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Comparative geotechnical analysis for ultimate bearing capacity of precast concrete piles using cone resistance measurements

  • Alaa M. Shaban EMAIL logo , Zahraa H. Al-Hashimi , Bashar H. Aleshaiqer and Paul J. Cosentino
Published/Copyright: April 9, 2024
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Open Engineering
From the journal Open Engineering Volume 14 Issue 1

Abstract

Computing the axial load capacity of pile foundations is often challenging for geotechnical engineers. Different theoretical and empirical approaches were proposed for determining the ultimate bearing capacity. Among these approaches, the in situ testing methods are based on cone penetration test (CPT) measurements. This study compares five CPT methods in estimating the axial load capacity of precast concrete piles evaluated at four piling construction projects in Northwest and Central Florida. The analytical methods used in this work are the Aoki and De Alencar method (1975), the Schmertmann method (1978), the Bustamante and Gianeselli Laboratoire Central des Ponts et Chausees method (1982), the Eslami and Fellenius method (1997), and the Eurocode 7 (2007). The outcomes indicated that the Eurocode method 7 had the most increased load capacity estimates, whereas the Eslami and Fellenius method yielded the lowest estimates. The results also indicated that the Aoki and De Alencar (1975) method consistently demonstrated the slightest differences among these values, showing its potential for reliable and consistent pile-bearing capacity estimations.

Keywords: axial load capacity; precast concrete piles; CPT measurement

1 Introduction

A precast concrete pile is one of the most favored forms of deep foundations. It is widely utilized in different engineering projects due to its versatility and suitability in a wide range of ground conditions. This type of pile is a pre-produced, elongated concrete member driven into the ground using a hydraulic or diesel hammer to a total depth ranging from 3 to 20 m. The ultimate bearing capacity and settlement are the governing criteria that must be considered in the design of axially load piles [1]. However, determining the axial load of a pile is a difficult task due to variations in soil properties and the type and shape of piles. To address these variable conditions, various design methods have been proposed and categorized into four analytical approaches: static analysis, dynamic analysis, full-scale loading methods, and in situ testing methods [2].

The in situ testing methods recently became the most common predictive method used in pile design due to fast developments in testing techniques, improved understanding of soil characteristics, and the subsequent insight into the inadequacies and limitations of some conventional laboratory testing methods [3,4]. Different in situ testing techniques have been developed and utilized for identifying soil properties and characterizing pile capacity. However, most of the field characterization techniques produce soil measurements with a high level of uncertainty, and the interpretation of these measurements depends merely on an empirical basis. The development of the cone penetration test (CPT) technique provides a direct logging device that gives a detailed description of the stratigraphic profile of the soils [5,6].

Several publications have highlighted the importance of using CPT in geotechnical investigations [7,8]. The benefits of using CPT in subsurface exploration include its rapid and direct testing, cost-effectiveness, throughput, reliable and repeatable measurements, and a clear view of the nature of undisturbed soil layers. In addition, the CPT provides a comprehensive theoretical basis for interpreting its parameters. Despite these advantages, CPT has disadvantages, such as the need for a well-trained operator, inability to retrieve soil samples, and challenges in performing tests in hard and rocky layers.

Over the last four decades, the CPT penetration process has been investigated by many experimental and theoretical studies to capture actual soil behavior [9,10,11,12,13,14,15,16]. Through these studies, profound comparisons between CPT measurements and the results of different field and laboratory tests have been examined, and several CPT-soil design methods have been developed. The CPT measurements established for pile design are tip cone resistance (q c), sleeve friction (f s), and pore water pressure (u 2). Several studies utilized cone measurements to develop empirical formulas that compute the capacity of driven piles (i.e., precast concrete piles). The final results of these empirical correlations can provide insight into how well these methods predict pile capacities.

This research primarily focuses on implementing a comparative analysis using five common pile design methods to predict the axial load capacity of piles based on CPT measurements. The analytical methods employed include the Aoki and De Alencar method (1975), the Schmertmann method (1978), the Bustamante and Gianeselli Laboratoire Central des Ponts et Chausees (LCPC) method (1982), the Eslami and Fellenius method (1997), and the Eurocode method 7 (2007). The expected results aim to provide an inclusive understanding of the static soil behavior along the pile’s shaft and base in the field, using the measurements resulting from field tests.

2 CPT methods for determining pile capacity

The study used a comparative analytical approach to evaluate the axial load capacity of precast concrete piles on construction projects located in northwest and central Florida. There are four different road projects: Ramsey Branch Road (RBS), Deer Street Crossing (DCS), State Road 417 (SR 417), and the Anderson Street Overpass (ASO). The main tool utilized to assess a pile's load capacity is the measurement of CPTs. The design used five different CPT methods: Aoki and de Alencar (1975), Schmertman (1978), Bustamante and Giancelli (1982), Islami and Velenius (1997), and Eurocode 7 (2007). This broad selection aims to evaluate the differences and effectiveness of each technique of each method in determining pile load capacity. A combination of formulas and properties, such as pore water pressure, sleeve friction, and cone tip resistance, were used to determine the tip and side friction resistance. For example, in Eurocode 7, the axial load capacity is determined directly from the cone tip resistance. In contrast, several electronic piezo parameters and measurements have been used in Eslami and Fellenius techniques to calculate unit side friction and end-bearing resistance. The following subsections present the most common approaches for determining the pile-bearing capacity from CPT results.

2.1 Aoki and De Alencar method (1975)

Based on cone tip resistance from CPT results, Aoki and De Alencar [17] developed empirical formulas to determine the ultimate toe-bearing (q b) and side-friction (q s) of piles embedded in a range of soil types, including sand, silt, and clay.

