Khanna’s path to the chairmanship was, in a sense, an extended audition. During his fourteen months as interim chair, he undertook what colleagues describe as an unusually systematic listening exercise, meeting extensively with faculty, staff, and students while also engaging the department’s external partners in industry and government. The goal was not ceremonial. He wanted a granular picture of the department’s strengths, its unmet needs, and the opportunities where civil and environmental engineering could grow. Those conversations fed directly into concrete administrative changes, including strengthened departmental operations, more rigorous academic and faculty planning, and the creation of a CEE Honors and Awards Committee designed to formally recognize excellence within the department.

That record of translating consultation into action was central to the case for his permanent appointment. Michele V. Manuel, the U. S. Steel Dean of Engineering, praised Khanna’s interim tenure as a model of responsive leadership. In her assessment, he listened carefully to every constituency the department serves and then converted what he heard into institutional change. She noted that he understands the department deeply, has already strengthened its operations and planning processes, and articulates a clear vision for where civil and environmental engineering at Pitt can expand in education, research, and external engagement. For a school weighing candidates from a national search, that combination of institutional knowledge and demonstrated execution proved decisive.

The search itself was a formal affair, chaired by Sanjeev Shroff and conducted by a committee that drew representation from the department’s faculty, staff, and students, as well as from the Swanson School leadership and the CEE Visiting Committee. That breadth of participation reflected the stakes: the chair of a civil and environmental engineering department sits at the intersection of academic priorities and the practical demands of infrastructure agencies, engineering firms, and municipalities that depend on the department’s graduates and research. The committee’s recommendation of Khanna, following the national search, signaled confidence that an internal candidate offered the strongest vision for the department’s future.

Khanna’s own academic trajectory is unusually broad for a civil and environmental engineer, and it helps explain the interdisciplinary ambitions he brings to the role. He joined the University of Pittsburgh in 2010 and rose through the faculty ranks, being promoted to full professor in 2023. Between 2017 and 2022, he served as the department’s associate chair for graduate studies, a position that placed him in charge of graduate recruitment, admissions, orientation, academic requirements, and program development. He has also chaired faculty searches and sat on committees at both the school and university levels, giving him a comprehensive view of how the institution’s academic machinery operates.

His educational background spans chemical engineering, statistics, and applied mathematics. Khanna earned his bachelor of engineering in chemical engineering from Punjab University before moving to The Ohio State University, where he accumulated three graduate degrees: a master’s in applied statistics and both a master’s and a doctorate in chemical engineering. That quantitative foundation is evident in his scholarship, which treats environmental systems not as isolated problems but as interconnected networks that can be modeled, optimized, and stress-tested. His methodological toolkit includes systems analysis, life-cycle assessment, optimization techniques, and data-driven modeling, all deployed to examine the environmental consequences of emerging technologies and complex engineered systems.

The subject matter of that research reads like a map of the challenges confronting infrastructure in the twenty-first century. Khanna has focused on water and resource recovery, exploring how wastewater and industrial byproducts can be transformed from liabilities into assets. He has examined the circular economy, asking how materials can circulate through the economy repeatedly rather than flowing from extraction to disposal. His work on resilient infrastructure addresses how civil systems can be designed to withstand shocks, whether from climate-driven extremes or other disruptions, and he has investigated emerging energy and water technologies that promise to decarbonize and democratize access to essential services. The through-line is a conviction that environmental performance must be quantified rigorously before it can be improved.

The scholarly record supporting that conviction is substantial. Khanna has published more than 75 peer-reviewed articles and has served as principal investigator or co-principal investigator on nearly $10 million in externally funded collaborative research, a figure that reflects both the competitiveness of his proposals and the collaborative character of his science. Since 2017, he has served as an editor of Resources, Conservation and Recycling, one of the leading journals in the field of resource sustainability, where he has helped shape the scientific conversation around material flows and circularity. His professional service extends to leadership roles within the Sustainable Engineering Forum of the American Institute of Chemical Engineers, and he participated in the National Academy of Engineering’s Frontiers of Engineering Education Symposium, a program that convenes rising leaders to rethink how engineers are trained.

Now, as permanent chair, Khanna has laid out a forward-looking agenda built on the premise that civil and environmental engineering is inherently interdisciplinary and should be organized as such. Among his stated priorities is a deeper integration of artificial intelligence into the department’s curricula, ensuring that graduates are fluent in the machine learning and data analysis tools increasingly used to design, monitor, and manage infrastructure. He also plans to develop new graduate pathways that connect civil and environmental engineering with public health and computing, formalizing the links between water quality, environmental conditions, and human health outcomes. In parallel, he intends to expand IRISE, the department’s initiative in resilient and intelligent infrastructure, and grow its partnerships, while strengthening research at the nexus of water, the environment, and public health.

