference is the diagonal spacing (SD).

𝑺𝑫=√(𝒔^𝟐+𝒃^𝟐 )

Where:

• s = lateral spacing
• b = longitudinal spacing

Steps:

1. Find P, d, and SD
2. Plot:
• log(d/2) → log(P)
• log(2 × SD) → log(4P)
3. 
   
   
   

 Example:
Axle Load = 445 kN
Tire pressure = 700 kPa
Spacing: 50 cm × 100 cm
Pavement Thickness = 25 cm

·         P = 111.25 kN

·         L = 55 cm → d=17d = 17d=17 cm

·         SD = 112 cm

Plot points. At log(z = 1.4), log(ESWL) = 2.25 → ESWL ≈ 178 kN

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2.2 Designing Flexible Pavement Using the CBR Method

The CBR (California Bearing Ratio) method is widely used for airfield and heavy-duty pavement design. It works by ensuring each layer is thick enough to distribute stress without causing shear failure in the underlying soil.

What is CBR?

CBR is a ratio comparing the resistance of soil to penetration under controlled moisture and density conditions to that of standard crushed stone.

CBR=P/Ps*100% ,

Where, P is the measured pressure for tested soil

 Ps is the pressure to achieve equal penetration on standard crushed stone.

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2.3 CBR Design Procedure

1. Determine CBR values of subgrade, subbase, and base course.
2. Use CBR design charts to find required thicknesses for given wheel load.
3. Subtract layer thicknesses to find individual layer depths.

Example:
Wheel Load = 25 kip
Subgrade CBR = 5%
Subbase CBR = 20%
Base CBR = 80%

·         Total thickness from subgrade (CBR 5%) = 58 cm

·         From subbase (CBR 20%) = 31 cm → Subbase = 27 cm

·         From base (CBR 80%) = 10 cm → Base = 21 cm

If base thickness > 15 cm, use multiple layers (e.g., 11 cm + 10 cm).

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Pros and Cons of the CBR Method

Advantages:

• Simple and fast
• Ideal for heavy, slow-moving loads (e.g., aircraft)
• Based on easily conducted lab tests

Limitations:

• Empirical: Based on 1950s test data
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• Sensitive to sample variability (moisture, compaction)
• May not represent real field behavior accurately

3.0 Flexible Pavement Design Using the AASHTO Method: A Step-by-Step Guide

Designing flexible pavement is a critical aspect of road construction, ensuring roads can sustain the loads of traffic over their intended lifespan. Among several design methods, the AASHTO method is widely used due to its empirical nature and straightforward approach. In this blog, we’ll explore how the AASHTO method works, focusing on traffic analysis, axle loads, and the key calculations that drive pavement design.

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3.1 Vehicle Count: The Foundation of Pavement Design

Before we begin designing, we must understand how much traffic the road will carry. This involves conducting a vehicle count, which is the first step in evaluating traffic loads.

There are two main methods for conducting a vehicle count:

• Manual counting
• Automatic counting

These counts help determine the number of vehicles using the road over a given period—typically the design life of the pavement (commonly 20 years for flexible pavement). But the count must go beyond just numbers—it must also include:

• Vehicle types
• Axle configurations
• Axle loads

This information allows us to calculate the Average Daily Traffic (ADT) and helps determine how much wear and tear the road will experience.

For new roads, where no historical traffic data exists, engineers use traffic forecasting based on regional trends in vehicle growth, ownership, and road usage.

 Reminder: The accuracy of your pavement design heavily depends on the quality of your vehicle count and classification data.

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3.2 Traffic Projections and Growth Factor

Knowing current traffic volumes isn't enough—we need to project traffic into the future to ensure our design remains functional for decades. This is done using a Growth Factor (GF).

There are two commonly used equations:

• Linear Formula:
  GF = (1 + GR/100)^DL
• Simplified Formula:
  GF = 1 + (GR/100) * DL

Where:

• GR = Growth Rate (%)
• DL = Design Life (years)

For example, if the annual growth rate is 3% over a 20-year design period,
GF = (1 + 0.03)^20 ≈ 1.81

AASHTO typically uses a 0–10% range for the growth rate, based on local data.

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3.3 Design Lane & Lane Distribution Factor (LDF)

Not all lanes carry the same load. Heavy trucks typically use the outermost slow lane, so we focus our design on that design lane. But since some heavy vehicles use other lanes, we apply a Lane Distribution Factor:

• 1 lane in each direction → LDF = 1.0
• 2 lanes per direction → LDF ≈ 0.9
• 3 or more lanes → LDF decreases further

However, if local laws restrict heavy trucks to a specific lane, LDF may remain 1.0 regardless of the number of lanes.