(1) q b = q ca ( tip ) Fb ,

(2) q s = q ca ( side ) C s FS ,

where q ca ( tip ) is the average cone tip resistance over a zone ranging from 4d below the pile tip to 8d above the pile tip, q ca ( side ) is the average cone tip resistance for each soil layer, Fb and Fs are empirical factors depending on the pile type, as illustrated in Table 1, C s is a coefficient determined based on the soil type, as listed in Table 2, and d is the pile width or diameter. The ultimate toe-bearing resistance resulting from equation (1) is limited to a maximum value of 150 tsf. However, equation (2) yields a maximum side-friction resistance of 1.2 tsf.

Table 1

Fb and Fs values for various types of piles

Pile type Fb Fs
Franki piles 2.50 5.0
Steel piles 1.75 3.50
Precast concrete piles 1.75 3.50
Bored piles 3.50 7.0
Table 2

C s values for various types of piles

Soil type C s (%) Soil type C s (%) Soil type C s (%)
Sand 1.4 Silt 3.0 Clay 6.0
Silty sand 2.0 Sandy silt 2.2 Sandy clay 2.4
Clayey silty sand 2.4 Clayey sandy silt 2.8 Sandy silty clay 2.8
Clayey sand 3.0 Clayey silt 3.4 Silty clay 4.0
Silty clayey sand 2.8 Sandy clayey silt 3.0 Silty sandy clay 3.0

2.2 Schmertmann method (1978)

This pile design method evolved from research on full-scale piles investigated by Nottingham [18]. Then, it was further amended by Schmertmann [19] to calculate the end bearing and side friction resistance of piles. Equation (3) gives the basis for the determination of end-bearing using data from cone tip penetrometer (q). The end-bearing computation procedure remains the same for the piles driven in clay, sand, and mixed soils. This method defines the pile tip resistance within a specific zone. This zone is defined as a range from 8d above the pile's tip and 0.7d to 4d below the pile's tip.

(3) q b = q c 1 + q c 2 2 ≤ 150 MPa ,

where q b is the ultimate toe-bearing resistance of the pile, q c 1 is the minimum of the average q c over a distance ranging from 0.7d to 4d below the pile’s tip, q c 2 is the minimum of the average q c over a distance 8d above the pile’s tip, and d represents the pile’s diameter or width. Note that the maximum end-bearing capacity in equation (3) is limited to 150 MPa. The unit-side friction resistance of piles is obtained from CPT sleeve-friction results (f s). In sand layers, the side friction resistance is computed using equation (4), which expresses local pile–soil friction at two depths: (1) penetration depth measured from the ground surface to a depth equal to 8d, and (2) embedment depth measured from 8d to the pile’s tip:

(4) q s = k s ∑ y = 0 y = 8 d l 8 d . f s A s + ∑ y = 8 d y = L f s A s ,

where q s is the ultimate pile-side friction capacity in sand soils, k s is the factor computed as a function of pile depth-to-width ratio, q c 2 is the minimum of the average soil resistance over a distance 8d above the pile’s tip, d is the pile width or diameter, l is the depth to f s considered, A s is the pile–soil contact area (i.e., surface area), f s is the sleeve friction resistance, and L is the length of pile.

The fiction capacity of piles in clay layers is predicted using equation (5). Schmertmann [19] stated that the maximum pile side-friction resistance obtained from this equation should not exceed 120 kPa:

(5) q s = k c f s ≤ 120 kPa = 1.2 tsf ,

where q s is the ultimate pile-side friction capacity in clay soils, k c is a correction factor computed using sleeve friction results, and f s is the sleeve friction resistance obtained from the CPT.

2.3 Bustamante and Gianeselli (1982)

This method, also known as LCPC-Laboratoire Central des Ponts et Chausees, was derived from the results analysis of 197 different static load tests in Europe [20]. The LCPC method utilized the cone tip resistance and factors related to soil and pile types for computing the pile's axial load capacity. The end-bearing resistance is determined as follows:

(6) q b = k b q eq ( tip ) ,

where q b is the ultimate toe-bearing resistance of the pile, k b is the bearing capacity factor computed based on soil and pile type, and q eq ( tip ) represents the average cone tip resistance within a zone ranging at 1.5d below and above the pile tip (i.e., cone tip resistance data that are greater than 1.3 average value and those that are smaller than 0.7 average value are neglected). The basic formula for estimating the unit-side friction resistance is given as follows:

(7) q s = q eq ( side ) k s ,

where q s is the ultimate pile-side friction resistance, k s is the side friction factor computed based on soil and pile type, and q eq ( side ) is the representative tip resistance for the corresponding layer. Tables 3 and 4 present the values of k b and k s that depend on the installation method of pile and type of the soil.

Table 3

Bearing capacity factor for different piles and soil types

Type of soil q c / P a k b
Bored piles Driven piles
Soft clay and mud <10 0.40 0.50
Moderately compact clay 10–50 0.35 0.45
Stiff clay and silt >50 0.45 0.55
Silt and loose sand ≤50 0.40 0.50
Gravel and moderately compact sand 50–120 0.40 0.50
Well-compacted sand and gravel >120 0.30 0.40
Soft chalk ≤50 0.20 0.30
Weathered to fragmented chalk >50 0.20 0.40

P a : reference stress = 100 kPa = 0.1 MPa = 1 tsf.

Table 4

Side-friction factor for different piles and soil types

Type of soil q c / p a k s
Bored piles Driven piles
Without casing With casing Concrete Steel
Soft clay and mud <10 30 30 30 30
Moderately compact clay 10–50 40 80 40 80
Stiff clay and silt >50 60 120 60 120
Silt and loose sand ≤50 60 150 60 120
Moderately compact sand and gravel 50–120 100 200 100 200
Well-compacted sand and gravel >120 150 300 150 200
Soft chalk ≤50 100 120 100 120
Weathered to fragmented chalk >50 60 80 60 80

P a : reference stress = 100 kPa = 0.1 MPa = 1 tsf.