The vision, as Khanna himself frames it, is grounded in the everyday ubiquity of the discipline he now leads. Civil and environmental engineering, he notes, shapes the systems that people rely on every single day, from the water that arrives at the tap to the roads and bridges that carry daily commutes. His ambition is to strengthen those systems through interdisciplinary education and research, working alongside the department’s faculty, staff, students, and external partners. In an era when infrastructure must simultaneously adapt to climate change, incorporate intelligent technologies, and serve public health, the University of Pittsburgh has placed its confidence in a leader whose entire career has been devoted to quantifying and improving the environmental performance of the systems that hold modern life together.

Subject of Research: Appointment of sustainability researcher Vikas Khanna as Chair of Civil and Environmental Engineering at the University of Pittsburgh Swanson School of Engineering

Article Title: Vikas Khanna named Chair of Civil and Environmental Engineering at Pitt

Article References: Vikas Khanna named Chair of Civil and Environmental Engineering at Pitt. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Vikas Khanna, University of Pittsburgh, Swanson School of Engineering, civil engineering, environmental engineering, sustainability, life-cycle assessment, circular economy, resilient infrastructure, artificial intelligence, water resource recovery, public health

The research team, led by Désiré Ndahirwa of UniLaSalle with colleagues including Hélène Lenormand, Hafida Zmamou and Nathalie Leblanc, focused on a question that has dogged the field for years. Wood ash contains reactive silica, alumina and calcium-bearing phases that can, in principle, behave like cement itself, reacting with water through hydraulic and pozzolanic pathways. In practice, however, pastes made from pure wood ash are weak and porous. Previous studies had shown that replacing moderate amounts of cement with wood ash often reduces compressive and flexural strength, and most work had examined substitution levels below 50 percent. Almost nothing was known about what happens at very high replacement levels, where wood ash dominates the mixture, and the stiffness of such materials, measured as Young’s modulus, had rarely been quantified despite its importance for structural design.

To close that gap, the researchers gathered four locally sourced wood ashes from the Normandy region of France. Two of them, designated WFA3 and WBA, came from the combustion of wood pellets and were delivered as wet sludge, requiring oven drying and crushing before use. The other two, WFA8 and WFA9, arrived as dry fine powders from a local heating plant operated by Coriance in Mont-Saint-Aignan, where boilers with power inputs of 6 and 8 megawatts burn forestry wood chips, bocage wood chips and pallet residues at temperatures between 900 and 1100 degrees Celsius. The team prepared seventeen paste formulations in total: four containing only wood ash, twelve blending 80 to 95 percent wood ash with 5 to 20 percent ordinary Portland cement, and a reference paste of pure cement, all compacted with a mini-Proctor device to boost density and cured for up to 28 days.

The chemical analysis alone revealed why wood ash is such a tricky raw material. The four ashes were dominated by calcium oxide, silica, potassium oxide and sulfur trioxide, but in wildly varying proportions. Sulfate contents reached 15.4 percent in WFA8 and 14 percent in WFA9, far above the 4 to 5 percent limit set by ASTM standards for pozzolans, and their combined pozzolanic oxides fell well below the required thresholds. In plain terms, these ashes do not qualify as conventional pozzolans, yet X-ray diffraction showed they carry crystalline phases such as portlandite, calcite, albite, alite, dolomite and sylvite that can still participate in binding reactions. The variability is a direct consequence of differing feedstocks, boiler designs and combustion temperatures, and it means each ash must be evaluated on its own terms rather than lumped into a single category.

When it came to mechanical performance, the effect of the small cement additions was unmistakable. Pure wood ash pastes managed compressive strengths of only 0.13 to 1.65 megapascals at 28 days, but raising the cement content to 20 percent lifted those values substantially. The best performer was the WFA8-based blend, which reached 5.49 megapascals, while WFA9 and WFA3 pastes achieved 4.01 and 3.87 megapascals respectively at the same dosage. The researchers attribute the gains to a richer supply of hydration products, including calcium silicate hydrate gel, portlandite and ettringite, formed as the cement’s tricalcium silicate reacts with water and progressively densifies the paste matrix. Stiffness told the same story: the modulus of elasticity, estimated from the linear portion of stress-strain curves, climbed with cement content, curing time and bulk density in three of the four ash families, with the highest values consistently recorded in mixtures containing 20 percent cement.

One ash refused to follow the script. The wood bottom ash, WBA, behaved atypically across every measurement. Its pastes lost compressive strength between 7 and 28 days at certain dosages, its modulus of elasticity peaked at 7 days and then declined, and thermogravimetric analysis found no detectable portlandite whatsoever. X-ray diffraction offered an explanation: the WBA pastes contained no alite, the calcium silicate phase that drives strength development in hydrating cement, and their dominant crystalline phases were calcite and quartz. Adding 20 percent cement pushed the estimated calcite content up from about 47 to 63.5 percent while quartz fell, a signature of carbonation of calcium silicate hydrate or the formation of complex, less efficient hydrate phases, both of which are associated with increased porosity and weaker binding.