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3.4 Directional Factor (DF)

Roads can be divided or undivided, and this impacts how we distribute traffic data:

• Divided Roads (with median):
  Count each direction separately → DF = 1.0
• Undivided Roads:
  Total count shared by both directions → DF = 0.5

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3.5 Truck Percentage (T)

Heavy vehicles cause the majority of pavement damage. The percentage of trucks—vehicles in Classes 4 to 13—must be calculated from the traffic survey.

For example, a 60-ft bus has an ESAL of 5.11, while a small car has only 0.0007. That's a 7,300 times greater impact!

This makes identifying and classifying vehicles absolutely essential for accurate pavement design.

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3.6 Equivalent Single Axle Load Factor (EALF)

Different vehicles and axle configurations cause varying amounts of damage. To simplify analysis, we use the Equivalent Single Axle Load Factor (EALF) to convert various axle loads into a standardized form.

Standard reference:

• 80 kN axle with dual tires

The formula:
EALF = (L / SL)^m
Where:

• L = Actual axle load
• SL = Standard axle load (usually 80 kN)
• m = Load damage exponent (typically 4.0)

Example:
A single axle with dual tires carrying 133 kN:
EALF = (133 / 80)^4 ≈ 7.7

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3.7 Truck Factor (TF)

Because each class of truck has different configurations and loads, we use a Truck Factor (TF) to quantify their cumulative effect:

TF = ∑(p × EALF)
Where:

• p = Percentage of that truck class
• EALF = Equivalent axle load factor

Example:

• Truck Type A (p = 0.55, EALF = 3) → TF = 0.55 × 3 = 1.65
• Truck Type B (p = 0.45, EALF = 2) → TF = 0.45 × 2 = 0.90
• Total TF = 1.65 + 0.90 = 2.55

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3.8 ESAL: Equivalent Single Axle Load

Now that we have all the components, we calculate ESAL—the total expected number of standard axle passes during the pavement's life.

ESAL Formula:

ESAL = ADT × T × TF × GF × LDF × DF × DL × 365

Where:

• ADT = Average Daily Traffic
• T = Truck Percentage
• TF = Truck Factor
• GF = Growth Factor
• LDF = Lane Distribution Factor
• DF = Directional Factor
• DL = Design Life (in years)
• 365 = Days per year

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Example Calculation

• Road: 6-lane divided highway
• Design Life: 20 years
• ADT: 2,000 vehicles/day
• Truck % (T): 40%
• TF: 3.18
• Growth Rate: 3% → GF = 1.80
• LDF = 1.0
• DF = 0.5

ESAL = 2000 × 0.40 × 3.18 × 1.80 × 1.0 × 0.5 × 20 × 365 ≈ 16,714,080

This value (ESAL) is used in the final pavement thickness design to ensure durability against cumulative loading.

4.0 Pavement Materials and Their Role in Flexible Pavement Design (AASHTO Method)

Designing a durable and effective flexible pavement begins with understanding the materials used in its construction. Each layer plays a specific role in distributing traffic loads, maintaining structural integrity, and ensuring long-term performance. In this article, we’ll explore how various pavement materials—starting from the subgrade to asphaltic layers—impact the structural design using the AASHTO method.

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4.1 Subgrade: The Foundation of Pavement Performance

The subgrade is the natural soil layer that serves as the foundation for all other pavement layers. Its stiffness—primarily influenced by soil type, compaction, and moisture content—is a critical factor in pavement design. In cases where in-situ soil is unsuitable, it must be replaced or improved to meet minimum design requirements.

Subgrade Testing Requirements

Pavement design typically requires subgrade evaluation through:

• Atterberg Limits (liquid and plastic limits)
• Soil gradation
• In-situ moisture content
• California Bearing Ratio (CBR)
• Resilient Modulus (Mr)

Both CBR and Mr help assess the subgrade’s stiffness, with the Mr being more commonly used in AASHTO-based designs.

Design Thresholds and Improvements

A minimum CBR of 10% is often required across the entire road alignment to ensure consistent performance. Any drop below this threshold not accounted for in design can compromise the pavement’s ability to carry expected loads. Subgrade should also meet the design CBR or Mr to a depth of at least 30 cm below the compacted layer.

Calculating Resilient Modulus (Mr)

While laboratory testing per AASHTO T-274 provides precise Mr values, simplified empirical equations are often used:

• For CBR < 10%:
• Mr (psi) = 1500 × CBR
• Mr (MPa) = 10 × CBR
• For CBR ≥ 10%:
• Mr (psi) = 2555 × CBR^0.64

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4.2 Granular Base and Subbase: Supporting the Structure

The granular base and subbase layers provide intermediate support between the subgrade and asphalt layers. Made of compacted coarse and fine aggregates, these layers must also exhibit sufficient stiffness to ensure load transfer.

Estimating Mr for Granular Materials

Mr for these layers can be estimated using the same equations as the subgrade if CBR is available from testing.