2.4 Eslami and Fellenius (1997)

This method relies on the electronic piezocone measurements of 330 CPT and pile load tests to determine the axial load capacity of different piles. This method, which is also known as the UniCone design approach, requires determining various geo-parameters for each soil layers based on CPT data [21]. Then, the unit-side friction resistance and the end-bearing resistance of a pile are calculated as follows:

(8) q b = q E × 10 ( 0.325 × I c − 1.218 ) ,

where q b is the ultimate toe-bearing resistance of the pile and q E is the effective cone resistance that is determined as follows:

(9) q E = q t − u 2 ,

I c is the soil behavior-type index.

q t and u 2 are the corrected cone tip resistance and pore pressure, respectively, measured from the pile’s tip to one diameter beneath the pile’s tip. Robertson [13] proposed the following formula to calculate the soil behavior type index, I c:

(10) I c = [ ( 3.47 − log Qtn ) 2 + ( 1.22 + log F ) 2 ] 0.5 ,

(11) Qtn = q t − P vo P a P a P ́ vo n ,

where Qtn is the normalized cone penetration resistance and F is the normalized sleeve friction that is determined as follows:

(12) F = f s ( q t − P vo ) × 100 ,

where P a is the atmospheric pressure (i.e., 100 kPa), P vo is the total overburden pressure, P ́ vo is the effective overburden pressure, and n is the stress exponent is dependent soil factor, which is equal to 1 for clays, 0.75 for silts, and 0.5 for sands. The exponent can also be estimated as follows:

(13) n = 0.381 × I c + 0.05 P ́ vo P a − 0.15 ≤ 0.1 .

The unit side-friction resistance can be calculated as follows:

(14) q s = q E × θ PT × θ TC × θ rate × 10 ( 0.732 × I c − 3.605 ) ,

where q E is the effective cone resistance along the pile side, θ PT is the pile type factor (1.13 for driven, 1.02 for jacked, and 0.84 for bored piles), θ TC is the coefficient for loading direction (1.11 for compression and 0.85 for tension), θ rate is the rate of coefficient (1.09 for constant rate and 0.97 for maintained load tests), and I c is the soil behavior-type index.

2.5 Eurocode 7 (2007)

Eurocode 7 [22] standard gives a direct procedure for determining the maximum axial load capacity of a single pile based on direct use of the cone tip resistance. According to Part 2 of Eurocode 7, the pile base and shaft resistance are derived as follows:

(15) q b = 0.5 × CF p × β × s q c; I ;mean + q c;II , mean 2 + q c;III , mean ,

where q t is the ultimate toe-bearing resistance of the pile, CF p is a factor for defining the pile's type as listed in Table 5, β is the pile point shape factor, and s is the pile base shape factor that is given as follows:

(16) s = 1 + sin θ ́ r ( 1 + sin θ ́ ) ,

where L is the large side of the rectangular pile point, B is the smaller side of the rectangular pile point, θ ́ is the effective angle of shearing resistance, and r is defined as the ratio of the large side to the smaller side of the pile point. The influence of soil strata below and above the pile base is considered by calculating the mean values of cone tip resistance (i.e., q c;I;mean , q c;II;mean , q c;III;mean ). These values are determined over depth intervals running below and above the level of the pile base as given in the following formulas:

(17) q c;I;mean = 1 d crit ∫ 0 d crit q c;I d z ,

(18) q c;II;mean = 1 d crit ∫ d crit 0 q c;II d z ,

(19) q c;III;mean = 1 8 D eq ∫ 0 − 8 D eq q c;III d z ,

where d crit is the critical depth that typically ranges from 0.7 D eq to 4 D eq , and D eq represents the equivalent diameter of the pile base. As given in equation 20, the basis for calculating the pile shaft resistance is the cone tip results (i.e., sleeve friction is not utilized in the calculation procedure)

(20) q s = a s × q c; z ,

where q t is the ultimate side-friction resistance of the pile, q c; z is the cut-off value of q c at depth z, and α s is the shaft resistance factor that depends on the types of soil. For sand and gravelly sand soils, a s typically ranges from 0.012 to 0.005, while for clay and silt soils, a s typically ranges from 0.020 to 0.025.

Table 5

Maximum values of pile class factor ( CF p )

Pile class CF p
Driven prefabricated piles 1
Cast in-place piles made by driving a steel tube 1
Flight auger piles 0.8
Bored piles with drilling mud 0.6

3 Piles testing sites

In this work, the CPTs were conducted on four piling construction projects in Northwest and Central Florida. The CPT soundings were continued to a depth greater than 20 m to have a continuous profiling of soil characteristics. Table 6 provides a detailed description of the names of sites and the properties of the driven piles.

Table 6

Summary of high pile rebound sites identified by FDOT

Site Type Size Length (m)
ASO Prestressed concrete pile 60 cm2 38
DCS Prestressed concrete pile 60 cm2 25
RBS Prestressed concrete pile 60 cm2 27
SR417 Prestressed concrete pile 60 cm2 30

4 Results and discussion

The bearing capacity of precast piles was examined in four roadway projects in which precast concrete piles were constructed: the ASO, Dear Crossing Street (DCS), Ramsey Branch Street (RBS), State Road 417 (SR417). For the piles at ASO, the results analysis showed that the bearing capacity increased as the depth of the piles increased. This observation was consistent across all five different methods employed for the analysis, highlighting the direct relationship between pile depth and bearing capacity at this site. As illustrated in Figure 1, the Eurocode 7 method consistently yielded the highest estimates of pile load capacity, ranging from 285 to 572 tons for depths spanning 6 to 12 m. Conversely, the Eslami and Fellenius method consistently provided the lowest capacity estimates, ranging from 78 to 195 tons for the same depth range. The analytical methods: [1] Aoki De Alencar, [2] LCPC, and [3] Schmertmann demonstrated median results with axial load capacity ranging from 100 to 390 tons.

