Machine Learning Approaches for Predicting Flexible Asphalt Pavement Elastic Modulus: ANN vs. Random Forest vs. XGBoost

This study compared four predictive models—Linear Regression (LR), Artificial Neural Networks (ANN), Random Forest (RF), and Extreme Gradient Boosting (XGBoost)—for estimating the elastic modulus of flexible asphalt pavement. ANN demonstrated the highest predictive accuracy, with an optimized architecture featuring a single hidden layer with nine neurons. It achieved the best performance, with an R² value of 0.997, RMSE of 0.677, and MAE of 0.483. LR showed the weakest results, while RF and XGBoost performed better, with XGBoost slightly outperforming RF. However, neither model surpassed ANN. The findings highlight the importance of selecting appropriate predictive models for pavement modulus estimation, as ANN effectively captured complex nonlinear relationships. Due to limited data, the study evaluated models without splitting the dataset, which may have led to an overly optimistic assessment. Future research should incorporate larger datasets from diverse pavement structures and traffic conditions to improve model generalization. Additionally, exploring hybrid modeling approaches that combine multiple machine learning algorithms could further enhance predictive accuracy, offering more robust solutions for pavement design and quality assessment

Effects of asphalt binder and aggregate gradation on dynamic modulus, resilient modulus and moisture resistance of asphalt concretes

In this paper, the effects of asphalt binder and aggregate gradation on dynamic modulus (|E*|), resilient modulus (Mr) and moisture resistance of asphalt concretes (AC) have been studied. Six different asphalt concretes are designed with two aggregate gradations (nominal maximum aggregate size of 12.5 and 19 mm) and three types of asphalt binders (penetration grades of 40/50, 60/70 and a polymer-modified bitumen PMB3). Dynamic modulus, resilient modulus and Tensile Strength Ratio (TSR) test have been performed on the studied AC. The |E*| values obtained from dynamic modulus test at various frequencies and temperatures are simulated using a linear viscoelastic model 2S2P1D. Experimental results indicate the clear effect of asphalt binder and aggregate gradation on mechanical properties of tested AC. The 2S2P1D model successfully simulates the |E*| master curve with high precision (R² values from 0.84 to 0.97). The roles of 40/50 and PMB3 asphalt binder in enhancing the performance of asphalt concretes are also clearly demonstrated under each specific temperature condition and mechanical property type

Experimental Evaluation for Improving the Engineering Properties of Concrete Using Partial Replacement of Natural Waste

With the global growth of building construction and infrastructure around the world, the global demand for concrete materials in the construction industry is increasing day by day. Natural waste can be considered an alternative substitute that can be partially mixed into concrete up to a certain limit while maintaining the strength and properties of the concrete for a long duration. In this research, crushed coconut shell as fine and coarse aggregate and coconut shell ash as cement are used as a partial replacement for fine aggregate, coarse aggregate, and cement in concrete. A mix design of M20-grade concrete was prepared as per BIS 1026 2019, and 150 × 150 × 150 mm³ sized cubes of concrete were designed. Concrete materials were replaced with a different form of coconut shells, as cement was replaced with coconut shell ash. In this research, the effects of replacing cement, fine aggregate (FA), and coarse aggregate (CA) were tested in concrete with alternative materials (CSA, CSFA, CSCA) at different levels (0–25%). Concrete strength was measured after 28 days, which represents reduced strength from 24.58 MPa (0%) to 12.80 MPa (25%) in replacing cement with CSA. Increased strength at 5% (28.58 MPa) but dropped to 8.29 MPa at 25% in replacing FA with CSFA. Reduced strength to 8.14 MPa at 25% in replacing CA with CSCA. Replacing all three together lowered strength to 7.25 MPa at 25%. So, only replacements of small proportion (CSFA at 5%) can improve strength, but higher percentages reduce concrete performance. After being prepared, the mould was kept for curing for 3, 7, 14, and 28 days, after which its compressive strength was tested. The result analysis shows that mixing up to 5-10% of crushed coconut shell (CCS) and coconut shell ash (CSA) in concrete does not affect the strength or durability. The limitation of using this natural waste is that it can be substituted up to a certain limit, and the strength graph decreases significantly beyond that limit

