NANOMATERIAL-ENHANCED SELF-HEALING CONCRETE PAVEMENT SYSTEM FOR IMPROVED DURABILITY

Abstract

NANOMATERIAL-ENHANCED SELF-HEALING CONCRETE PAVEMENT SYSTEM FOR IMPROVED DURABILITY ABSTRACT The present invention relates to a self-healing concrete pavement system utilizing nanomaterials to enhance durability and extend the lifespan of concrete structures. The system comprises a concrete matrix embedded with nanomaterials such as carbon nanotubes and graphene, which detect and respond to microcracks. An integrated sensor network continuously monitors the pavement's structural integrity, identifying microcrack formation. Upon detection, an autonomous healing agent release mechanism, controlled by a central module, dispenses a nanomaterial-infused agent that interacts with the cracks, initiating repair. The system also includes machine learning algorithms to predict areas of high stress and optimize the healing process. This innovative approach significantly improves resistance to environmental wear, reduces the need for frequent repairs, and enhances the overall performance of concrete pavements. The method involves embedding nanomaterials, detecting microcracks, and releasing healing agents, providing an efficient, durable solution for concrete infrastructure.

Specification

Description:in which it is to be performed
NANOMATERIAL-ENHANCED SELF-HEALING CONCRETE PAVEMENT SYSTEM FOR IMPROVED DURABILITY

FIELD OF THE INVENTION

Various embodiments of the present invention generally relate to concrete pavements. More particularly, the invention relates to nanomaterial-enhanced self-healing concrete pavement system for improved durability.

BACKGROUND OF THE INVENTION

Concrete is one of the most widely used construction materials in infrastructure projects, particularly for roads, bridges, and pavements, due to its strength, durability, and cost-effectiveness. However, despite its advantages, concrete is prone to deterioration over time due to factors such as environmental stress, heavy traffic loads, temperature fluctuations, and moisture penetration. This deterioration often manifests as cracks, which can lead to significant structural issues if not promptly addressed. Traditionally, repairing these cracks involves labor-intensive and costly manual intervention, disrupting traffic and increasing the overall maintenance costs.
To address these challenges, self-healing concrete technologies have been developed, aimed at automatically repairing cracks as they occur. These technologies typically involve the incorporation of healing agents within the concrete that are released when a crack forms. While effective, existing self-healing solutions are often limited by their response time, healing capacity, or inability to detect microcracks early enough to prevent further damage. Additionally, current systems may lack the ability to predict high-stress areas that are prone to cracking, leading to inefficiencies in crack prevention and repair.
Nanomaterials, such as carbon nanotubes and graphene, have emerged as promising materials to enhance the mechanical properties and self-sensing capabilities of concrete. These nanomaterials can detect microcracks before they develop into larger issues and, when combined with advanced healing agents, can significantly improve the self-repair capabilities of concrete structures. Furthermore, the integration of sensor networks and machine learning algorithms in modern infrastructure systems enables real-time monitoring and predictive maintenance, allowing for more efficient and targeted interventions.
The present invention builds on these advancements by providing a self-healing concrete pavement system that utilizes nanomaterials, real-time sensor networks, and machine learning algorithms. This innovative system addresses the limitations of existing solutions, offering enhanced durability, cost-effective maintenance, and proactive damage prevention for concrete pavements.

SUMMARY OF THE INVENTION

The present invention relates to a self-healing concrete pavement system designed to enhance durability and reduce maintenance using nanomaterials and advanced sensing technologies. The system integrates nanomaterials such as carbon nanotubes and graphene into the concrete matrix to detect and repair microcracks autonomously. A sensor network monitors the structural health of the pavement in real-time, identifying microcracks as they form. Upon detection, an autonomous healing agent release mechanism deploys a nanomaterial-infused agent to fill and repair the cracks. The system also employs machine learning algorithms to predict high-stress areas, allowing for preemptive reinforcement and damage prevention. Additionally, the system features a communication interface that enables remote monitoring and diagnostics, providing real-time data to maintenance teams. This innovative approach significantly extends the lifespan of concrete pavements, reduces the frequency of repairs, enhances safety, and promotes sustainable infrastructure by minimizing material and resource consumption.
One or more advantages of the prior art are overcome, and additional advantages are provided through the invention. Additional features are realized through the technique of the invention. Other embodiments and aspects of the disclosure are described in detail herein and are considered a part of the invention.
BRIEF DESCRIPTION OF THE FIGURES

