Home Evaluation of clay layer presence on shallow foundation settlement in dry sand under an earthquake
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Evaluation of clay layer presence on shallow foundation settlement in dry sand under an earthquake

  • Ali Ismaiel Ali EMAIL logo
Published/Copyright: March 18, 2024
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Abstract

Seismically, settlement of buildings with shallow foundations lying above dry sand soils has caused severe destruction in recent earthquakes. This study investigated the effect of seismic loads with shallow foundations located above sandy soil containing an intermediate soft clay layer. The impact of a clay layer’s existence with different thickness and closeness to the base of foundation when subjected to El Centro earthquake with 6.9 magnitude. This investigation has been carried out with the help of a three-dimensional PLAXIS 3D, which has been used to solve many geotechnical issues. A database was created for the various dynamic and static parameters of soils in seismically active areas of Iran and Iraq and USA. In this research, important factors are recognized, including relative density. Clay layer thickness and proximity to the foundation, the soil relative density the results of this research indicated that shallow foundation settlement increased on the dry sand and decreased with the presence of clay layer thickness and wave propagation in cohesion soil is less than cohesion-less soil. In addition, it was reached that as close as the clay layer to the foundation the settlement increased.

1 Introduction

The geotechnical engineering understanding of the seismic shallow foundation behavior has industrialized over the historical 60 years with the appearance and modification of solutions to some separate features of the overall problem, encouraged and motivated by field interpretations.

Shallow foundations are the most public types of foundations used to support mid-rise constructions in a height seismic risk. The inadequate design of structures during recent earthquakes has interested many researchers to study the existing methods and improve new approaches for seismic-resistant design. Foundations of structures constructed in seismic regions and the demands to withstand the load and deformation through an earthquake will perhaps be the most severe in their design life. Owing to the seismic loading, shallow foundations may experience a high increase in settlement. The influence of sandy soils in various conditions (loose, medium, dense) placed on a soft clay layer with different thicknesses and exposed to seismic waves and the closeness of the soft clay layer to the base of the foundation was also studied. Moreover, the influence of earthquake on a shallow foundation was investigated. Many types of research have exposed that the dynamic interaction between the soil, foundation, and structure can influence the seismic response of the building through an earthquake. Using the finite element method (FEM), positioned on multilayer soil on a resistant building’s seismic response is investigated. Effective post- and preprocessing abilities make it easier to analyze and model.

The information. If an analysis is repeated, over a period, it is relatively straightforward to make modifications.

These soil parameters are critical for the hardening soil model to be employed in this work as data inputs. It also requires the use of data input from a 1940 earthquake (the El Centro earthquake) to analyze the behavior of shallow foundations under seismic waves using the finite element program PLAXIS 3D. As a result, it should be highlighted that soil is a common element in seismic wave transmission to the foundation.

This study investigation concentrates on the key problems of what effect the presence of a soft clay layer beneath the foundation has on the foundation’s output during an earthquake to find out the ability of the soft clay layer. Does the soft clay layer decrease or increase the settlement?

In addition, there is a difference between a foundation constructed on sandy soil and one built on sandy soil with a soft clay layer within it. The model’s results will be compared and discussed.

2 Research objectives

  1. One of the key objectives of this study is to assess the impact of a soft clay layer, with varying thickness and closeness distances, on the performance of a shallow foundation subjected to different seismic loads. The presence of such a layer, located beneath loose sand, can significantly affect the behavior of the foundation during an earthquake, making it crucial to evaluate its influence.

  2. The other objective is to evaluate the activity of shallow foundations under seismic excitation using real seismic data from Iraq, the USA, and Iran. To conduct the analyses, PLAXIS 3D finite element tools were used.

3 Literature review and research

The behavior of shallow foundations in earthquakes has advanced progressively over the last 60 years, such as the appearance and improvement solutions for several different surfaces of the overall challenges, prompted and stimulated by field observations. The growth of insights and strategies for the various facets of seismic foundation activity has been more rapid in recent years. Total solutions, predictably, necessitate numerical solution methods that make them less diaphanous than their predecessors. The analysis starts by looking at relevant aspects of soil and rock actions, some of which have not yet been fully studied. An analysis of the literature on the action of shallow foundations under seismic loading is presented in this chapter. This study highlights earthquake fundamentals, soil–structure interaction, and shallow foundations under earthquake activity.