Reviewing the degradation of environmental pollution in cement concrete structures using Nano-Titanium Dioxide

The rising levels of pollution globally affect cement concrete structures and historical monuments by making them fade, stained, and dull due to settling of dust particles. Titanium Dioxide (NT) is a naturally occurred photocatalytic material when used with construction materials (CM), offers benefits such as environmental pollution degradation and self-cleaning action. Moreover, its application supplements in enacting the original appearance of the structure for longer times. The main aim of this review study is to summarize the current information available primarily on ‘environmental pollution degradation and self-cleaning effect’. The standard tools for effective summarization of existing data like a) PRISMA analysis, b) VOSviewer, and c) Citespace were used. Further, the major research gaps, environmental impacts, concept of sustainability in relation to utilization of NT and future trends are incorporated. This review successfully concludes the potential application of NT in cement concrete structures for possible reduction of environmental pollution

Performance comparison of hyperbolic paraboloidal shell footing with its flat counterpart

While traditional flat footings are commonly used in construction, hyperbolic paraboloidal shell footings present potential benefits in load distribution and settlement reduction. The study encompasses two primary aspects: the design of both footing types in accordance with Indian standard practices, followed by a comparative analysis of their performance utilizing finite element methodology. Performance comparison is carried out concentrating on vertical settlement, stress distribution, and the amount of concrete required under centric gravity loads. The hyperbolic paraboloidal shell footing was modeled with curved surfaces, and the underlying soil was treated as nonlinear using the Mohr-Coulomb yield criteria. The amount of concrete required for a hyperbolic paraboloidal shell footing is significantly less, calculated to be 0.61 times that of a flat footing.

Strengthening of Deficient Drop-in-ends with Near Surface Mounted (NSM) Steel Bars under static and repeated loading

The present research work, presented the results of eight drop-in-ends specimens tested experimentally to investigate the efficiency of the NSM steel bars technique in strengthening the drop-in-ends including internal miss detailing, under static and repeated loading. Two values of shear span/depth (a/d) ratios was considered, namely are 1.0 and 1.5. Several variables were considered including (a/d) ratio, effect of deficient nib reinforcement (by about 40%) and the type of loading. The behaviour has been discussed in terms of cracking load, failure load, cracking pattern, load-deflection curve and failure mode. Results revealed that increasing a/d ratio from 1.0 to 1.5 yielded a reduction in capacity and the corresponding deflection by 33% and 5%.Moreover, capacity reduced by 11% and 5% for the two values of a/d respectively, when the nib steel reduced by (40%).Furthermore, it was found that the strengthening by NSM steel bars resulted in increasing capacity by 15% and 14% for the two a/d ratio respectively. Regarding the repeated loading tests, it was found that capacity and corresponding deflection reduced by 25% and 42% for a/d =1.0 relative to the strengthened specimen and tested under static loading ,while the respective values for a/d =1.5 were 5% and 3%.  In addition, it was obtained that the capacity was reduced by 16% when increasing a/d ratio from 1.0 to 1.5

Innovations in Green Construction: A Comprehensive Review of Limestone Calcined Clay Cement

Cement production is a major environmental concern, releasing nearly one tonne of carbon dioxide for every tonne of cement produced making it one of the largest industrial contributors to global CO₂ emissions. Limestone Calcined Clay Cement concrete is a new type of concrete that uses a mix of limestone and calcined clay as its binder. Combining limestone and calcined clay creates a low-clinker cement blend with impressive early-age strength. The durability of these cement systems is closely linked to their pore structure, which directly impacts how easily substances can move through the material. It is an eco-friendly, cost-effective, and high-performing option, offering a sustainable alternative to traditional Portland cement. This review paper provides insights into the edge-cutting features of LC3, manufacturing process of LC3. This review paper also details the emphasis on composition, properties, and applications of LC3. The review paper summarizes the findings from the numerous literature surveys, research gaps, and further areas for research and development

Influence of Aggregate Type and Size on Residual Mechanical Properties of Post-Heated Geopolymer Concrete: Experimental Study and Applications of Artificial Neural Networks