Figure 1 Pile load capacity versus depth at ASO.
Figure 1

Pile load capacity versus depth at ASO.

At the DCS, the results also showed that as pile depth increased, so did the bearing capacity. The Eurocode 7 method consistently provided the highest load capacity estimates, ranging from 410 to 593 tons for depths between 6 and 12 m, while the Eslami and Fellenius method consistently yielded the lowest estimates, ranging from 84 to 196 tons for the same depth range. Additionally, the Aoki and De Alencar method demonstrated the average results among these values, as shown in Figure 2.

Figure 2 Pile load capacity versus depth at DCS.
Figure 2

Pile load capacity versus depth at DCS.

Similar trends in pile-bearing capacity calculations were observed across the remaining roadway projects. In the case of the RBS site, the Eurocode 7 method also consistently provided the highest load capacity estimates, ranging from 127 to 293 tons for depths between 6 and 12 m. Conversely, the Eslami and Fellenius method consistently yielded the lowest estimates, ranging from 37 to 141 tons for the same depth range (Figure 3). Similarly, at the SR417 site, the Eurocode 7 method consistently provided the highest load capacity estimates, ranging from 330 to 477 tons for depths between 6 and 12 m. Again, the Eslami and Fellenius method consistently yielded the lowest estimates, ranging from 111 to 194 tons for the same depth range, as illustrated in Figure 4.

Figure 3 Pile load capacity versus depth at RBS.
Figure 3

Pile load capacity versus depth at RBS.

Figure 4 Pile load capacity versus depth at SR417.
Figure 4

Pile load capacity versus depth at SR417.

The analytical results were evaluated by determining the relative error in axial load capacity of the pile (i.e., relative error of pile-REP), which is calculated based on a limit load capacity L and E is the estimated load capacity of the pile as given below:

(21) REP = E − L L × 100 .

Figure 5 illustrates that the Eslami and Fellenius method gives the lowest estimate of the pile load capacity. For a 12 m pile length, the estimated load capacity was lower than the limit load capacity by about 8, 2, 10, and 3% for ASO, DCS, RBS, and SR417, respectively. However, the Eurocode method that includes all CPT measurements significantly overestimates the load-bearing capacity of the piles. For a 12 m pile length, the predicted load capacity was higher than the limit load capacity by about 35, 37, 32, and 26% for ASO, DCS, RBS, and SR417, respectively. Therefore, these methods (i.e., Eslami and Fellenius method and Eurocode method) should not be utilized without implementing the in situ pile load test for confirmation. The results also showed that the Aoki and De Alencar (1975) method consistently demonstrated the smallest differences among these values, indicating its potential for reliable and consistent pile-bearing capacity estimations since the method takes into account the soil characteristics along the pile’s length. This is an essential consideration in geotechnical pile design because the properties of the soil can vary significantly at different depths. By estimating the soil tip resistance over a large zone both below and above the pile’s tip and soil side friction, the method captures a more comprehensive behavior of the pile–soil interaction.

Figure 5 REP calculated between the estimated pile capacity and limit load capacity. (a) ASO, (b) Deer Crossing Street (DCS), (c) Ramsy Branch Street (RBS), and (d) State Road 417 (SR417).
Figure 5

REP calculated between the estimated pile capacity and limit load capacity. (a) ASO, (b) Deer Crossing Street (DCS), (c) Ramsy Branch Street (RBS), and (d) State Road 417 (SR417).

5 Conclusions

Based on the results of this research, several conclusions can be drawn as listed below:

  • The investigation unequivocally establishes that the axial load capacity of precast concrete piles exhibits a consistent and substantial increase with depth across a spectrum of roadway projects (ASO, DCS, RBS, and SR417). This reaffirms the importance of factoring in depth-related variations for a comprehensive understanding of pile behavior.

  • The Eurocode 7 method consistently produces the highest load capacity estimates. This method considers additional parameters such as base shape factor, critical depth, and effective angle of shearing resistance that might yield higher axial load capacity compared to other methods.

  • Among the analytical methods being utilized, Eslami and Fellenius’s method consistently provided the most conservative estimation, predicting the lower capacities for the driven concrete piles.

  • The Aoki and De Alencar method, characterized by minimal differences in load capacity estimates, not only establishes itself as a reliable approach but also provides nuanced insights into the intricacies of load capacity estimation.

  • The selection of the method of estimation is critical for accurate pile capacity determination, emphasizing the need to consider project-specific conditions.

  • The use of empirical correlations based on CPT measurements appears to be a suitable and simplified approach for predicting pile capacity, although the accuracy of capacity estimation should be validated through a wide range of full-scale field load tests.

Acknowledgements

The authors would like to thank the research engineers and other staff of the Florida Department of Transportation for their outstanding efforts in implementing the necessary CPT field tests.

  1. Conflict of interest: Authors state no conflict of interest.

  2. Data availability statement: The datasets generated during the current research are available from the corresponding author on reasonable request.

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Received: 2023-12-08
Revised: 2024-02-15
Accepted: 2024-03-04
Published Online: 2024-04-09