The accompanying figures where like reference numerals refer to identical or functionally similar elements throughout the separate views and which together with the detailed description below are incorporated in and form part of the specification, serve to further illustrate various embodiments and to explain various principles and advantages all in accordance with the invention.
FIG. 1 is a diagram that illustrates a self-healing concrete pavement system using nanomaterials for enhanced durability, in accordance with an embodiment of the invention.
FIG. 2 is a diagram that illustrates a flow diagram with a method for enhancing the durability of a self-healing concrete pavement system using nanomaterials, in accordance with an embodiment of the invention.
Skilled artisans will appreciate the elements in the figures are illustrated for simplicity and clarity and have not necessarily been drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help to improve understanding of embodiments of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

While various embodiments of the invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions may occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed. It shall be understood that different aspects of the invention can be appreciated individually, collectively, or in combination with each other.
FIG. 1 is a diagram that illustrates a self-healing concrete pavement system 100 using nanomaterials for enhanced durability, in accordance with an embodiment of the invention.
The memory 102 often referred to as RAM (Random Access Memory), is the component of a computer system that provides temporary storage for data and instructions that the processor needs to access quickly. It holds the information required for running programs and performing calculations. The memory 102 can be thought of as a workspace where the processor can read from and write to data.
The processor 104 referred to as the Central Processing Unit (CPU), is the "brain" of the computer system. It carries out instructions, performs calculations, and manages the flow of data within the system. The processor 104 fetches instructions and data from memory, processes them, and produces results.
The one or more communication interfaces 106 refer to the various methods and protocols used to transfer data between different systems, devices, or components. These interfaces can be hardware-based, software-based, or a combination of both.
The memory 102 and the processor 104 are connected through buses, which are electrical pathways for transferring data and instructions.
The communication bus 108 plays a vital role in enabling effective and efficient communication within a system. It establishes the foundation for exchanging information, coordinating actions, and synchronizing operations among different components, ensuring the system functions as an integrated whole.
The self-healing concrete pavement system utilizing nanomaterials for enhanced durability comprises several components working together to ensure long-lasting structural integrity. At its core, the system features a concrete matrix embedded with nanomaterials, including carbon nanotubes and graphene-based particles. These nanomaterials are specifically chosen for their ability to detect microcracks as they form within the matrix and to reinforce the tensile strength of the concrete. This provides a robust and resilient pavement structure capable of self-monitoring and self-repairing over time.
A sensor network is integrated into the concrete matrix, allowing for real-time monitoring of structural health. The sensors are designed to detect the formation of microcracks at an early stage, ensuring that damage is addressed promptly. Once the sensors detect a microcrack, they relay this information to a control module, which processes the data and triggers the next phase in the self-healing process.
The system includes an autonomous healing agent release mechanism, which is activated based on signals received from the sensor network. This release mechanism is responsible for deploying a specialized healing agent into the affected areas of the concrete. The healing agent itself contains microcapsules with a polymeric solution that, when combined with the nanomaterials in the concrete matrix, forms a durable bond, effectively repairing the cracks.

The control module also plays a critical role in optimizing the system's performance. It utilizes machine learning algorithms to analyze sensor data and predict areas of high stress within the pavement. By doing so, the system can proactively strengthen these areas before significant damage occurs, thereby enhancing the durability and resilience of the pavement.
Additionally, the system features a communication interface that allows the structural health data to be transmitted to an external monitoring system. This enables remote diagnostics and real-time analysis of the pavement's condition, providing maintenance teams with valuable insights into when and where repairs may be necessary.
This advanced system not only extends the life of concrete pavements but also minimizes the need for costly and frequent repairs by utilizing nanotechnology and autonomous maintenance processes.
FIG. 2 is a diagram that illustrates a flow diagram 200 with a method for enhancing the durability of a self-healing concrete pavement system using nanomaterials, in accordance with an embodiment of the invention.
The method for enhancing the durability of a self-healing concrete pavement system using nanomaterials involves several key steps to ensure long-lasting performance and structural integrity. The process begins with embedding a plurality of nanomaterials within a concrete matrix. The nanomaterials selected, such as carbon nanotubes and graphene-based particles, are chosen for their exceptional mechanical properties, which help to reinforce the concrete and improve its ability to detect and repair microcracks.
Following the embedding process, a sensor network is integrated into the concrete matrix. This sensor network is strategically placed to monitor the pavement's structural health and detect the formation of microcracks in real time. The sensors are equipped to continuously scan the concrete for signs of deterioration, particularly focusing on the development of microcracks that could compromise the overall integrity of the pavement.

