Contribution to the Study of Pathologies and the Management of Civil Engineering Structures: Case of The Bafoussam-Makenene Section of The National Road RN4 in Cameroon

Contribution to the Study of Pathologies and the Management of Civil Engineering Structures: Case of The Bafoussam-Makenene Section of The National Road RN4 in Cameroon

Nie Noumsi Thierry Constant(1), Yamb Emmanuel(2), Ngapgue François(3), Fokwa Didier(4)

(1),(3)Fotso Victor University Institute of Technology, Civil Engineering Department, Research Unit of Industrial Systems and Engineering Environment (UR-ISIE), University of Dschang, Cameroon

(2),(4)Advanced Teacher Training College of Technical Education, Civil Engineering Department, Research Unit of Mechanics, University of Douala, Cameroon

ABSTRACT – In industry, and particularly in the field of civil engineering, it is now essential to

understand the condition of engineering structures. To effectively assess and evaluate their

condition, it is fundamental to analyze the causes of damage throughout their lifespan, which manifest as pathologies. This is all done to establish a diagnosis necessary for decision-making and the determination of maintenance strategies. Therefore, a site survey and inventory, consisting of gathering basic information on the structures, was carried out on the Bafoussam- Makenené section of National Route 4. Following this inventory campaign, an inspection was also conducted on all the engineering structures. Apart from the deterioration observed on the various deck components and the lack of monitoring, the identified structures are in an “acceptable” condition from a structural point of view. Subsequently, Using the Pareto principle, they conducted statistical analyses that allowed them to identify strategic structures requiring enhanced monitoring. They also developed decision-making tools and proposed a flowchart outlining the various steps involved in assessing the condition of a bridge. Finally, the overall work clearly demonstrated the need to assess the condition of the engineering structures along the Ndé River bridge Mlem River bridge route on the Bafoussam-Makenené section of National Route 4 (RN4).

Keywords: Pathologies; Condition; Civil Engineering, Structures; Road; Diagnosis

INTRODUCTION

In the face of increasing economic constraints and the pursuit of sustainable infrastructure management, project owners seek to keep their networks operational over increasingly extended periods. During road construction, several obstacles may arise, including rivers, streams, mountains, railways, and others. Crossing such obstacles requires the construction of artificial structures known as civil engineering structures (bridges, culverts, box culverts, tunnels, as well as large embankments and drains). Several causes underlie the disasters observed on our road networks. For example, on the DoualaYaoundé axis, the collapse of a culvert led to the derailment of the train at Eseka, which resulted in numerous fatalities. Other examples include the scouring of the large embankment on the communal road (Second Bishops Crossroad-Cami Toyota), and the settlement of the large embankment on the CAMN000407 section (Banganté-Bandjoun) of the RN4, which has caused traffic congestion in Bafoussam and traffic jams in the Banganté area, directly impacting transport costs. In addition, in Togo (2008), the collapse of the Amakpapé bridge on the RN1 the main corridor

linking Lomé port with hinterland countries such as Burkina Faso, Niger, and Mali had major economic implications at both national and sub-regional levels [1]. Similarly, in Algeria, the collapse of the bridge on RN77 at PK 101+350 in Setif Province; in Canada (Québec) the collapse of the combined railway and road bridge over the Saint Lawrence River near Lévis (Saint-Nicolas district), which fell first in 1907 and again on September 11, 1916; and in Italy, the collapse of the Genoa Bridge (Northeast) in August 2018 (Ouest France, published 03/08/2020). Following these disasters, we focused our attention on bridge-type civil engineering structures [2].

Several studies have been conducted on the pathology and management of engineering structures in developed countries, but very few in Africa, specifically in Cameroon. This highlights the need for a thorough understanding of the triggering phenomena that lead to these pathologies, and thus a focus on preserving engineering structures while considering all eventualities [3-6].

LITERATURE REVIEW

Fig 2: Distribution of structures by type of bridge and other structures M. ACHRRABI et al (1986)

Studies carried out on files checked in recent years by the engineering works services show the following distribution for the repairs figure 3.