© 2024 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

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  43. Special Issue: AESMT-3 - Part II
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  45. Physical and mechanical response of porous metals composites with nano-natural additives
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  49. Static behavior of piled raft foundation in clay
  50. Ultra-low-power CMOS ring oscillator with minimum power consumption of 2.9 pW using low-voltage biasing technique
  51. Using ANN for well type identifying and increasing production from Sa’di formation of Halfaya oil field – Iraq
  52. Optimizing the performance of concrete tiles using nano-papyrus and carbon fibers
  53. Special Issue: AESMT-5 - Part II
  54. Comparative the effect of distribution transformer coil shape on electromagnetic forces and their distribution using the FEM
  55. The complex of Weyl module in free characteristic in the event of a partition (7,5,3)
  56. Restrained captive domination number
  57. Experimental study of improving hot mix asphalt reinforced with carbon fibers
  58. Asphalt binder modified with recycled tyre rubber
  59. Thermal performance of radiant floor cooling with phase change material for energy-efficient buildings
  60. Surveying the prediction of risks in cryptocurrency investments using recurrent neural networks
  61. A deep reinforcement learning framework to modify LQR for an active vibration control applied to 2D building models
  62. Evaluation of mechanically stabilized earth retaining walls for different soil–structure interaction methods: A review
  63. Assessment of heat transfer in a triangular duct with different configurations of ribs using computational fluid dynamics
  64. Sulfate removal from wastewater by using waste material as an adsorbent
  65. Experimental investigation on strengthening lap joints subjected to bending in glulam timber beams using CFRP sheets
  66. A study of the vibrations of a rotor bearing suspended by a hybrid spring system of shape memory alloys
  67. Stability analysis of Hub dam under rapid drawdown
  68. Developing ANFIS-FMEA model for assessment and prioritization of potential trouble factors in Iraqi building projects
  69. Numerical and experimental comparison study of piled raft foundation
  70. Effect of asphalt modified with waste engine oil on the durability properties of hot asphalt mixtures with reclaimed asphalt pavement
  71. Hydraulic model for flood inundation in Diyala River Basin using HEC-RAS, PMP, and neural network
  72. Numerical study on discharge capacity of piano key side weir with various ratios of the crest length to the width
  73. The optimal allocation of thyristor-controlled series compensators for enhancement HVAC transmission lines Iraqi super grid by using seeker optimization algorithm
  74. Numerical and experimental study of the impact on aerodynamic characteristics of the NACA0012 airfoil
  75. Effect of nano-TiO2 on physical and rheological properties of asphalt cement
  76. Performance evolution of novel palm leaf powder used for enhancing hot mix asphalt
  77. Performance analysis, evaluation, and improvement of selected unsignalized intersection using SIDRA software – Case study
  78. Flexural behavior of RC beams externally reinforced with CFRP composites using various strategies
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  80. Experimental investigation of RC beams strengthened with externally bonded BFRP composites
  81. Generalized RKM methods for solving fifth-order quasi-linear fractional partial differential equation
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  84. Implementation for the cases (5, 4) and (5, 4)/(2, 0)
  85. Center group actions and related concepts
  86. Experimental investigation of the effect of horizontal construction joints on the behavior of deep beams
  87. Deletion of a vertex in even sum domination
  88. Deep learning techniques in concrete powder mix designing
  89. Effect of loading type in concrete deep beam with strut reinforcement
  90. Studying the effect of using CFRP warping on strength of husk rice concrete columns
  91. Parametric analysis of the influence of climatic factors on the formation of traditional buildings in the city of Al Najaf
  92. Suitability location for landfill using a fuzzy-GIS model: A case study in Hillah, Iraq
  93. Hybrid approach for cost estimation of sustainable building projects using artificial neural networks
  94. Assessment of indirect tensile stress and tensile–strength ratio and creep compliance in HMA mixes with micro-silica and PMB
  95. Density functional theory to study stopping power of proton in water, lung, bladder, and intestine
  96. A review of single flow, flow boiling, and coating microchannel studies
  97. Effect of GFRP bar length on the flexural behavior of hybrid concrete beams strengthened with NSM bars
  98. Exploring the impact of parameters on flow boiling heat transfer in microchannels and coated microtubes: A comprehensive review
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  100. Special Issue: AESMT-6
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  102. Forecasting empirical formula for suspended sediment load prediction at upstream of Al-Kufa barrage, Kufa City, Iraq
  103. Optimization and characterization of sustainable geopolymer mortars based on palygorskite clay, water glass, and sodium hydroxide
  104. Sediment transport modelling upstream of Al Kufa Barrage
  105. Study of energy loss, range, and stopping time for proton in germanium and copper materials
  106. Effect of internal and external recycle ratios on the nutrient removal efficiency of anaerobic/anoxic/oxic (VIP) wastewater treatment plant
  107. Enhancing structural behaviour of polypropylene fibre concrete columns longitudinally reinforced with fibreglass bars
  108. Sustainable road paving: Enhancing concrete paver blocks with zeolite-enhanced cement
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  113. An image encryption method based on modified elliptic curve Diffie-Hellman key exchange protocol and Hill Cipher
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  115. Effect of surface roughness on the interface behavior of clayey soils
  116. Investigated of the optical properties for SiO2 by using Lorentz model
  117. Measurements of induced vibrations due to steel pipe pile driving in Al-Fao soil: Effect of partial end closure
  118. Experimental and numerical studies of ballistic resistance of hybrid sandwich composite body armor
  119. Evaluation of clay layer presence on shallow foundation settlement in dry sand under an earthquake
  120. Optimal design of mechanical performances of asphalt mixtures comprising nano-clay additives
  121. Advancing seismic performance: Isolators, TMDs, and multi-level strategies in reinforced concrete buildings
  122. Predicted evaporation in Basrah using artificial neural networks
  123. Energy management system for a small town to enhance quality of life
  124. Numerical study on entropy minimization in pipes with helical airfoil and CuO nanoparticle integration
  125. Equations and methodologies of inlet drainage system discharge coefficients: A review
  126. Thermal buckling analysis for hybrid and composite laminated plate by using new displacement function
  127. Investigation into the mechanical and thermal properties of lightweight mortar using commercial beads or recycled expanded polystyrene
  128. Experimental and theoretical analysis of single-jet column and concrete column using double-jet grouting technique applied at Al-Rashdia site
  129. The impact of incorporating waste materials on the mechanical and physical characteristics of tile adhesive materials
  130. Seismic resilience: Innovations in structural engineering for earthquake-prone areas