A shallow foundation is usually located at a shallow depth and transmits loads to the near-surface strata. A foundation is shallow: according to Terzaghi and Peck (1967) if the structural bases with the least dimension (usually the width B) is equal to or greater than the foundation depth (Df). This is a criterion. It is appropriate for regular shallow foundations, but not for narrow or very small foundations. Df has been estimated to be as large as 3–4B by some scholars. Df is used in this situation. The masonry footings were dimension-stone footings made up of stones that had been carved and dressed to a precise size and shape [1]. An earthquake creates a series of waves, which move across the earth and inflict damage depending on their intensity. Instruments capable of tracking thousands of miles away from the epicenter can be used. The type of earthquake that occurred is revealed by the seismic wave. Individual wave paths separate in all directions as they move away from the source.

Waves of seismic activity: Huge strain energy emitted during an earthquake passes through the Earth’s layers as seismic waves in all directions, reflecting and refracting at each interface, as shown in Figure 1 [2].

Figure 1 
               Arrival of seismic waves at a site.
Figure 1

Arrival of seismic waves at a site.

4 Finite element program

Soil behavior is simulated using advanced foundational models. PLAXIS 3D is used to characterize the soil model and to simulate the performance of shallow foundations subjected to earthquake excitation. Since the relationship between soil, base, and structure influences the dynamic properties and seismic response of the building, the construction engineer must carefully consider these parameters to ensure a secure and cost-effective seismic design.

Since 1960, FEM has been used to solve geotechnical engineering problems. It was the beginning to insert this method and link it into geotechnical engineering. PLAXIS 3D is a full-featured 3D geotechnical element program that was created exactly for deformation study, stability, and flux in geotechnical engineering constructions.

It has advanced features in addressing modeling challenges in the most complex geotechnical projects that are difficult to represent on PLAXIS2D. It is now easy to model the finite elements (3D) [3].

FEM is a powerful tool for analyzing complex engineering problems. Developed over a decade, FEM divides large problems into smaller parts, minimizing the solution process. FEM is an effective and important method, widely used to solve complex engineering problems [4].

4.1 Geometry of the 3D model

The model has three dimensions: a width of 1.5 m, a length of 1.5 m, and a height of 0.5 m (X = 200 m, Y = 100 m, and Z = 40 m). The point load on the shallow base and prescribed displacements under the soil mode are shown in Figure 2a and b.

Figure 2 
                  (a) Geometric model and soil layers and (b) shallow foundation and displacement.
Figure 2

(a) Geometric model and soil layers and (b) shallow foundation and displacement.

5 Sensitivity for the model dimension

The depth of the numerical model has been considered to be equal to 40 m since the position of the rock layer has been assumed to be at a depth of 40 m from the natural ground surface; a similar modeling approach has been used in other numerical analyses in the literature as mentioned by Van Nguyen et al. [5]. The width of the model has been considered equal to 200 m. The width has been selected based on parametric analyses conducted to investigate the influence of the FEM width on the settlement results. The parametric analyses have been carried out by simulating different model widths. It was found that the results of the analysis were not influenced by the FEM extension. The results of the model width study are shown in Figure 3.

Figure 3 
               Sensitivity of soil dimensions.
Figure 3

Sensitivity of soil dimensions.

This clearly shows that the model width has an insignificant influence on the obtained results after an extension of x ≥ 200 m.

6 Modeling of soil

Soil representation models (soil models) are a quantitative representation of soil behavior since model parameters are used to determine soil properties. The more experience dealing with PLAXIS, the more accurate the results will be. The wider the understanding of soil models and the limits of the use of each model and the method of determining model parameters, the greater the judgment and the ability to understand the nature of the results in PLAXIS OUTPUT.

Table 1 gives the hardening soil parameters [6].

Table 1

Properties of hardening soil

Parameter Loose sand Medium sand Dense sand Unit
E 50 ref 20,000 30,000 40,000 kN/m2
E ur ref 60,000 90,000 120,000 kN/m2
E oed ref 20,000 30,000 40,000 kN/m2
Cohesion, c 0.0 0.0 0.0 kN/m2
Friction angle, ϕ 30 35 40 °
Dilatancy angle, ψ (ψ = ϕ – 30) 0 5 10 °
Poisson’s ratio, ν ur 0.2 0.2 0.2

Parameters of the Soft Soil model

c: cohesion

ϕ: friction angle

ψ: dilatancy angle

λ: modified compression index

κ: modified swelling index

ν ur: Poisson’s ratio for unloading/reloading.