Enlargement 3%

Reconstruction of the Apron 5%

Repair 17%

Reinforcement 15%

Reconstruction

60%

Refurbishment

Fig 3: Allocation for the rehabilitation of structures. M. ACHRRABI et al (1986)

Their work notes that reconstruction represents 60% of the total. Therefore, they highlight the importance of the efforts concentrated by the DRCR (Department of Roads and Highways) to improve the road network’s safety status, as well as the deliberate policy of undertaking safety operations through local alignment adjustments. The aim of their work is to identify deterioration using various devices provided by the monitoring system and to interpret the resulting damage, leading to a diagnosis. This also includes explaining the origins of the deterioration and providing a prognosis, which involves predicting the consequences of the defects. To this end, they compiled a list of structures through a virtual inventory and inspection. This allowed them to simultaneously assess numerous parmeters. Furthermore, the assessment should not be limited to the parts of the structures visible from the roadway, but should encompass the entire structure. This is due to the major problem of accessibility or access routes. This study reveals that in Morocco, a significant number of structures in service were built before the current regulations on loads came into force. In addition to these instances of deterioration, the authors note that it is also necessary to identify any malfunctions (blocked bearings, restricted expansion, poorly functioning joints, etc.) that create parasitic forces, the intensity of which should be verified beforehand.

The author has conducted research on bridge maintenance systems. Bridges are key components of any country’s transportation system. Bridges are costly structures, and therefore, regular maintenance and repair are essential. Nearly one-third of bridges in the United States are estimated to be in deteriorated condition. This research presents the development of a knowledge base for a decision support system for concrete bridges. Ultimately, flowcharts were developed for the proposed decision support system for concrete bridge maintenance. The rules are established using EXSYS Professional Shell to assist the bridge engineer in making decisions regarding bridge girder repairs. The aim of his work in 2007 was to review the currently available literature on concrete, focusing on bridge beam problems. For the author, this study primarily concerns corrosion, cracking, delamination, as well as crumbling, damage caused by vehicle accidents, and scouring. The work involved studying various repair and

rehabilitation methods in practice. It also included developing a summary of repair and rehabilitation strategies from the literature review. Finally, it led to the development of selection criteria and flowcharts for a proposed decision support system designed to assist bridge engineers in making decisions regarding bridge beam and pier repairs. In this context, he developed a knowledge base and flowcharts for such a system. The research methodology can be broken down into several stages. Problems associated with concrete bridge beams and piers were studied. Furthermore, the author established inspection processes and tools to identify various concrete bridge beams and piers. A literature review was conducted on repair materials, techniques, tools, and strategies for concrete bridge beam problems. Subsequently, a decision support system was studied using an expert shell called “EXSYS Professional” by the author. Selection criteria, in addition to tree diagrams, were developed in the final stage. This work suggests that the development of tree diagrams or flowcharts for decision support has been proposed for delamination, cracking, vehicle damage, and scour. The development of an implementation plan for the decision support system and the development of the auxiliary inspection form to extract more data for bridge maintenance have been initiated.

The author focused on bridge pathologies and rehabilitation. Over time, bridges lose the original quality of their materials and some of the strength of their structures. This is true even if these engineering structures were initially very well designed and constructed during the planning and construction phases. This loss of initial performance can be attributed to aging and changes in operating conditions, such as increased traffic and loads for which the structure was designed. The research conducted here is primarily focused on diagnosing a bridge in a pathological state, identifying the nature of the various defects and their probable causes, understanding the different inspection methods to be used, and, where applicable, the procedure for evaluating the structure in order to propose a repair or reinforcement project. In this context, he cataloged various problems and their probable causes; then discussed the different inspection methods used and, where applicable, carried out an assessment of the structure. This work resulted in the availability of the knowledge necessary to diagnose a bridge in a pathological condition [7-10].

The authors worked on diagnosing bridge and road pathologies in Brazil. Infrastructure is an essential and decisive element of a country’s economic development. In this context, bridges are of fundamental importance to society and the economic development of cities. The aim of this work is to present an overview of bridges in the southern region of Brazil, specifically in the city of Pato Branco. The goal is to identify the most recurring damage in order to provide a basis for administrators and ensure the proper functioning of the transport infrastructure. To this end, they collected data using visual methods and photographic records. After analysis, the author identified several pathologies affecting both concrete and wooden bridges. These problems can be summarized as damage caused by humidity, cracks, corrosion, erosion, clogged drains, rotten wood, uneven pillars, and foundation compression, among other issues. This work reveals that the main aspects of each structure, such as location, superstructure material, length, road width, type of structure, and estimated age, led to the identification of the structures. The city of Pato Branco is responsible for 66% of the bridge administration (Figure 11). Other bridges in the road network are managed by the DNIT (5%) and the DER-PR (2%).