  131. Automatic human identification using fingerprint images based on Gabor filter and SIFT features fusion
  132. Performance of GRKM-method for solving classes of ordinary and partial differential equations of sixth-orders
  133. Visible light-boosted photodegradation activity of Ag–AgVO3/Zn0.5Mn0.5Fe2O4 supported heterojunctions for effective degradation of organic contaminates
  134. Production of sustainable concrete with treated cement kiln dust and iron slag waste aggregate
  135. Key effects on the structural behavior of fiber-reinforced lightweight concrete-ribbed slabs: A review
  136. A comparative analysis of the energy dissipation efficiency of various piano key weir types
  137. Special Issue: Transport 2022 - Part II
  138. Variability in road surface temperature in urban road network – A case study making use of mobile measurements
  139. Special Issue: BCEE5-2023
  140. Evaluation of reclaimed asphalt mixtures rejuvenated with waste engine oil to resist rutting deformation
  141. Assessment of potential resistance to moisture damage and fatigue cracks of asphalt mixture modified with ground granulated blast furnace slag
  142. Investigating seismic response in adjacent structures: A study on the impact of buildings’ orientation and distance considering soil–structure interaction
  143. Improvement of porosity of mortar using polyethylene glycol pre-polymer-impregnated mortar
  144. Three-dimensional analysis of steel beam-column bolted connections
  145. Assessment of agricultural drought in Iraq employing Landsat and MODIS imagery
  146. Performance evaluation of grouted porous asphalt concrete
  147. Optimization of local modified metakaolin-based geopolymer concrete by Taguchi method
  148. Effect of waste tire products on some characteristics of roller-compacted concrete
  149. Studying the lateral displacement of retaining wall supporting sandy soil under dynamic loads
  150. Seismic performance evaluation of concrete buttress dram (Dynamic linear analysis)
  151. Behavior of soil reinforced with micropiles
  152. Possibility of production high strength lightweight concrete containing organic waste aggregate and recycled steel fibers
  153. An investigation of self-sensing and mechanical properties of smart engineered cementitious composites reinforced with functional materials
  154. Forecasting changes in precipitation and temperatures of a regional watershed in Northern Iraq using LARS-WG model
  155. Experimental investigation of dynamic soil properties for modeling energy-absorbing layers
  156. Numerical investigation of the effect of longitudinal steel reinforcement ratio on the ductility of concrete beams
  157. An experimental study on the tensile properties of reinforced asphalt pavement
  158. Self-sensing behavior of hot asphalt mixture with steel fiber-based additive
  159. Behavior of ultra-high-performance concrete deep beams reinforced by basalt fibers
  160. Optimizing asphalt binder performance with various PET types
  161. Investigation of the hydraulic characteristics and homogeneity of the microstructure of the air voids in the sustainable rigid pavement
  162. Enhanced biogas production from municipal solid waste via digestion with cow manure: A case study
  163. Special Issue: AESMT-7 - Part I
  164. Preparation and investigation of cobalt nanoparticles by laser ablation: Structure, linear, and nonlinear optical properties
  165. Seismic analysis of RC building with plan irregularity in Baghdad/Iraq to obtain the optimal behavior
  166. The effect of urban environment on large-scale path loss model’s main parameters for mmWave 5G mobile network in Iraq
  167. Formatting a questionnaire for the quality control of river bank roads
  168. Vibration suppression of smart composite beam using model predictive controller
  169. Machine learning-based compressive strength estimation in nanomaterial-modified lightweight concrete
  170. In-depth analysis of critical factors affecting Iraqi construction projects performance
  171. Behavior of container berth structure under the influence of environmental and operational loads
  172. Energy absorption and impact response of ballistic resistance laminate
  173. Effect of water-absorbent polymer balls in internal curing on punching shear behavior of bubble slabs
  174. Effect of surface roughness on interface shear strength parameters of sandy soils
  175. Evaluating the interaction for embedded H-steel section in normal concrete under monotonic and repeated loads
  176. Estimation of the settlement of pile head using ANN and multivariate linear regression based on the results of load transfer method
  177. Enhancing communication: Deep learning for Arabic sign language translation
  178. A review of recent studies of both heat pipe and evaporative cooling in passive heat recovery
  179. Effect of nano-silica on the mechanical properties of LWC
  180. An experimental study of some mechanical properties and absorption for polymer-modified cement mortar modified with superplasticizer
  181. Digital beamforming enhancement with LSTM-based deep learning for millimeter wave transmission
  182. Developing an efficient planning process for heritage buildings maintenance in Iraq
  183. Design and optimization of two-stage controller for three-phase multi-converter/multi-machine electric vehicle
  184. Evaluation of microstructure and mechanical properties of Al1050/Al2O3/Gr composite processed by forming operation ECAP
  185. Calculations of mass stopping power and range of protons in organic compounds (CH3OH, CH2O, and CO2) at energy range of 0.01–1,000 MeV
  186. Investigation of in vitro behavior of composite coating hydroxyapatite-nano silver on 316L stainless steel substrate by electrophoretic technic for biomedical tools
  187. A review: Enhancing tribological properties of journal bearings composite materials
  188. Improvements in the randomness and security of digital currency using the photon sponge hash function through Maiorana–McFarland S-box replacement
  189. Design a new scheme for image security using a deep learning technique of hierarchical parameters
  190. Special Issue: ICES 2023
  191. Comparative geotechnical analysis for ultimate bearing capacity of precast concrete piles using cone resistance measurements
  192. Visualizing sustainable rainwater harvesting: A case study of Karbala Province
  193. Geogrid reinforcement for improving bearing capacity and stability of square foundations
  194. Evaluation of the effluent concentrations of Karbala wastewater treatment plant using reliability analysis
  195. Adsorbent made with inexpensive, local resources
  196. Effect of drain pipes on seepage and slope stability through a zoned earth dam
  197. Sediment accumulation in an 8 inch sewer pipe for a sample of various particles obtained from the streets of Karbala city, Iraq
  198. Special Issue: IETAS 2024 - Part I
  199. Analyzing the impact of transfer learning on explanation accuracy in deep learning-based ECG recognition systems
  200. Effect of scale factor on the dynamic response of frame foundations
  201. Improving multi-object detection and tracking with deep learning, DeepSORT, and frame cancellation techniques
  202. The impact of using prestressed CFRP bars on the development of flexural strength
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  204. A data augmentation approach to enhance breast cancer detection using generative adversarial and artificial neural networks
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  206. Special Issue: 51st KKBN - Part I
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https://doi.org/10.1515/eng-2024-0007
Keywords for this article
axial load capacity; precast concrete piles; CPT measurement
Creative Commons
BY 4.0