When a microcrack is detected, the system detects microcracks using the sensor network and triggers the release of a healing agent into the affected area. The healing agent contains nanomaterials that interact with the concrete matrix to initiate the self-healing process. This step is crucial, as it ensures that cracks are addressed early before they expand into larger structural issues. The healing agent may consist of microcapsules that rupture upon contact with the microcrack, releasing a polymeric solution that reacts with the embedded nanomaterials to form a durable bond and effectively repair the crack.
As part of the system's proactive approach, the method further includes utilizing machine learning algorithms to predict areas where microcracks are most likely to form. By analyzing historical data on the pavement's performance, the machine learning model can identify high-stress areas and preemptively strengthen them, reducing the likelihood of crack formation in these zones.
The system also allows for real-time monitoring and data transmission to an external control system. This enables continuous assessment of the pavement's condition, providing maintenance teams with up-to-date information on its health and facilitating remote diagnostics.
To further optimize the healing process, the system includes a step for adjusting the amount of healing agent released based on the size and location of the detected microcracks. By tailoring the release of the healing agent to the specific needs of each crack, the system ensures efficient use of resources and enhances the effectiveness of the repair process.
This method offers a comprehensive approach to maintaining concrete pavements, combining nanomaterials, sensor networks, and machine learning to create a self-healing, durable pavement system that requires minimal maintenance and delivers long-term structural performance.
Exemplary Embodiments
1. Embedding Nanomaterials for Self-Healing Concrete
In an embodiment, the self-healing concrete pavement system incorporates nanomaterials such as carbon nanotubes and graphene within the concrete matrix. These nanomaterials are selected for their ability to enhance the tensile strength of the concrete while providing self-sensing capabilities. As microcracks form in the pavement, the embedded nanomaterials detect the structural changes and work in conjunction with an integrated sensor network to identify the exact location of the damage.
2. Sensor Network for Real-Time Crack Detection
In an embodiment, the system integrates a sensor network throughout the concrete matrix. These sensors continuously monitor the structural health of the pavement, detecting microcracks at an early stage. The sensors are wirelessly connected to a central control module that processes the data in real time. Upon detecting a microcrack, the sensors send a signal to the autonomous healing agent release mechanism to initiate the repair process.
3. Autonomous Healing Agent Release Mechanism
In an embodiment, the healing process is triggered automatically when a microcrack is detected. The autonomous healing agent release mechanism contains microcapsules filled with a polymeric solution mixed with nanomaterials. When the sensor network identifies a crack, the control module signals the release mechanism to dispense the healing agent directly into the crack. The microcapsules rupture upon contact, releasing the polymeric solution, which interacts with the nanomaterials in the concrete to form a strong, durable bond that repairs the crack.
4. Machine Learning-Driven Predictive Maintenance
In an embodiment, the system uses machine learning algorithms to predict areas within the pavement that are most prone to stress and microcrack formation. The machine learning model analyzes historical pavement performance data, environmental conditions, and traffic patterns to forecast future damage. Based on these predictions, the control module can instruct the system to strengthen or preemptively heal high-stress areas before significant damage occurs, ensuring long-term durability.
5. Remote Monitoring and Diagnostics via Communication Interface
In an embodiment, the system includes a communication interface that allows remote monitoring of the pavement's condition. Data from the sensor network is transmitted to an external monitoring system, enabling maintenance teams to assess the structural health of the pavement in real time. This remote diagnostics feature helps teams plan proactive maintenance and avoid costly physical inspections. The communication interface may also alert maintenance personnel when significant microcracks are detected or when the healing agent needs replenishment.
These exemplary embodiments showcase the various components of the system working in harmony to ensure the long-lasting durability of concrete pavements through autonomous, efficient self-healing processes.
The self-healing concrete pavement system using nanomaterials offers several significant advantages:
1. Extended Durability and Lifespan: The use of nanomaterials like carbon nanotubes and graphene reinforces the concrete, enhancing its tensile strength and resilience. The system's ability to detect and repair microcracks autonomously significantly extends the lifespan of the pavement, reducing wear and tear over time.