Bridge Administration Pato Branco

Pato Branco/ Itapejera D’Oeste

Pato Branco/Vitorino Pato Branco/Manopolis DNIT-BR158

Pato Branco/Clevelandia

66%

Particular

Pato Branco/Honorio Serpa

DER-PR 280

Fig 4: Distribution of Bridge Administrations. Moacir KRIPKA et al (2012)

The structural model adopted for the construction of bridges in the city of Pato Branco is that made of round timbers or roughing beams and in concrete bridges, of beams and slabs (Fig 5).

Number of bridges

BePaomutsres

SPcoorptéee

BPriodngtes 50 8

Fig 5: Structural model of the bridges of the city of Pato Branco.Moacir KRIPKA et al (2012)

They categorized the bridges according to their length. Thus, the existing bridges in the city are comprised of 74% small bridges less than 10 meters long and 90% with a span of less than 20 meters (Fig 6). Concrete bridges have a surface area of 765.70 m² and wooden bridges

197.25 m². The longest bridges are managed by state and federal government agencies. It is worth noting that, in the case of small bridges, we observed a lack of attention to design, construction, operation, maintenance, and other aspects of care that are essential for bridges.

Number of bridges

PBornitdsges

Fig 6: Length of bridges in the city of Pato Branco. Moacir KRIPKA et al (2012)

Obtaining precise data on the age of the bridges (Fig 7) is difficult due to the lack of records kept by the agency authorities. The information in this table is derived from the registration plates affixed to the bridges and the markings made on the fresh concrete.

Number of bridges

Fig 7: Distribution of the estimated age of bridges in the city of Pato Branco Moacir KRIPKA et al (2012)

The bridges in the town of Pato Branco were built with readily available materials, consisting of 48% wood and 52% concrete (Fig 8). However, it should be noted that the lack of planning and qualified technical staff to handle these materials ultimately resulted in a multitude of pathologies.

Number of bridges

0 Total

DrBinokis

CoBnectroente

BProidngtess 58 28 30

Figure 8: Bridge superstructure material in the city of Pato Branco Moacir KRIPKA et al (2012)

Bien Précaire Tolérable

Fig 9: Apparent stability conditions in accordance with standard 010/2004 PRO DNIT Moacir KRIPKA et al (2012).

The author believes it would be desirable for those responsible for the implementation and maintenance of this public domain to develop a bridge management plan. This would ensure better physical and financial performance, as well as greater safety for the public.

The author has worked on the management of engineering structures and their lifecycle, based on a cross-cutting approach from modeling to decision-making. The aging of

infrastructure assets, their maintenance, and their management constitute one of the challenges of the 21st century. Identified during the previous century, this issue requires us to rethink our methods, methodologies, and our ability to integrate new technologies. The aim of this work was to propose a relevant response to the complexity of decision-making. According to the author (2015), this complexity stems from various aspects inherent to this type of decision It [11-13]. is multi-scale (system/network, infrastructure, structure, etc.), multi-criteria, multi- stakeholder, multi-temporal, and uncertain (presence of risks, incomplete information, lack of knowledge, etc.). It relies on highly heterogeneous data (qualitative, quantitative) and can sometimes be subjective (political dimension). The work has led to the development of methodologies for the optimized management of infrastructure portfolios. It has also broadened knowledge of methods and tools related to life-cycle cost analysis and the integration of structural health monitoring strategies into the management of engineering structures [14-15].

The work highlights a need for generic integrated management models to guide design and construction decisions in order to control, on the one hand, the economic and environmental impact of construction and, on the other hand, to increase the robustness of structures in the face of accidents. It also addresses the planning and justification of maintenance operations, with a focus on cost/performance optimization, and the justification of monitoring (inspection), maintenance, and repair/replacement procedures by quantifying their operational benefits in terms of reducing uncertainty in decision-making processes and overall cost reduction. He worked on the issue of bridge maintenance, focusing on management tools. The management of engineering structures is therefore becoming a crucial issue for the economies of all countries. According to the author, this requires the design of a Bridge Management System (BMS) [16]. This aims to improve management procedures and promote preventive bridge maintenance. He establishes a health assessment (a check-up) of the structures before the foreseeable onset of problems, such as the appearance of oxidized reinforcement [17-19].