K0nc: horizontal/vertical stress ratio in normally consolidated 1D compression (determines the shape parameter M)

In addition, you need to define the initial size of the yield surface by appropriate POP/OCR value! [7].

7 Verification model

The verification of PLAXSIS 3D of a shallow foundation resting on a dense sand layer and influenced by the El Centro earthquake, which has 6.9 intensity, was performed by comparing the results with the experimental work of “Al-Neami et al. (2021), which used a multi-degree freedom shaking table and a fixed container, which was manufactured in order to study the influence of earthquake intensity and soil relative density on the shallow foundation’s settlement. A series of shaking experiments were conducted using a 0.7 × 0.7 × 0.8 m container to study the shallow foundation behavior. The shallow foundation was resting at the center of dry sandy soil having two relative densities (55 and 80%) and influenced by two local magnitudes of earthquakes Jalisco and Guerrero having intensities of 6.4 and 7.2, respectively [8].

Figure 4 demonstrates the comparison between experimental work influenced by the Guerrero earthquake having 7.2 intensity results of Al-Neami et al. (2021) and finite analysis of a dense sand case influenced by the El Centro earthquake with 6.9 intensity. Acceleration histories of the used earthquakes are shown in Figure 5.

Figure 4 
               Shaking table.
Figure 4

Shaking table.

Figure 5 
               History of earthquake acceleration.
Figure 5

History of earthquake acceleration.

The results show that the settlement of a shallow foundation lying on a dense sand layer and influenced by the El Centro earthquake having 6.9 intensity is 34 mm, while the experimental work of Al-Neami is 24 mm for Guerrero, which has 7.2 intensity, and 20 mm for Jalisco, which has 6.4 intensity, influenced the shallow foundation. The results indicate that the settlement using a finite element analysis increased by 42% and this difference may be due to the difference between the dimension of the experimental box and the PLAXSIS 3D soil dimension, which shows more reality to the earthquake and the difference of earthquake intensity [8].

8 Results

8.1 Effect of sandy soil condition without soft clay layer presence on foundation settlement under effect earthquake

There are great benefits in using advanced models in order to recognize the reality of the initial soil structure and its subsequent damage caused by the applied dynamic loads. Soil deformations produced from the passageway of a seismic wave through the soil might threaten the stability of any geotechnical structure; therefore, PLAXIS 3D program was used to create different models, which include a shallow foundation with dimensions (1.5 m × 1.5 m × 0.5 m), which underlies the three layers. Two different conditions exist in two sandy soil layers (loose sand, medium, dense) and an intermediate soft clay layer with various thicknesses (3, 4, and 5 m), it was discovered that this alteration reduced settlement. Figure 6 shows the use of loose sandy soil, which produces a maximum amount for settlement of about 61.6309 mm at a 5.32 s time.

Figure 6 
                  Amount of settlement in loose sand.
Figure 6

Amount of settlement in loose sand.

Moreover, Figure 7 shows the use of medium sandy soil, which produces a maximum settlement of about 42.78609 mm at a time of 6.16 s.

Figure 7 
                  Amount of settlement in medium sand.
Figure 7

Amount of settlement in medium sand.

Moreover, Figure 8 shows the use of dense sandy soil, which produces a maximum settlement of about 34.01353 mm at a time of 6.16 s.

Figure 8 
                  Amount of settlement in dense sand.
Figure 8

Amount of settlement in dense sand.

As a result, Figure 9 shows that dense sand reduces the settlement in the soil by a higher amount than medium sand and loose sand. Figure 10 illustrates a settlement competition for without loose sand case.

Figure 9 
                  Amount of settlement in loose, medium, and dense sand.
Figure 9

Amount of settlement in loose, medium, and dense sand.

Figure 10 
                  Maximum settlement competition without clay.
Figure 10

Maximum settlement competition without clay.

8.2 Effect of soft clay from closeness to the foundations base

In order to understand the seismic wave response, many parameters become important to discuss. As a result, to obtain the maximum benefit from many methods of seismic analysis, soil closeness to the foundation was one of the parameters that should be investigated.