Layer Coefficients in AASHTO Design

Layer coefficients are crucial for determining pavement thickness:

• Base Layer (a₂):
• AASHTO Equation:
  a₂ = 0.249 × log₁₀(EBS) − 0.977
  EBS = Base modulus (psi)
• Typical values:
  a₂ ≈ 0.14 (for Mr ≈ 30,000 psi or CBR = 100)
• Subbase Layer (a₃):
• AASHTO Equation:
  a₃ = 0.227 × log₁₀(ESB) − 0.839
  ESB = Subbase modulus (psi)
• Typical values:
  a₃ ≈ 0.11 (for Mr ≈ 15,000 psi or CBR = 30)

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4.3 Stabilized Materials: Enhanced Strength and Performance

Stabilized materials are used where enhanced stiffness and durability are required. Two common types include:

Cement-Stabilized Layers

These consist of aggregates mixed with cement and water, compacted in one layer. Key steps include:

• Mixing at an approved plant
• Mechanical spreading (no graders)
• Compaction to 98% MDD
• Construction joints with vertical faces
• Curing for 7 days under wet hessian sheets

Layer Coefficient Determination:
Use modulus or UCS values along with AASHTO charts to estimate structural coefficients.

Asphalt-Treated Base (ATB)

ATB includes aggregates, bitumen, and filler. It’s handled like asphalt layers:

• Laid with a paver (max thickness = 50 mm)
• Compaction ≥ 95% of Marshall density
• Temperature maintained between 80°C to 149°C

Use elastic modulus or Marshall stability to determine the layer coefficient from AASHTO graphs.

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4.5 Asphalt Concrete: The Surface of Flexible Pavement

Asphalt Concrete (AC), or Hot Mix Asphalt (HMA), forms the pavement’s top layer. Depending on its position, asphalt layers can be:

• Wearing course (surface)
• Binder course (intermediate)
• Base course (bottom AC layer)

Each course serves a unique function. The surface resists rutting, while base layers focus on fatigue resistance.

Key Factors Affecting AC Performance

• Aggregate Properties: Angular, non-flaky aggregates offer better interlock.
• Binder Content: Must be carefully balanced; too little leads to dry, brittle mixes; too much causes bleeding and deformation.
• Volumetric Properties: Air voids and voids filled with bitumen (VFB) are essential indicators of durability.

Trial Mixes and small trial sections are recommended to verify mix design compliance.

Mixing and Compaction Temperatures

Precise temperature control is vital. Overheating burns the binder; under-compaction due to cold mixes reduces density and durability.

Layer Coefficient for Asphaltic Concrete

In the AASHTO method, the asphalt layer coefficient depends on resilient modulus (Mr at 21°C):

• Typical range: 0.2 to 0.44
• Use 0.44 for high-quality HMA (Mr ≈ 3.1 GPa or 450,000 psi)

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4.6 Summary of Material Properties and Coefficients

Layer	Typical Mr (psi)	Typical CBR	Layer Coefficient
Asphalt Concrete	450,000	—	0.44
Granular Base	30,000	100	0.14
Granular Subbase	15,000	30	0.11
Subgrade	1,500–25,000	10–15	Calculated via Mr

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5.0 Introduction to AASHTO Pavement Design Method

The AASHTO design method is an empirical approach based on traffic loading and pavement performance data. The key steps include:

• Estimating Equivalent Single Axle Loads (ESAL) based on traffic data
• Determining parameters: reliability, standard deviation, serviceability loss, and Mr
• Using charts to obtain the Structural Number (SN)
• SN guides the thickness design for each pavement layer

 

 

5.1 Reliability (R)

In pavement design, reliability refers to the confidence level that the designed pavement will perform satisfactorily under projected traffic loads for the entire design life. Expressed as a percentage, reliability accounts for uncertainties in traffic forecasting and material behavior.

• High-reliability levels are applied to roads with heavy traffic, such as truck routes and urban highways, where traffic volume is consistently high.
• Lower-reliability levels are acceptable for low-volume roads, where a slight underestimation in traffic may significantly affect pavement performance.

For example: A reliability of 95% is commonly used for major highways, while 75% might be acceptable for rural roads.

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5.2  Resilient Modulus (Mr) & Layer Coefficients

The resilient modulus (Mr) represents the stiffness of pavement materials under repeated loading. While direct testing is possible, it's often substituted using empirical equations based on California Bearing Ratio (CBR) values:

For Subgrade (CBR ≤ 10%):

               𝑴𝒓=𝟏𝟓𝟎𝟎∗𝑪𝑩𝑹

• For Base/Subbase (CBR > 10%):
• 
         𝑴𝒓=𝟐𝟓𝟓𝟓∗𝑪𝑩𝑹^(𝟎.𝟔𝟒)

The layer coefficients (a1, a2, a3) reflect the relative contribution of each layer to the overall structural capacity:

Layer	Typical Coefficient
Asphaltic Concrete (AC)	a₁ = 0.44
Aggregate Base Course	a₂ = 0.14
Subbase Layer	a₃ = 0.11

Optional: Use graphs or empirical formulas to determine precise coefficients for materials based on local conditions.