His work reveals that, through a simplified yet realistic calculation of the structure, its actual behavior can be approximated. The effects of fixed and variable loads are approximated through calculations for each structural component (beams, slabs, hammer piers), ensuring that the simplified model approximates the complex behavior with a deviation of less than 10%. For simply supported beams, a good assessment of their strength is considered to involve checking their bending resistance at mid-span and their shear resistance at the support. In 2018, the author observed that quantitative indicators compare the resisting forces to the applied forces. The higher the indicator, the greater the strength of the structural element. In the case of prestressed structures, the resistance effect is very strongly linked to the integrity of the prestressing. Tables 1 and 2 provide the classification of the structure’s condition based on the percentage of prestressing required relative to the initial prestressing [20-23].

Table 1: Classification of Bridge Condition According to Prestress Percentage (ULS)

Table 2: Classification of Bridge Condition According to Prestress Percentage (SLS) [24]

1

It defines the overall QR indicator for the resistance of beams to bending, shear force, and for the resistance of the floor slab, by retaining the maximum of the different coefficients. A structure is then classified among the 5 given in Table 3 [25-27].

Table 3: Global Quantitative Risk Indicator for a Structure

This work (2018) made it possible to derive the identified factors from the severity ratings, using a weighting system. Following tests carried out on about ten works, a selection of weighting ratings per theme was proposed and adopted, leading to the classification of the works into 5 risk clases (Table 4) [28-30].

Table 4: Classification of Bridges According to Risk (APR)

The author therefore suggests combining these indicators to assess the mechanical condition, taking into account the likely state of the preload. A decision-making matrix has been proposed and is illustrated in Table 5 [31- 33].

Table 5: Percentage of Structures Belonging to Each (APR, QR) Pair

The author has worked on a decision-support tool applied to engineering structures. He observes that structures can be affected by defects of varying severity, stemming from multiple causes. The author’s work aims to develop a geographic information system (GIS) that serves as a decision-support tool for engineering structure managers. In this work, he used a method based on visual inspection of the damage. This inspection drew upon the pathology of engineering structures, which allowed for the classification of the four structures according to the principles of the quality image assessment of engineering structures (QIAS). This work resulted in the classification of the four structures according to the IQOA method. We have the box girder bridge at PK44+300 (class 2ES), the composite bridge at PK44+700 (class 3), the rail bridge at PK46+600 (class 2E), and the central underpass at PK46+850 (class 2) [34-35].

Classification of Bridge Condition

The condition of the bridges is characterized by the selection of one of five condition classes, possibly supplemented by an “S” designation for user safety (see Table 6) [36].

Table 6: Classification of Structures According to the IQOA Method

According to the approach to assessing the class in which a bridge should be placed is carried out according to the process summarized in the flowchart of Figure 10. The decision elements refer to a set of notions and terms concerning the different parts of bridges to be considered and the types of intervention, the definitions of which are provided afterwards [37- 38].

Apparent condition of the structure

Fig 10: Flowchart of the Methodology for Bridge Classification

Equipment

The author (2017) defines equipment as devices added to the load-bearing structure and designed to allow the user to operate the structure in satisfactory conditions of comfort and

safety. It also facilitates structural monitoring and maintenance, and improves its aesthetics [39- 40].

The most frequently encountered structural equipment, presented in Table 7, is as follows:

Table 7: Summary of Bridge Equipment [41]

With C: comfort and safety of the user, A : aesthetics, S: monitoring.

The author presents an example of the classification of four bridges on the RN12 in Table 8.

Table 8: Example of Classification of 4 Bridges on the RN12

The structures are classified according to the most unfavorable class of each element type, summarized in Table 9 [42-44].

Table 9: Summary of Final Classifications of Structures

MATERIALS AND METHODS

Study site location: The study covers the West Region. The project area is bounded by the following geographic coordinates:

• Latitude: 5° 30′ 0 North
• Longitude: 10° 40′ 0 East The project consists of three sections, as shown in Table 10.