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  2. Methodology of automated quality management
  3. Influence of vibratory conveyor design parameters on the trough motion and the self-synchronization of inertial vibrators
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  20. Assessing the need for the adoption of digitalization in Indian small and medium enterprises
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  39. Communication
  40. Techniques to mitigate the admission of radon inside buildings
  41. Erratum
  42. Erratum to “Effect of short heat treatment on mechanical properties and shape memory properties of Cu–Al–Ni shape memory alloy”
  43. Special Issue: AESMT-3 - Part II
  44. Integrated fuzzy logic and multicriteria decision model methods for selecting suitable sites for wastewater treatment plant: A case study in the center of Basrah, Iraq
  45. Physical and mechanical response of porous metals composites with nano-natural additives
  46. Special Issue: AESMT-4 - Part II
  47. New recycling method of lubricant oil and the effect on the viscosity and viscous shear as an environmentally friendly
  48. Identify the effect of Fe2O3 nanoparticles on mechanical and microstructural characteristics of aluminum matrix composite produced by powder metallurgy technique
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  50. Ultra-low-power CMOS ring oscillator with minimum power consumption of 2.9 pW using low-voltage biasing technique
  51. Using ANN for well type identifying and increasing production from Sa’di formation of Halfaya oil field – Iraq
  52. Optimizing the performance of concrete tiles using nano-papyrus and carbon fibers
  53. Special Issue: AESMT-5 - Part II
  54. Comparative the effect of distribution transformer coil shape on electromagnetic forces and their distribution using the FEM
  55. The complex of Weyl module in free characteristic in the event of a partition (7,5,3)
  56. Restrained captive domination number
  57. Experimental study of improving hot mix asphalt reinforced with carbon fibers
  58. Asphalt binder modified with recycled tyre rubber
  59. Thermal performance of radiant floor cooling with phase change material for energy-efficient buildings
  60. Surveying the prediction of risks in cryptocurrency investments using recurrent neural networks
  61. A deep reinforcement learning framework to modify LQR for an active vibration control applied to 2D building models
  62. Evaluation of mechanically stabilized earth retaining walls for different soil–structure interaction methods: A review
  63. Assessment of heat transfer in a triangular duct with different configurations of ribs using computational fluid dynamics
  64. Sulfate removal from wastewater by using waste material as an adsorbent
  65. Experimental investigation on strengthening lap joints subjected to bending in glulam timber beams using CFRP sheets
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  72. Numerical study on discharge capacity of piano key side weir with various ratios of the crest length to the width
  73. The optimal allocation of thyristor-controlled series compensators for enhancement HVAC transmission lines Iraqi super grid by using seeker optimization algorithm
  74. Numerical and experimental study of the impact on aerodynamic characteristics of the NACA0012 airfoil
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  76. Performance evolution of novel palm leaf powder used for enhancing hot mix asphalt
  77. Performance analysis, evaluation, and improvement of selected unsignalized intersection using SIDRA software – Case study
  78. Flexural behavior of RC beams externally reinforced with CFRP composites using various strategies
  79. Influence of fiber types on the properties of the artificial cold-bonded lightweight aggregates
  80. Experimental investigation of RC beams strengthened with externally bonded BFRP composites
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  90. Studying the effect of using CFRP warping on strength of husk rice concrete columns
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  104. Sediment transport modelling upstream of Al Kufa Barrage
  105. Study of energy loss, range, and stopping time for proton in germanium and copper materials
  106. Effect of internal and external recycle ratios on the nutrient removal efficiency of anaerobic/anoxic/oxic (VIP) wastewater treatment plant
  107. Enhancing structural behaviour of polypropylene fibre concrete columns longitudinally reinforced with fibreglass bars
  108. Sustainable road paving: Enhancing concrete paver blocks with zeolite-enhanced cement
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  110. Design and simulation of photonic crystal fiber for highly sensitive chemical sensing applications
  111. Optimization and design of a new column sequencing for crude oil distillation at Basrah refinery
  112. Inductive 3D numerical modelling of the tibia bone using MRI to examine von Mises stress and overall deformation
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  118. Experimental and numerical studies of ballistic resistance of hybrid sandwich composite body armor
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  120. Optimal design of mechanical performances of asphalt mixtures comprising nano-clay additives
  121. Advancing seismic performance: Isolators, TMDs, and multi-level strategies in reinforced concrete buildings
  122. Predicted evaporation in Basrah using artificial neural networks
  123. Energy management system for a small town to enhance quality of life
  124. Numerical study on entropy minimization in pipes with helical airfoil and CuO nanoparticle integration
  125. Equations and methodologies of inlet drainage system discharge coefficients: A review
  126. Thermal buckling analysis for hybrid and composite laminated plate by using new displacement function
  127. Investigation into the mechanical and thermal properties of lightweight mortar using commercial beads or recycled expanded polystyrene
  128. Experimental and theoretical analysis of single-jet column and concrete column using double-jet grouting technique applied at Al-Rashdia site
  129. The impact of incorporating waste materials on the mechanical and physical characteristics of tile adhesive materials
  130. Seismic resilience: Innovations in structural engineering for earthquake-prone areas
  131. Automatic human identification using fingerprint images based on Gabor filter and SIFT features fusion
  132. Performance of GRKM-method for solving classes of ordinary and partial differential equations of sixth-orders