Scanning electron microscopy added a visual dimension to the story. Under the microscope, pure cement paste appeared dense and well packed, bristling with the products of hydration, while pastes made from 100 percent wood ash showed loosely arranged particles riddled with interparticle voids, along with unreacted ash grains and dark fragments of unburnt wood. With 20 percent cement added, the microstructure tightened, porosity dropped and hydration products proliferated, with needle-like ettringite crystals, gel-like calcium silicate hydrates, plate-shaped portlandite and rhombohedral calcite all visible. The ashes from the heating plant, WFA8 and WFA9, consistently produced more compact matrices than the pellet-derived WFA3 and the bottom ash WBA, underlining how much origin and processing shape a material’s destiny.

The mineralogical detective work also turned up some genuinely unexpected chemistry. In the WFA8 blends, introducing cement promoted the formation of alunite, a potassium aluminum sulfate hydroxide phase not present in the unblended paste, alongside an array of compounds including syngenite, arcanite, serandite and harmotome. Thermogravimetric analysis at 7 and 28 days complemented the diffraction data, identifying calcium silicate hydrates and ettringite dehydrating between 50 and 200 degrees Celsius, AFm phases such as calcium monocarboaluminate and hemicarboaluminate decomposing between 200 and 300 degrees, portlandite dehydroxylating between 400 and 500 degrees, and carbonates releasing carbon dioxide from 500 to 800 degrees. The two techniques agreed closely, with the single discrepancy being ettringite in the bottom ash pastes, which thermal analysis detected but diffraction did not, likely because its concentration fell below the instrument’s detection limit.

What emerges from the study is a nuanced but practical message. Low doses of ordinary Portland cement, between 5 and 20 percent, can meaningfully upgrade pastes in which wood ash makes up as much as 95 percent of the solid content, provided the ash is fine and reasonably reactive. The improvements in stiffness, strength and microstructure are real, even if the resulting materials remain suited to low-strength applications such as lightweight binders rather than load-bearing concrete. The decisive variable, the authors conclude, is the variability of the ash itself: its origin, chemistry and mineralogy govern everything from phase development to porosity. That insight carries weight well beyond Normandy. With millions of tons of biomass ash generated annually and cement production responsible for a major share of global carbon dioxide emissions, even modest cement dosages that transform a landfill-bound waste into a functional building material represent a meaningful step toward circular, lower-carbon construction. The next challenge will be standardizing how ashes are characterized and selected, so that builders can trust what is in the bag before it ever reaches the site.

Subject of Research: The effect of low ordinary Portland cement content on the stiffness, microstructure and mineralogical composition of wood ash-based pastes

Article Title: Effect of low ordinary Portland cement content on stiffness, microstructure and mineralogical composition of wood ash pastes

Article References: Ndahirwa, D., Lenormand, H., Zmamou, H., Chenot, E., Potel, S., & Leblanc, N. (2026). Effect of low ordinary Portland cement content on stiffness, microstructure and mineralogical composition of wood ash pastes. Cleaner Engineering and Technology, 34, Article 101303. https://doi.org/10.1016/j.clet.2026.101303

Image Credits: AI Generated

DOI: 10.1016/j.clet.2026.101303

Keywords: wood ash, ordinary Portland cement, Young's modulus, compressive strength, X-ray diffraction, thermogravimetric analysis, scanning electron microscopy, calcium silicate hydrate, ettringite, porosity, biomass ash, sustainable construction

Concrete, the backbone of modern infrastructure, traditionally relies on natural sand as a fine aggregate. However, the extraction of natural sand has increasingly raised environmental alarms due to riverbed degradation, habitat destruction, and rising extraction costs. Against this backdrop, the remarkable potential of industrial waste byproducts to replace natural aggregates has garnered significant attention. Yet, balancing the incorporation of these unconventional materials without compromising structural integrity has remained a critical challenge until now.

The research conducted by Singh and colleagues intricately explores the integration of various industrial wastes, such as fly ash, slag, and other mineral residues, as substitutes for conventional fine aggregates within an alkali-activated binding matrix. Alkali activation, an innovative cementitious technology, utilizes reactive aluminosilicates and alkaline solutions to produce hardened binders. Unlike ordinary Portland cement, alkali-activated materials demonstrate superior durability, chemical resistance, and a drastically reduced carbon footprint, aligning perfectly with global sustainability goals.