Table 10: Different Sections of the Study Itinerary

Fig11: Delimitation of the Study Area (Forêtcommunale-Cameroun.org)

Choice of the Itinerary

Over forty years old, the bridges and overpasses on National Route RN4 were built in the 1980s. This road underwent improvements to bring it up to the standard requirements of a major highway. Since then, apart from occasional routine maintenance, these structures have not undergone any further improvements. However, subjected to the combined effects of climate variations, traffic (growth and stress from overloaded axles), and of course, the passage of time, these structures are showing signs of fatigue, cracks, and deformations that are worsening due to the lack of specific interventions. It is to address this potentially catastrophic failure that they undertook a study of the bridges and overpasses on the Bafoussam – Makenene section of National Route 4 in Cameroon [45-46].

Methods

RESULTS

With regard to the bridges, each structure, in general, was subjected to a thorough examination. The deterioration, by category of structural elements, was established based on visual observations. To assess the evolution of the different states throughout the life cycle of the structures, they adopted four classification levels: fairly good, good, average, and poor. To ensure the success of these operations on the Geographic Information System (GIS), a number of requirements were met:

• Verification of topographic maps to allow work across the entire study area,
• Development of a database and display of a point cloud,
• Thematic analysis.

Classification of works Classification of works

Fig 12: classification of structures according to degradation groups

In addition, table 12 presents the main degradations classified according to their degree of recurrence and also the different Pareto diagrams [51-54].

Table 12: Classification of Degradations According to Their Degree of Recurrence

% Partiel % Cumulés

Log. (% Cumulés)

Densité % Partiel Puissance (% Partiel)

Fig 14: Histogram of the Pareto Diagram of Bridges in the Study Area

For each of these degradations, adequate solutions were identified and are presented in Table 13.

Table 13: Adequate Solutions Adopted Sizing of bearings; supply and installation; choice of bearing type according to structure type

For culverts, each structure, in general, was also carefully examined. The degradations by category of elements were established based on visual observations. In addition, Table 14 and the Pareto diagrams present the main degradations according to their recurrence [55-57].

Table 14: Classification of Degradations According to Their Degree of Recurrence (Culverts)

y = 38,045ln(x) + 12,547 R² = 0,9646

0 0

1 2 3 4 5 6 7 8 9

% des désordres % Cumulés Densité % Partiel Puissance (% Partiel)

Fig 15: Histogram of the Pareto Diagram of Culvert Degradations

0,5 2,5 4,5 6,5 8,5

100 100

100

y = 54,711x-1,895 R² = 0,9078

BM BB D BA BP

y = 13,835ln(x) + 77,353 R² = 0,9937

0 0

BM BB D BA BP

% par types % Cumulés Densité % Partiel Puissance (% Partiel)

Fig 16: Histogram of the Pareto Diagram of Different Types of Structures

y = 44,934ln(x) + 34,749 R² = 0,9901

% Partiel % Cumulés

>20 <20 <100 >100

Densité % Partiel Puissance (% Partiel)

Fig 17: Histogram of the Pareto Diagram of Bridge Openings

For a sound analysis, we defined the population, the statistical unit, the studied variable, and the nature of the variable. This variable was classified as a quantitative discrete variable. This enabled us to produce the tables showing position and dispersion characteristics [59-60].

Table 15: Statistics of Bridge Degradations (OA) According to Number

y = -1,1173×2 – 4,0135x + 103,07 R² = 0,9932

y = 0,9408×2 + 4,6719x + 0,9195 R² = 0,9991

% Cumulés Croissants % Cumulés décroissants

Fig 18: Histogram of the Cumulative Frequencies of Bridges

Table 16: Statistics of Culvert Degradations (OH) According to Number

y = -0,8341×2 – 3,9954x + 103,79 R² = 0,9909

y = 0,7134×2 + 4,544x – 0,7704 R² = 0,9979

% Cumulés décroissants % Cumulés Croissant

Fig 19: Histogram of the Cumulative Frequencies of Bridges

Table 17: Statistics of the Types of Structures Studied and According to Their Span