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5.3 Design Serviceability Loss (ΔPSI)

Serviceability is a measure of how well a pavement performs. The design serviceability loss (ΔPSI) is the difference between:

• Initial serviceability: Right after construction (usually ~4.2)
• Terminal serviceability: When the pavement is no longer acceptable and needs rehabilitation

Road Class	Typical ΔPSI
Urban Truck Route	1.2
Low-Volume Road	2.0

Roads with heavier traffic have stricter serviceability requirements.

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5.4 Overall Standard Deviation (So)

The standard deviation accounts for variability in design inputs and construction quality. A value of 0.45 is commonly used for flexible pavements.

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5.6 Pavement Design Steps Using AASHTO 1993

The AASHTO design method revolves around calculating the Structural Number (SN) — a weighted sum of the thickness and quality of each pavement layer.

Step 1: Determine ESALs (Equivalent Single Axle Loads)

Use traffic data, axle load surveys, and growth projections to compute:

𝑬𝑺𝑨𝑳=𝑨𝑫𝑻(𝒄𝒖𝒓𝒓𝒆𝒏𝒕)∗𝑻∗𝑻𝑭∗𝑮𝑭∗𝑳𝑫𝑭∗𝑫𝑭∗𝑫𝑳∗𝟑𝟔𝟓

Where:

• AADT: Average Annual Daily Traffic
• T: Truck percentage
• TF: Truck Factor (from EALF)
• DL: Design Life (years)
• GF: Growth Factor
  
  

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Step 2: Determine Design Parameters

You'll need to gather:

• Reliability (R)
• Standard Deviation (So)
• Design Serviceability Loss (ΔPSI)
• Effective Moduli (Mr) from CBR values
• Layer Coefficients (a1, a2, a3)
• Drainage Coefficients (m1, m2, m3) – often assumed as 1.0 for basic designs

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Step 3: Use AASHTO Design Charts

Input your parameters into the design chart to determine SN1, SN2, and SN3 (cumulative structural numbers for asphalt, base, and subbase layers).

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Step 4: Calculate Layer Thicknesses

Once SN values are known, compute layer thicknesses using:

• Asphalt Layer (D1):

𝑫𝟏=(𝐒𝐍𝟏∗𝟐.𝟓𝟒)/𝒂𝟏

• Base Course (D2):

𝑺𝑵𝟐=𝒂𝟏∗𝑫𝟏+𝒂𝟐∗𝒎𝟐∗𝑫𝟐

𝑫𝟐=((𝑺𝑵𝟐∗𝟐.𝟓𝟒−𝒂𝟏∗𝑫𝟏))/(𝒂𝟐∗𝒎𝟐)

• Subbase Layer (D3):

𝑺𝑵𝟑=𝒂𝟏∗𝑫𝟏+𝒂𝟐∗𝒎𝟐∗𝑫𝟐+𝒂𝟑∗𝒎𝟑∗𝑫𝟑

𝑫𝟑=((𝑺𝑵𝟑∗𝟐.𝟓𝟒−𝒂𝟏∗𝑫𝟏−𝒂𝟐∗𝒎𝟐∗𝑫𝟐))/(𝒂𝟑∗𝒎𝟑)

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5.5 Pavement Design Example: 4-Lane Highway

Design Inputs:

• CBR values:
• Subgrade: 10%
• Subbase: 30%
• Base: 80%
• AADT: 1088 vehicles (60% trucks)
• Design Life: 20 years
• Growth Rate: 6.5%
• ESAL Calculated: 16.9 million

Resilient Modulus:

• Mr (Subgrade) = 15 ksi
• Mr (Subbase) = 22.53 ksi
• Mr (Base) = 42.20 ksi

SN and Thickness:

• SN1 (AC) = 3.3 → D1 = 19 cm
• SN2 (AC + Base) = 4.2 → D2 = 17 cm
• SN3 (Total SN) = 5.2 → D3 = 23 cm

Asphalt Courses:

• Base course: 8 cm
• Binder course: 6 cm
• Wearing course: 5 cm

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Additional Considerations

• Minimum and maximum course thickness must be respected for constructability and compaction.
• Local conditions like drainage, utilities, and flood zones may require design modifications.
• Empirical knowledge from existing roads in the region can enhance design reliability.

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Final Pavement Cross-Section Summary:

Layer	Thickness (cm)
Asphalt Concrete	19
Aggregate Base	17
Subbase	23

Total Pavement Thickness = 59 cm