2. Cost-Effective Maintenance: By detecting and addressing microcracks early, the system reduces the need for frequent, costly repairs. The self-healing mechanism prevents small cracks from evolving into larger structural issues, saving both time and resources.
3. Real-Time Structural Monitoring: The integrated sensor network provides continuous monitoring of the pavement's structural integrity, allowing for real-time detection of microcracks. This ensures timely intervention, minimizing the risk of sudden pavement failures.
4. Proactive Damage Prevention: The machine learning algorithms used in the system predict high-stress areas where microcracks are likely to form, allowing for preemptive reinforcement. This proactive approach helps reduce future damage and enhances pavement performance.
5. Environmental Sustainability: By reducing the need for frequent repairs and replacements, the system decreases the consumption of materials and energy associated with traditional pavement maintenance. The use of nanomaterials further improves the system's efficiency and durability, promoting sustainable infrastructure development.
6. Improved Safety: Early detection and autonomous repair of microcracks ensure that the pavement remains in optimal condition, reducing the risk of accidents caused by deteriorating road surfaces.
7. Remote Monitoring and Diagnostics: The system's communication interface allows for remote monitoring and diagnostics, enabling maintenance teams to assess the pavement's condition in real time and schedule necessary repairs without extensive physical inspections.
This combination of durability, cost-efficiency, and advanced monitoring makes the invention a highly effective solution for modern infrastructure challenges.
Those skilled in the art will realize that the above-recognized advantages and other advantages described herein are merely exemplary and are not meant to be a complete rendering of all of the advantages of the various embodiments of the present invention.
In the foregoing complete specification, specific embodiments of the present invention have been described. However, one of ordinary skill in the art appreciates that various modifications and changes can be made without departing from the scope of the present invention. Accordingly, the specification and the figures are to be regarded in an illustrative rather than a restrictive sense. All such modifications are intended to be included with the scope of the present invention and its various embodiments.
, Claims:I/WE CLAIM:
1. A self-healing concrete pavement system using nanomaterials for enhanced durability, comprising:
a. a concrete matrix embedded with nanomaterials, wherein the nanomaterials are configured to detect and respond to microcracks formed within the concrete matrix;
b. a sensor network integrated within the concrete matrix, wherein the sensors are adapted to monitor structural integrity and detect the presence of microcracks;
c. an autonomous healing agent release mechanism, activated in response to signals from the sensor network, wherein the healing agent contains nanomaterials configured to fill and repair microcracks upon release; and
d. a control module operatively connected to the sensor network and the autonomous healing agent release mechanism, wherein the control module processes data from the sensors and initiates the release of the healing agent.
2. The system of claim 1, wherein the nanomaterials include carbon nanotubes and graphene-based particles, configured to enhance the tensile strength of the concrete matrix.
3. The system of claim 1, wherein the healing agent includes microcapsules containing a polymeric solution, which reacts with the nanomaterials to form a durable bond at the site of microcracks.
4. The system of claim 1, further comprising a communication interface configured to transmit structural health data to an external monitoring system for remote diagnostics and analysis.
5. The system of claim 1, wherein the control module includes machine learning algorithms to predict areas of high stress within the pavement, optimizing the release of the healing agent.
6. A method for enhancing the durability of a self-healing concrete pavement system using nanomaterials, comprising:
a. embedding a plurality of nanomaterials within a concrete matrix;
b. integrating a sensor network into the concrete matrix for monitoring the formation of microcracks;
c. detecting microcracks using the sensor network;
d. releasing a healing agent containing nanomaterials into the microcracks upon detection by the sensor network; and
e. repairing the microcracks by interacting the healing agent with the nanomaterials in the concrete matrix.
7. The method of claim 6, further comprising the step of utilizing machine learning algorithms to predict microcrack formation patterns and preemptively strengthen high-stress areas of the concrete pavement.
8. The method of claim 6, wherein the healing agent includes microcapsules that rupture upon contact with the microcracks, releasing a polymeric solution to initiate the self-healing process.
9. The method of claim 6, wherein the sensor network provides real-time monitoring data to an external control system for continuous pavement condition assessment.
10. The method of claim 6, further comprising the step of adjusting the amount of healing agent released based on the size and location of the detected microcracks to optimize the self-healing process.

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