Text dommage

Document analysis

Auscultation and precise diagnosis of the state of the structure

Visual observation

Safety of the structure

Detection, identificatio n and observations of degradations

Laboratrory analysis

Detection, identificatio n and observation of tastings

Visuel inspection

Estimation and predictions of degradation assessment

Predictive model

Determination of the objectives of repair or strengthening

Selectio n of the best suited technical methods

Putting the specification s of the preparation or strengthning projet

Realizati on of the work

Control and reception of work

Monitorin g of the effectiven ess of receipt or strengthen ing, manageme nt, surveillanc e, now of the work

Situation analysis

Fig 20: Organization chart of the various stages to follow for the assessment of the condition of a bridge

DISCUSSION

After conducting various laboratory tests, the following results were observed:

Thematic analysis of equipment such as safety devices revealed that 9.09% of the safety devices on the Bafoussam – Makenene section are in good condition, 9.09% are in poor condition, and 81.8% are in fair condition.

The condition of the bridges is characterized by selecting one of six condition classes, highlighting only structures in classes C and D on our study route.

Based on ABC diagrams, we classify the defects and structures into three classes as follows:

• Class A:

• The disorders that account for 80% of the bridge pathologies in the histogram of Figure 13 are 5 out of 8 and range from D8 to D4. These correspond to environmental pathologies and construction-related pathologies.
• The structures that account for 80% of management problems in our study area in the histogram of Figure 14 are 9 out of 11.
  • Class B:
• The disorders that represent 15% of the bridge pathologies in the histogram of Figure 13 are 2 out of 8 and range from D3 to D2. These also correspond to environmental and construction-related pathologies.
• The structures that represent 15% of the management problems in our study area in the histogram of Figure 14 are 2 out of 11.
  • Class C:
• The disorder that represents 5% of the bridge pathologies in the histogram of Figure 13 is 1 out of 8, which is D1. This corresponds to design pathologies [61-63].
• The structure that represents 5% of the management problems in our study area in the histogram of Figure 14 is 1 out of 11.

  We can therefore observe that the Pareto 20/80 principle is verified. Thus, according to Pareto, the bridge pathologies and management problems to be treated as a priority are environmental and construction-related. For each of these degradations, adequate solutions were identified and presented in Table 12 [64].

  According to the ABC diagrams, we classify the disorders and structures into three classes as follows:

  • Class A: The disorders that account for 80% of culvert pathologies in the histogram of Figure 15 are 6 out of 9, ranging from D9 to D4. These correspond to environmental and construction-related pathologies.
  • Class B: The disorders that represent 15% of culvert pathologies in the histogram of Figure 15 are 2 out of 9, ranging from D3 to D2. These also correspond to environmental and construction-related pathologies.
  • Class C: The disorder that represents 5% of culvert pathologies in the histogram of Figure 15 is 1 out of 9, which is D1. This corresponds to environmental and construction-related pathologies.

    Again, the Pareto 20/80 principle is verified. Thus, according to Pareto, the culvert pathologies and management problems to be treated as a priority are environmental and construction-related. From our study, our itinerary includes five types of civil engineering structures: Metal Culverts (MC), Concrete Culverts (CC), Box Culverts (BC), Reinforced Concrete Bridges (RCB), and Prestressed Concrete Bridges (PCB). Concerning bridges, their choice and design depend on several factors, such as functional data, highlighting here the span. Hence, the Pareto diagrams were developed for their analysis [65].

    According to the ABC diagrams, we classify the disorders and structures into three classes as follows:

  • Class A:
• The structures that account for 80% of the types of structures in the histogram of Figure 16 are metal culverts, with a ratio of 105/134 in our study area.
• The structures that account for 80% according to their span in the histogram of Figure 17 are structures with spans > 20 and also < 20, totaling 4/11 and 3/11, respectively.
  • Class B:
• The structures that represent 15% of the types of structures in the histogram of Figure 16 are concrete culverts and box culverts, with a ratio of 10/134 for CC and 8/134 for BC.
• The structures that represent 15% according to their span in the histogram of Figure 17 are those with spans > 100 and 100, each totaling 2/11.
  • Class C:
• The structures that represent 5% of the types of structures in the histogram of Figure 16 are bridges, with a ratio of 7/134 for RCB and 4/134 for PCB [66].