8.2.1 For 2 m soft clay far from the base of the foundation case

Figure 11 illustrates the effect of a soft clay layer closeness. The 2m-thick layer of soft clay lying away from the base of the foundation and beneath a sandy soil having various conditions (loose, medium, and dense). It seems that the distance between the soft clay layer and the foundation is crucial. It is obvious that the presence of a 2 m soft clay layer affects the settlement produced due to the earthquake. The results show that the settlement under the shallow foundation reduced about 10.23, 17.2, and 19.1% for loose, medium, and dense sand cases, respectively. Because foundations are mostly placed at a depth Df below the ground surface, the term “Df” refers to the foundation’s depth in the soil. The overburdened soil’s shear strength is considered the same as the soil beneath the footing’s foundation. The depth impact may be lessened or ignored entirely if the overloaded soil is weaker than the foundation soil (John Wiley & Sons 2006 Analysis and Design of Shallow and Deep Foundations). Figure 12 illustrates the maximum settlement competition for 2 m soft clay layer case.

Figure 11 
                     Soft clays (2 m) away from the base with (loose, medium, and dense sand).
Figure 11

Soft clays (2 m) away from the base with (loose, medium, and dense sand).

Figure 12 
                     Maximum settlement comparison for 2 m soft clay.
Figure 12

Maximum settlement comparison for 2 m soft clay.

8.2.2 For 4 m soft clay far from the base of the foundation

Figure 13 illustrates the effect of a 4 m soft clay layer away from the base of the foundation having loose, medium, and dense sand. It seems the distance between the soft clay layer and the foundation affects the settlement. It is clear from the results that as farther the soft clay layer is from the foundation, the lower the settlement occurs, and the closer the soft clay layer is to the foundation, the higher the settlement occurs. The settlement reduced about 26.9, 38.1, and 33.6% with loose, medium, and dense, respectively. As a result, with increasing density, the settlement reduces greater than loose soil condition. Figure 14 illustrates the settlement competition for 4 m soft clay layer case.

Figure 13 
                     Soft clays (4 m) away from the base with loose, medium, and dense sand.
Figure 13

Soft clays (4 m) away from the base with loose, medium, and dense sand.

Figure 14 
                     Maximum settlement comparison for 4 m soft clay.
Figure 14

Maximum settlement comparison for 4 m soft clay.

8.2.3 For 6 m soft clay far from the base of the foundation

Figure 15 illustrates the effect of a 6 m soft clay layer away from the base of the foundation with loose, medium, and dense sand. It seems that the distance between the soft clay layer and the foundation affects the settlement. It is so clear that with increasing the distance from the base of the foundation, the settlement gets lesser.

Figure 15 
                     Soft clays (6 m) away from the base with loose, medium, and dense sand.
Figure 15

Soft clays (6 m) away from the base with loose, medium, and dense sand.

The settlement reduced about 43.1, 46.7, and 39.6% for loose, medium, and dense sand, respectively. The less amount of settlement occurred with dense sand, so it is clear that the denser the sand is lesser, the settlement occurs. This result confirms that the uncertainty in site response results due to soft clay soil is much higher when compared to sandy soils. Figure 16 illustrates the maximum settlement competition for 6 m soft clay layer case.

Figure 16 
                     Maximum settlement comparison for 6 m soft clay.
Figure 16

Maximum settlement comparison for 6 m soft clay.

8.3 Effect of thickness of soft clay layer

The extent of waves and degree of harm during an earthquake is powerfully influenced by the response of soil shaking. However, the most significant and usually problematic in geotechnical engineering earthquake is the estimation of ground response due to such motion. A parametric study was conducted to evaluate the effects of soft clay presence and thickness (T = 3, 4, 5 m) included in sandy soil models on shallow foundation performance.

8.3.1 For 3 m soft clay layer thickness

Figure 17 illustrates the effect of a 3 m soft clay layer thickness on the settlement of the foundation with the (loose, medium, and dense) sand cases. It is obvious that with the dense sand case, the settlement of the shallow foundation reduces much more than that of loose or medium sand cases. The results indicate that the settlement reduced by about 10.23, 17.2, and 19.1% for loose, medium, and dense sand cases due to the presence of a 3 m soft clay layer. It is clear from the results that dense sand cases showed less settlement. Figure 18 illustrates the maximum settlement comparison for 3 m soft clay layer case.