Central to their study is the novel concept of “performance-driven utilization,” whereby the selection and proportioning of industrial wastes are carefully optimized to meet stringent mechanical and durability performance metrics. This intelligent design framework transcends empirical mix designs by embracing a data-driven methodology, incorporating physicochemical characterization, microstructural analyses, and advanced mechanical testing. This holistic strategy ensures the resulting concrete not only performs on par with, or surpasses, traditional mixes but also exhibits enhanced sustainability attributes.

One of the study’s key breakthroughs is the successful ambient curing of the alkali-activated concrete. Conventionally, many geopolymers or alkali-activated materials require elevated temperature curing—often limiting scalability and increasing energy consumption. By demonstrating that industrial waste-infused alkali-activated concrete can attain requisite strength and durability characteristics under ambient temperatures, the research paves the way for more energy-efficient, cost-effective, and pragmatic construction applications.

The researchers meticulously characterized the particle size distribution, mineralogical composition, and surface morphology of the industrial wastes employed. These parameters critically influence the reactivity, workability, and bonding characteristics of the concrete. For instance, the incorporation of finely divided fly ash and granulated blast furnace slag not only contributed to filler effects but also participated actively in the binding phase through pozzolanic and latent hydraulic reactions. This synergistic interplay significantly augmented the microstructural densification and reduced porosity.

Mechanical testing revealed that mixes with tailored industrial waste content achieved compressive strengths exceeding 40 MPa after 28 days of ambient curing—a remarkable feat demonstrating the feasibility of these materials for structural applications. Additionally, durability assessments, including resistance to sulfate attack, chloride penetration, and freeze-thaw cycles, indicated superior performance vis-à-vis conventional concrete. Such resilience renders this technology particularly suitable for harsh environmental exposures often encountered in infrastructure projects worldwide.

An intriguing aspect of the study lies in its environmental impact evaluation. Life cycle assessment (LCA) metrics underscored substantial reductions in carbon dioxide emissions, energy consumption, and natural resource depletion relative to standard Portland cement concrete. By valorizing industrial waste streams—often destined for landfills or disposal—the approach inherently embodies the principles of circular economy, waste minimization, and industrial symbiosis.

Furthermore, the scalability and adaptability of this method were highlighted through case studies simulating real-world production scenarios. The versatility to adjust the mix design based on locally available waste materials allows for broad geographic applicability, especially in regions grappling with both waste management challenges and infrastructure development demands. This localization potential not only mitigates transportation-related carbon footprints but also empowers regional economies by converting liabilities into construction assets.

In terms of practical implementation, the researchers advocate for collaboration with industry stakeholders, regulatory bodies, and policymakers to foster technology transfer and standardization. They emphasize the necessity for developing comprehensive guidelines and quality control protocols to ensure consistent material performance across diverse production batches and construction environments. Such coordinated efforts will be instrumental to mainstream adoption and regulatory acceptance.

The study also opens promising avenues for further interdisciplinary research. Investigations into nano-engineered additives, self-healing functionalities, and hybrid composites combining alkali-activated binders with traditional cementitious systems could unlock new frontiers in concrete technology. Moreover, long-term field monitoring and durability trials under various climatic stresses will reinforce confidence in this innovative material system and elucidate performance trends over extended service lives.

Notably, the socio-economic implications of this research cannot be overstated. By lowering the reliance on finite natural sand resources and simultaneously reducing industrial waste accumulation, the construction industry gains a dual advantage: safeguarding ecosystems and diminishing raw material procurement costs. The cumulative effect may contribute to more affordable housing and infrastructure solutions while aligning with global climate action commitments.

As urbanization accelerates and infrastructure demands escalate globally, the urgency for sustainable material innovations intensifies. This pioneering research by Singh, Singh, and Paruthi embodies the transformative potential of science and engineering to challenge conventional paradigms and chart a sustainable pathway forward. By converting industrial detritus into high-performance concrete components through an environmentally benign process, they redefine what is possible in material engineering for the built environment.

In conclusion, the performance-driven utilization of industrial wastes in ambient-cured alkali-activated concrete stands as a beacon of hope and ingenuity amidst pressing environmental and infrastructural challenges. The synergy of material science, structural engineering, and sustainability principles embodied in this study offers a compelling blueprint for the future of concrete technology. As the industry moves towards decarbonization and circularity, such advancements will be instrumental in sculpting resilient, eco-conscious, and economically viable built environments for generations to come.

Subject of Research: Performance-driven utilization of industrial wastes as fine aggregates in ambient-cured alkali-activated concrete.

Article Title: Performance-driven utilization of industrial wastes as fine aggregates in ambient-cured alkali activated concrete.