We can therefore conclude that the Pareto 20/80 principle is verified. Thus, according to Pareto, the types of structures to be treated as a priority are culverts, although bridges are not excluded, as they represent the Pareto tail, hence the use of Demings Wheel (PDCA cycle). From Table 14, we observe that the most frequent pathology for bridges corresponds to the mode (8). Our study shows that the number of disorders averages 5 for the pathologies recorded during the investigation campaigns. The confidence interval is 85.71%, which leads to pathologies with a number of disorders around an average of 5.31 and standard deviation of

2.22 disorders. About 50% of the pathologies in our study involve at least 5 disorders out of 8.

From Table 15, we observe that the most frequent pathology for culverts corresponds to the mode (9). Our study shows that the number of disorders averages 6 for the pathologies recorded during the investigation campaigns. In our study, the confidence interval is 79.54%, leading to pathologies with a number of disorders around an average of 6, with a standard deviation of 2.43 disorders. About 50% of the pathologies involve at least 6 disorders out of 9 [67].

We note that the value of the median is close to the mean, indicating that the distribution of values is symmetric.

From Table 16, our study shows that metal culverts ar the most numerous structures, with a mode of 1. Regarding spans, the mode is 2. Thus, culverts are the most degraded types

of structures, with an average of 1. Concerning spans, the average span is 2. Consequently, 97.01% represents the confidence interval percentage for structure types, with an average around 1.48 per structure type and a standard deviation of 1.006. Similarly, 82% represents the confidence interval percentage for spans, with an average around 2.27 depending on the span and a standard deviation of 1.052 [68].

RECOMMENDATIONS

In the end, it is clear that the overall work carried out for the management of civil engineering structures is multidisciplinary: it involves both the manager (project owner), who aims to ensure the durability of the assets, and the inspector (design office or contractor), responsible for identifying and quantifying the defects. All these approaches therefore converge toward the same goal: not only to detect disorders and their causes as early as possible in order to promote minor maintenance over major repairs, but also, and above all, to minimize risks to the structure and its users. Although it has been demonstrated that most of the disorders recorded on structures occur during the operation phase, it is nonetheless important to emphasize that strictness during the design and construction phases would prevent many complications during maintenance and also in the repair of defects (see the issue caused by the absence of bearing bosses). At the end of our study, we recommend stricter control during the execution of structures with particular emphasis on: The construction of waterproofing systems (deck slab coating, scuppers, and downpipes), The selection and installation of bearing devices (always providing systems for their maintenance), Concrete mix design (water content and quality, reinforcement cover, aggregate size), Its implementation (vibration, compaction, etc.) [69-70]. Hence, the necessity and importance of a quality assurance plan (QAP) for civil engineering structures [70-71].

CONCLUSION AND PERSPECTIVES CONCLUSION

This research work focused on the pathologies and management of civil engineering structures for the assessment of their condition and the enhancement of their durability. Based on the above, the following conclusions are made:

• The stock of civil engineering structures is relatively recent, as approximately 30% of bridges managed by the Directorate of Road Operations and Maintenance are less than 50 years old,
• An overall view of the stock of civil engineering structures in our country, based on the inventory and inspection carried out in 2015, even though it was only based on visual observations,
• Thus, at the end of this work, we can affirm that given the complexity of road network management, the use of Geographic Information Systems (GIS) constitutes a considerable time-saving advantage: The ability to quickly visualize, in map form, the position of an infrastructure and access its characteristics from the office provides a daily time-saving benefit for users. Moreover, one of the main strengths of GIS is the ability to provide unified management of all data related to the network. After thematic

  analysis of equipment such as safety devices, it was observed that 9.09% of safety devices along the BafoussamMakenene section are in good condition, 9.09% in poor condition, and 81.8% in average condition. This makes it possible, through a single tool, to integrate all parameters essential to achieving a satisfactory level of safety [72-75].

  PERSPECTIVES

  At the end of this work, it becomes clear that there remain numerous aspects worth further investigation or exploration, such as:

• A deeper study of the issue of the durability of civil engineering structures in Cameroon, so that the elaboration of the influencing factors of this durability is considered across different regions,
• The establishment of a Quality Assurance Plan (QAP).

ACKNOWLEDGEMENTS

The authors would like to thank Professor Emeritus FOGUE Médard and Professor FONKWA Didier for reviewing this work and providing their valuable contribution to its completion.

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