Figure 17 
                     Soft clay thickness (3 m) with loose, medium, and dense sand.
Figure 17

Soft clay thickness (3 m) with loose, medium, and dense sand.

Figure 18 
                     Maximum settlement comparison for (3 m) soft clay.
Figure 18

Maximum settlement comparison for (3 m) soft clay.

8.3.2 For 4 m soft clay layer thickness

Figure 19 illustrates the effect of a 4 m soft clay layer thickness on the settlement of the foundation having (loose, medium, and dense) sand cases. It is obvious that with dense sand cases, the settlement of the shallow foundation reduces much more than with loose or medium sand cases. The results indicate that the settlement reduced by about 14.65, 23.1, and 24.15% for loose, medium, and dense sand cases, respectively. As the sand gets denser, the settlement of the shallow foundation decreases about 10%. Figure 20 illustrates the maximum settlement comparison for 4 m soft clay layer case.

Figure 19 
                     Soft clay thickness (4 m) with loose, medium, and dense sand.
Figure 19

Soft clay thickness (4 m) with loose, medium, and dense sand.

Figure 20 
                     Maximum settlement comparison for 4 m soft clay.
Figure 20

Maximum settlement comparison for 4 m soft clay.

8.3.3 For 5 m soft clay layer thickness

Figure 21 illustrates the effect of a 5 m soft clay layer thickness on the settlement of the foundation with the (loose, medium, dense) sand cases. It is obvious that with dense sand cases, the settlement of the shallow foundation reduces much more than that of loose or medium sand cases. The results indicate that the settlement reduced by about 18.96, 28.47, and 25.2%, respectively, for loose, medium, and dense sand cases due to the presence of a soft clay layer lying 5 m away from the shallow foundation. The results indicate that dense sand cases showed the highest performance. Figure 22 illustrates the maximum settlement comparison for 5 m soft clay layer case.

Figure 21 
                     Soft clay thickness (5 m) with loose, medium, and dense sand.
Figure 21

Soft clay thickness (5 m) with loose, medium, and dense sand.

Figure 22 
                     Maximum settlement comparison for (5 m) soft clay.
Figure 22

Maximum settlement comparison for (5 m) soft clay.

9 Conclusion

  1. The closeness of a soft clay layer affected the performance of a shallow foundation exposed to a seismic wave. It was reached that as close the soft clay layer to the foundation as the settlement under the foundation increased.

  2. With increasing the thickness of the intermediate soft clay layer, the settlement of a shallow foundation reduction was higher for all soil conditions (loose, medium, and dense).

  3. A shallow foundation for cohesive soils is less sensitive to the earthquake, and that for dry cohesion less soil may be more susceptible.

  4. Wave propagation in cohesion soil is less than in cohesion-less soil.

  5. The stress increased with the acceleration of the earthquake increase.

  6. Earthquake with higher acceleration has a higher influence on shallow foundation stability.

  1. Funding information: The author states no funding involved.

  2. Conflict of interest: The author states no conflict of interest.

  3. Data avilability statement: The most datasets generated and/or analysed in this study are comprised in this submitted manuscript. The other datasets are available on reasonable request from the corresponding author with the attached information.

References

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Received: 2023-09-08
Revised: 2023-12-08
Accepted: 2023-12-23
Published Online: 2024-03-18

© 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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  112. Inductive 3D numerical modelling of the tibia bone using MRI to examine von Mises stress and overall deformation
  113. An image encryption method based on modified elliptic curve Diffie-Hellman key exchange protocol and Hill Cipher
  114. Experimental investigation of generating superheated steam using a parabolic dish with a cylindrical cavity receiver: A case study
  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
  203. Assessment of surface hardness and impact strength of denture base resins reinforced with silver–titanium dioxide and silver–zirconium dioxide nanoparticles: In vitro study
  204. A data augmentation approach to enhance breast cancer detection using generative adversarial and artificial neural networks
  205. Modification of the 5D Lorenz chaotic map with fuzzy numbers for video encryption in cloud computing
  206. Special Issue: 51st KKBN - Part I
  207. Evaluation of static bending caused damage of glass-fiber composite structure using terahertz inspection
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