Article References: Singh, P., Singh, H. & Paruthi, S. Performance-driven utilization of industrial wastes as fine aggregates in ambient-cured alkali activated concrete. Sci Rep (2026). https://doi.org/10.1038/s41598-026-56374-z

Image Credits: AI Generated

Traditional vehicles, powered primarily by fossil fuels, offer dismal energy efficiency. Studies show conventional cars convert only about 1% of the gasoline’s energy into actual motion, with the remainder dissipated as heat or used to propel heavy vehicle frames with little return in demonstrated utility. This startling inefficiency not only implies vast squandered resources but also exacerbates environmental degradation and climate change impacts. It is within this context that the Sustainable Mobility Center recognizes the urgent need for systemic rethinking—moving beyond incremental tech improvements to holistic redesign.

One of the key challenges the Center addresses is the inherent complexity of global transportation ecosystems. This complexity arises from the intricate interplay of vehicles, infrastructure, energy grids, operational frameworks, human behaviors, and policy environments. For example, while electric vehicles (EVs) reduce local pollution, their dependence on electric grids powered in part by fossil fuels shifts pollution burdens geographically rather than eliminating them. Moreover, the surge in EV adoption poses significant questions regarding grid stability and demand management, reflecting the interconnectedness of mobility and energy systems.

Stanford faculty co-directors Marco Pavone and Ram Rajagopal emphasize that this initiative is more than a technological endeavor; it is a profound cultural and systemic shift grounded in interdisciplinary innovation. The center leverages Stanford’s strengths across AI, autonomy, energy research, and data science, embedding these advances into transportation design for real-world scalability. AI and autonomous systems, in particular, are viewed as essential catalysts for achieving efficiency, safety, and coordination levels previously unattainable in the movement of people and goods.

The center’s approach is shaped by a systems-level philosophy, recognizing that reducing emissions or improving technology in isolation will not suffice. Instead, it demands coordinated redesigns that harmonize vehicle innovation, digital and physical infrastructures, energy generation and distribution, policy frameworks, and human-centric service design. This multifaceted approach acknowledges mutually reinforcing relationships. For instance, optimizing multi-modal transport networks requires simultaneous consideration of logistics, infrastructure resilience, economic incentives, and behavioral adaptations.

Integral to the center’s mission is bridging advanced research with practical impact. The leadership team combines expertise extending from fundamental energy science and power systems to autonomous vehicle engineering and entrepreneurial ventures in smart grid technologies. This breadth ensures the center operates at the nexus of theoretical insight, technological innovation, and real-world deployment, facilitating smoother pathways from lab breakthroughs to urban and regional mobility transformations.

The center’s activities will be sustained through collaborative industry partnerships, with corporate sponsors funding research and strategic initiatives. This model ensures that research remains attuned to market realities and fosters ecosystems where academia, industry, and government align around shared sustainability objectives. The founding industrial supporters—including major players from automotive manufacturing, shipping, logistics, energy, and technology sectors—underscore the broad stakeholder commitment needed to accomplish these objectives.

To tackle the inherently complex challenges in sustainable mobility, the center has framed several “Grand Challenges.” These include zero-emission freight logistics, development and scaling of sustainable aviation fuels, creation of intelligent logistics systems, establishment of multi-modal transportation networks, and enhancement of infrastructure resilience. Pursuing solutions for these challenges demands coordinated progress across adjacent technical domains so that advancements in vehicles, infrastructure, policies, and safety synchronize to unlock transformative benefits.

The Sustainable Mobility Center’s research structure is organized around five key pillars. These pillars encapsulate critical dimensions necessary for holistic mobility redesign. First is energy systems, focusing on electrification strategies, sustainable fuel development, grid interaction, and resilience. Second is infrastructure, emphasizing digital and physical assets such as charging networks and data-enabled transport systems. Third encompasses economics and policy, tackling incentive alignment and regulatory frameworks to ensure equitable and widespread adoption. Fourth pillar prioritizes safety, aiming to secure trustworthiness and resilience especially as autonomous technologies proliferate. The final pillar advocates interdisciplinary design that melds engineering, urban planning, and behavioral sciences to center human experience and systemic coherence.

By convening distinguished academic, industrial, and government leaders, the center fosters a collaborative ecosystem dedicated to defining priorities and articulating pathways for sustainable mobility innovations. This approach not only accelerates research synergies but also promotes scalable deployment of solutions that address intertwined sustainability imperatives—from emissions reductions and energy efficiency to social equity and economic viability.

With emerging technologies like AI and autonomy perceived not just as complementary but as central pillars of sustainability, the center is positioned to drive a paradigm shift in mobility systems. The persistent energy waste and environmental costs inherent in legacy transportation modes call for bold innovation, and Stanford’s initiative provides a beacon for how integrated technological, economic, and policy strategies can coalesce to reimagine our planet’s mobility future.

As the Sustainable Mobility Center embarks on this mission, it beckons a new era where the movement of goods and people is seamlessly efficient, environmentally harmonious, financially accessible, and robustly safe. The integration of advanced AI, smart infrastructures, and sustainable energy networks promises to revolutionize mobility with far-reaching impact—paving the way for cleaner cities, healthier communities, and a regeneration of trust in transportation as a foundation for equitable global progress.