To mitigate environmental impacts from Portland cement (PC) production, the researcher’s efforts is introducing eco-friendly alternatives such as Geopolymer concrete (GPC). While GPC shows promise, further research is required to understand how fire or elevated temperatures affect GPC’s mechanical properties. This research investigates the effects of elevated temperatures (200℃, 400℃, 600℃, and 800℃) on the residual mechanical properties (compressive, flexural, splitting-tensile strengths, and modulus of elasticity) of ambient-cured fly-ash (FA)-based GPC compared to PC mixtures. The study examined various concrete types (GPC and PC), three coarse aggregate types (basalt, gravel, and crushed dolomite), and three crushed dolomite sizes (40 mm, 20 mm, and 14 mm). Additionally, Artificial Neural Network (ANN) models were developed to predict the residual compressive strength of both ambient-cured and heat-cured GPC after exposure to elevated temperatures. Results showed that basalt aggregate significantly enhanced the residual mechanical properties at 800 ℃, outperforming crushed dolomite and gravel in compressive, flexural, splitting-tensile strengths, and modulus of elasticity, with increases of (20%, 80%), (26%, 244%), (10%, 100%), and (14%, 140%), respectively. Moreover, the residual mechanical properties were found to be inversely proportion with max size of coarse aggregate. In addition, using ANN models proved its efficient in predicting the compressive strength for both ambient and heat-cured GPC with R² values of 0.94 and 0.887, respectively

Study on Mechanical and Tribological Characterization of Titanium Diboride (TiB2) Reinforced Al7075 Composites by Taguchi Technique

Three distinct titanium diboride (TiB2) weight percentages 3%, 6%, and 9% were incorporated into Al7075-TiB2 composites by stir casting. Al7075-TiB2 composites' wear and mechanical characteristics were evaluated. The microstructural investigation titanium diboride verified the stable interfacial bond between the matrix and reinforcing material as well as the uniform distribution of TiB2 particles. Superior mechanical properties were noted when comparing the 9% TiB2 composites to the 3 and 6% TiB2 composites. The tensile strength was increased by 11.94% for 9% TiB2 reinforced Al composites. Dry sliding wear was measured with pin-on-disc device. Measurements of the samples' wear loss as well as coefficient of friction (COF) showed that the cumulative wear loss for each composite varied linearly with load. As seen by the optical microscope, all specimens within the prescribed tension and sliding distance appear to have oxidative wear on the worn-out surfaces of the wear mechanism. Wear rate is most affected by weight percentage TiB2 (48.43%), followed by load (19.08%), according to the ANOVA. The wt. % of TiB2, at 37.68%, has the biggest effect on the COF, followed by sliding distance (20.54%). Taguchi technique validates the beneficial impact of weight percentage TiB2 on wear loss and COF. The composite reinforced with 9% TiB2 has the finest tribological and mechanical properties

Structural Health Monitoring of Steel Girder Bridge Using Photogrammetry and LiDAR Scan Technology: Proof of Concept

Bridges require regular inspection and maintenance; however, traditional inspections are performed manually at prescribed intervals, involving substantial manpower, high costs, and safety risks due to the challenging locations of many bridges. To address these limitations, the present study focused on developing a methodology to automate technical inspections of bridges using a hybrid approach combining LiDAR and photogrammetry. Unlike past drone inspections, which were largely limited to basic photography and videography, this approach integrates advanced technologies for more comprehensive data collection. For this purpose, a single-span steel girder bridge with a span of 45.7 meters, located between Beas and tto Tanda in the state of Punjab, India, was selected. A Proof-of-Concept (PoC) was developed using high-fidelity digital models, created through photogrammetry with UAV-mounted high-resolution cameras and LiDAR, to carry out 16 inspection missions. The development of these high-fidelity digital models enabled flexible viewing, analysis, and measurement of various structural parameters, including the schedule of dimensions diagram, camber, distortions, rail levels, creep, and eccentricity. The parameters measured from the digital models were compared with the limiting values specified by RDSO, as well as with manually collected data. It was observed that the dimensional measurements obtained through the automated technology were within ±5 mm of the drawings and previous inspection reports, indicating that photogrammetry combined with LiDAR is a reliable and effective alternative technology for bridge inspection