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  134. Production of sustainable concrete with treated cement kiln dust and iron slag waste aggregate
  135. Key effects on the structural behavior of fiber-reinforced lightweight concrete-ribbed slabs: A review
  136. A comparative analysis of the energy dissipation efficiency of various piano key weir types
  137. Special Issue: Transport 2022 - Part II
  138. Variability in road surface temperature in urban road network – A case study making use of mobile measurements
  139. Special Issue: BCEE5-2023
  140. Evaluation of reclaimed asphalt mixtures rejuvenated with waste engine oil to resist rutting deformation
  141. Assessment of potential resistance to moisture damage and fatigue cracks of asphalt mixture modified with ground granulated blast furnace slag
  142. Investigating seismic response in adjacent structures: A study on the impact of buildings’ orientation and distance considering soil–structure interaction
  143. Improvement of porosity of mortar using polyethylene glycol pre-polymer-impregnated mortar
  144. Three-dimensional analysis of steel beam-column bolted connections
  145. Assessment of agricultural drought in Iraq employing Landsat and MODIS imagery
  146. Performance evaluation of grouted porous asphalt concrete
  147. Optimization of local modified metakaolin-based geopolymer concrete by Taguchi method
  148. Effect of waste tire products on some characteristics of roller-compacted concrete
  149. Studying the lateral displacement of retaining wall supporting sandy soil under dynamic loads
  150. Seismic performance evaluation of concrete buttress dram (Dynamic linear analysis)
  151. Behavior of soil reinforced with micropiles
  152. Possibility of production high strength lightweight concrete containing organic waste aggregate and recycled steel fibers
  153. An investigation of self-sensing and mechanical properties of smart engineered cementitious composites reinforced with functional materials
  154. Forecasting changes in precipitation and temperatures of a regional watershed in Northern Iraq using LARS-WG model
  155. Experimental investigation of dynamic soil properties for modeling energy-absorbing layers
  156. Numerical investigation of the effect of longitudinal steel reinforcement ratio on the ductility of concrete beams
  157. An experimental study on the tensile properties of reinforced asphalt pavement
  158. Self-sensing behavior of hot asphalt mixture with steel fiber-based additive
  159. Behavior of ultra-high-performance concrete deep beams reinforced by basalt fibers
  160. Optimizing asphalt binder performance with various PET types
  161. Investigation of the hydraulic characteristics and homogeneity of the microstructure of the air voids in the sustainable rigid pavement
  162. Enhanced biogas production from municipal solid waste via digestion with cow manure: A case study
  163. Special Issue: AESMT-7 - Part I
  164. Preparation and investigation of cobalt nanoparticles by laser ablation: Structure, linear, and nonlinear optical properties
  165. Seismic analysis of RC building with plan irregularity in Baghdad/Iraq to obtain the optimal behavior
  166. The effect of urban environment on large-scale path loss model’s main parameters for mmWave 5G mobile network in Iraq
  167. Formatting a questionnaire for the quality control of river bank roads
  168. Vibration suppression of smart composite beam using model predictive controller
  169. Machine learning-based compressive strength estimation in nanomaterial-modified lightweight concrete
  170. In-depth analysis of critical factors affecting Iraqi construction projects performance
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  172. Energy absorption and impact response of ballistic resistance laminate
  173. Effect of water-absorbent polymer balls in internal curing on punching shear behavior of bubble slabs
  174. Effect of surface roughness on interface shear strength parameters of sandy soils
  175. Evaluating the interaction for embedded H-steel section in normal concrete under monotonic and repeated loads
  176. Estimation of the settlement of pile head using ANN and multivariate linear regression based on the results of load transfer method
  177. Enhancing communication: Deep learning for Arabic sign language translation
  178. A review of recent studies of both heat pipe and evaporative cooling in passive heat recovery
  179. Effect of nano-silica on the mechanical properties of LWC
  180. An experimental study of some mechanical properties and absorption for polymer-modified cement mortar modified with superplasticizer
  181. Digital beamforming enhancement with LSTM-based deep learning for millimeter wave transmission
  182. Developing an efficient planning process for heritage buildings maintenance in Iraq
  183. Design and optimization of two-stage controller for three-phase multi-converter/multi-machine electric vehicle
  184. Evaluation of microstructure and mechanical properties of Al1050/Al2O3/Gr composite processed by forming operation ECAP
  185. Calculations of mass stopping power and range of protons in organic compounds (CH3OH, CH2O, and CO2) at energy range of 0.01–1,000 MeV
  186. Investigation of in vitro behavior of composite coating hydroxyapatite-nano silver on 316L stainless steel substrate by electrophoretic technic for biomedical tools
  187. A review: Enhancing tribological properties of journal bearings composite materials
  188. Improvements in the randomness and security of digital currency using the photon sponge hash function through Maiorana–McFarland S-box replacement
  189. Design a new scheme for image security using a deep learning technique of hierarchical parameters
  190. Special Issue: ICES 2023
  191. Comparative geotechnical analysis for ultimate bearing capacity of precast concrete piles using cone resistance measurements
  192. Visualizing sustainable rainwater harvesting: A case study of Karbala Province
  193. Geogrid reinforcement for improving bearing capacity and stability of square foundations
  194. Evaluation of the effluent concentrations of Karbala wastewater treatment plant using reliability analysis
  195. Adsorbent made with inexpensive, local resources
  196. Effect of drain pipes on seepage and slope stability through a zoned earth dam
  197. Sediment accumulation in an 8 inch sewer pipe for a sample of various particles obtained from the streets of Karbala city, Iraq
  198. Special Issue: IETAS 2024 - Part I
  199. Analyzing the impact of transfer learning on explanation accuracy in deep learning-based ECG recognition systems
  200. Effect of scale factor on the dynamic response of frame foundations
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