Subject of Research: Sustainable and integrated transportation systems utilizing AI, autonomy, advanced energy integration, and systemic redesign for global sustainability.

Article Title: Stanford’s Sustainable Mobility Center: Rethinking Transportation for a Low-Carbon, Equitable Future

News Publication Date: Not explicitly stated; inferred May 21 for inaugural meeting

Web References:
– https://sustainablemobility.stanford.edu
– https://energy.stanford.edu
– https://fuels.stanford.edu
– https://ora.stanford.edu

References: Not explicitly provided in the original content.

Image Credits: Courtesy Center for Automotive Research at Stanford

Keywords: Sustainable mobility, electric vehicles, transportation efficiency, energy systems, AI and autonomy, smart grids, zero-emission freight, sustainable aviation fuel, multi-modal transport, infrastructure resilience, policy and economics, interdisciplinary design

One pivotal development in the modernization of construction is the advent of intelligent construction systems. These systems incorporate advanced technologies, including artificial intelligence, machine learning, and data analytics, to optimize various aspects of the construction process. These innovations enhance project management, improve safety standards, and reduce environmental impacts, demonstrating the potential of technology-driven methodologies. As more engineers and architects embrace these intelligent solutions, the future of construction looks increasingly promising.

The current trend in intelligent construction extends beyond mere technological integration; it embodies a paradigm shift towards a more integrated approach. This shift acknowledges the profound interplay between civil engineering and environmental management, particularly in the context of water resources. Hydraulic engineering has emerged as a cornerstone of intelligent construction, addressing the need for sustainable water management systems. The intersection of civil engineering and hydraulic systems offers innovative solutions to modern urban challenges, such as flooding and water scarcity, essential for a resilient infrastructure.

The upcoming 2nd International Conference on Civil Engineering and Smart Construction (ICCESC 2025) is poised to be a pivotal event for scholars and practitioners in the field. This conference aims to bridge the gap between cutting-edge research and current industrial practices. By creating a platform for knowledge exchange, the conference will showcase the latest advancements in both civil engineering and smart construction technologies. Furthermore, it serves as an opportunity for researchers and industry professionals to collaborate and foster synergistic relationships that advance the construction sector.

In addition to the exploration of intelligent construction, the conference will address various facets of civil engineering. Geotechnical, structural, and hydraulic engineering are just a few areas that will feature prominently in discussions. These disciplines are crucial not only to the built environment but also to the well-being of communities. The emphasis on innovative design and sustainable practices reflects an urgent need to adapt engineering solutions to the realities of climate change and population growth. The dialogue at ICCESC 2025 is expected to deepen the understanding of how such adaptations can be implemented effectively.

Given the ongoing global urbanization trend, intelligent construction has become increasingly relevant. Cities around the world face unprecedented challenges, including infrastructure degradation and increased resource consumption. Intelligent construction methodologies provide tools to address these issues through smart resource management and predictive maintenance strategies. Such approaches not only promise cost efficiency but also align with broader sustainability goals by minimizing waste and optimizing resource use.

As the conference approaches, the call for papers invites researchers and industry leaders to contribute their insights and findings. This collective intellectual effort is essential for advancing the field of civil engineering. Topics such as disaster prevention, green building practices, and engineering informatics will be explored, reflecting the diverse range of challenges faced by the industry. Furthermore, the integration of intelligent equipment and robotics into the construction process signifies a revolutionary shift towards automation and enhanced safety protocols.

A focal point of discussion at the conference will be the role of digital construction technologies. The transition from traditional construction methods to digitized processes is a significant leap towards innovation in the industry. Technologies such as Building Information Modeling (BIM) and virtual reality are transforming how projects are designed and executed. These tools facilitate collaboration among all stakeholders, ensure accuracy in project planning, and enhance communication across teams.

Moreover, the integration of smart construction principles into urban planning can fulfill the resilience and adaptability required in modern infrastructure. Concepts such as green architecture and intelligent building design contribute significantly to achieving sustainability goals while enhancing the quality of life for urban residents. As researchers delve into these concepts, it becomes evident that the future of urban development hinges on sustainable practices, smart technology, and innovative engineering solutions.

In closing, the evolution of civil engineering is a chronicle of adaptation, resilience, and innovation. The importance of intelligent construction cannot be overstated as it heralds a future where technology and engineering combine to create sustainable and efficient infrastructures. The 2nd International Conference on Civil Engineering and Smart Construction is set to shine a spotlight on these developments, promoting discourse that encourages growth and collaboration within the industry. As we progress towards this future, it is imperative that we harness the potential of intelligent construction to address contemporary challenges and build a sustainable legacy.

The dynamic shifts in civil and hydraulic engineering reflect broader societal innovations and challenges; however, they also underscore a continuity of purpose to build stronger, safer, and more sustainable communities. The convergence of technology and engineering signifies a pivotal moment that not only redefines construction practices but also reshapes how we envisage the future of urban living. As we embrace these advancements, the collective efforts of researchers, practitioners, and policymakers will be instrumental in realizing the vision of smart, resilient cities worldwide.

Subject of Research: Intelligent Civil Engineering and Smart Construction
Article Title: Advances in Intelligent Construction: Shaping the Future of Civil Engineering
News Publication Date: October 27, 2023
Web References: [Insert website links if available]
References: [Insert reference details if available]
Image Credits: [Insert image credits if available]

Keywords

Civil Engineering, Intelligent Construction, Hydraulic Engineering, Sustainable Building, Urban Development, Engineering Technology, Smart Infrastructure, Disaster Management, Digital Construction, Green Architecture, Intelligent Design, Predictive Maintenance.

As urban areas continue to expand at an unprecedented rate, the demand for water has surged, creating a critical need for efficient management and forecasting systems. The researchers aimed to tackle this challenge by employing artificial neural network models, which are sophisticated computational frameworks designed to mimic the human brain’s structure and functionality. These models excel at identifying patterns within large datasets, making them particularly effective for predictions in complex environments like urban water systems.

The primary focus of the study was to develop a robust model that could accurately predict water demand in various municipalities across Southern Brazil. By gathering historical data encompassing various factors such as population growth, temperature fluctuations, and rainfall patterns, the researchers were able to train their neural network to discern the underlying patterns influencing water consumption. This approach not only allowed for the creation of a predictive tool but also highlighted the multifaceted nature of urban water demand.

One key aspect of the research was the design and implementation of the neural network model. The study employed a multi-layer perceptron, a type of feedforward artificial neural network, which is particularly suitable for regression tasks, such as forecasting. By utilizing multiple layers of interconnected nodes, the model can capture nonlinear relationships within the data, enabling it to generate precise and actionable forecasts about future water demand levels.

An essential part of the study’s success lay in the preprocessing of data to ensure the quality and relevance of the input fed into the neural network. This involved normalizing the data to mitigate issues related to scale differences among various input features. Additionally, the team employed techniques such as cross-validation to validate their findings and prevent overfitting, which is a common issue in predictive modeling where a model becomes too tailored to the training data at the expense of its performance on unseen data.

The results of the study presented compelling evidence that artificial neural networks can significantly enhance the accuracy of water demand forecasting. The model was able to predict water usage trends with remarkable precision, allowing municipalities to make informed decisions regarding water resource management. This capability is crucial as it enables stakeholders to proactively address potential shortages and optimize supply chains, paving the way for more resilient urban environments.

Furthermore, the implications of this research extend beyond immediate water management. By implementing reliable forecasting systems, cities in Southern Brazil can better plan infrastructure projects, such as plumbing upgrades and new pipeline installations, thereby increasing their investment efficiency. Accurate forecasting also contributes to sustainable development goals, as it aligns with efforts to ensure availability and sustainable management of water and sanitation for all.

Notably, the adoption of artificial intelligence in urban water systems is increasingly gaining traction in various parts of the world. Cities are beginning to grasp the potential of such advanced technologies to transform traditionally static management practices into dynamic, responsive systems. The findings of this study reinforce the idea that modern challenges necessitate modern solutions, particularly in areas where resource scarcity is becoming more prominent due to environmental changes.

This research also sheds light on the broader application of artificial intelligence in urban planning. The integration of AI-driven models allows for more sophisticated and nuanced understanding of urban dynamics. Policymakers can utilize these insights to create sustainable and resilient policies that prioritize water conservation while accommodating the needs of growing urban populations.

The use of such innovative technology could also serve as a template for other regions facing similar urbanization challenges. As cities across the globe grapple with climate variability and increasing water demand, the methodologies developed in Southern Brazil could be adapted and implemented in diverse geographic contexts. This demonstrates the universal relevance of the study, as challenges related to water management are not confined to one particular region but resonate globally.

In conclusion, the research conducted by Estrada and his colleagues represents a significant milestone in harnessing artificial neural networks for urban water demand forecasting. By demonstrating the potential for machine learning to offer valuable insights into consumption patterns, this study serves as a rallying call for urban planners, policymakers, and environmental advocates to embrace technological advancements in their quest for sustainability. The integration of AI in urban water management represents not just a step forward in practical applications, but a vision for a future where cities can exist harmoniously with their natural water resources.

In an era marked by increasing uncertainty related to climate change and urban expansion, studies like these are vital in transforming how cities approach resource management. Through the use of empirical data and advanced modeling techniques, cities can cultivate a proactive rather than reactive approach to problem-solving, ensuring that they not only meet current demands but also safeguard the interests of future generations.

Strong partnerships between researchers, technologists, and urban planners will be essential as communities worldwide seek to embrace these innovative forecasting models. As this study illustrates, the effective amalgamation of data science and urban management has the potential to revolutionize our approach to sustainable living.

As the dialogue around the sustainability crisis continues, it is imperative that both public and private sectors invest in research and development to explore the full capabilities of artificial intelligence in resource management. By doing so, cities can not only enhance their resilience but also improve the quality of life for their residents, thus creating a legacy of sustainability for generations to come.

Subject of Research: Urban water demand forecasting via artificial neural network models in Southern Brazil.

Article Title: Urban water demand forecasting via artificial neural network models: a case study in Southern Brazil.

Article References:

Estrada, A.V., Henning, E., Kalbusch, A. et al. Urban water demand forecasting via artificial neural network models: a case study in Southern Brazil.
Discov Sustain 6, 1105 (2025). https://doi.org/10.1007/s43621-025-01917-z

Image Credits: AI Generated

DOI:

Keywords: Urban water demand, artificial neural networks, sustainability, forecasting, climate change, resource management.

Dr. Nairn posits that infrastructure transcends the traditional definitions of roads, bridges, and dams. He argues compellingly that natural features such as wetlands, rivers, and forests are equally pivotal in defining our infrastructural landscape. He has emphasized the importance of understanding how these ecosystems contribute essential services to society, thereby reinforcing the need for a holistic approach to engineering that acknowledges the intrinsic value of natural systems.

In a groundbreaking move, Dr. Nairn’s research has secured a new five-year, $3 million grant from the U.S. Army Corps of Engineers through their Engineering with Nature program. This funding will facilitate a comprehensive evaluation of the long-term benefits of integrating these natural systems into infrastructure planning. As the urgency for sustainable infrastructure becomes more pronounced due to climate change and aging constructions, this research aims not only to study natural infrastructure but also to quantify its advantages with empirical rigor.

Natural infrastructure offers a plethora of services that benefit communities, including improved flood control, enhanced water and air quality, and increased biodiversity. These benefits are often rendered in more sustainable and economically viable manners compared to traditional engineering solutions, such as concrete dams and levees. By examining the interplay between natural and engineered systems, Dr. Nairn aims to unlock a new paradigm of benefits that can arise from collaborative approaches rather than adversarial ones.

The novelty of this research lies in its methodological approach. Traditional engineering has often overlooked ecosystem monitoring and the quantification of the benefits provided by natural infrastructure systems. The new research under Dr. Nairn will focus on developing and deploying highly sophisticated tools and techniques to measure the ecological functions of these systems. The research plans to leverage cutting-edge technology, including unmanned aerial systems equipped with advanced sensors, to capture detailed environmental data.

Through these advanced methods, researchers can gather crucial information about local flora, such as the health of native vegetation, on incredibly intricate scales, down to centimeter-level granularity. This capability enables a more nuanced understanding of how plant communities interact with their environment, providing valuable insights into biodiversity conservation and carbon cycling processes. These technological advancements are integral to reshaping our perception of infrastructure and the role nature plays in enhancing societal resilience.

The concept of designing with nature is not a novel idea; civilizations have long recognized the benefits of integrating natural elements into their architectures, as evidenced by historical examples from the Hanging Gardens of Babylon to the use of turf roofs by ancient Norse settlers. However, the convergence of modern engineering principles with ecological insight has not been extensively explored until now. Renowned ecosystem ecologist H.T. Odum, in his seminal work, “A Prosperous Way Down,” called for a reevaluation of societal structures to align more closely with ecological principles, urging us to rethink our interactions with the environment.

The recent uptick in recognition of nature-based solutions is timely, especially as extreme weather events escalate and existing infrastructure systems show their limits. The growing advocacy for integrating natural infrastructure methods reflects a shift in political and economic support for more sustainable strategies in infrastructure development. Dr. Nairn’s research specifically aims to address systems within the Great Plains, including inland rivers, streams, and multipurpose reservoirs, aided by a scientific focus on quantifiable performance metrics.

To achieve meaningful advancements, the research will encompass a variety of methodologies, including field experiments and laboratory simulations. By generating temporally and spatially explicit data, Dr. Nairn aims to create a comprehensive understanding of how built environments and natural systems can coexist harmoniously. The outcomes of this work promise to foster a culture of resilience in engineering, ultimately paving the way for future generations to inherit infrastructure that works in concert with nature.

The urgency for this research cannot be overstated. As Dr. Dayton M. Dorman, a postdoctoral researcher in Dr. Nairn’s lab, highlights, the current landscape of U.S. infrastructure is at a crucial juncture where many systems are poised for replacement. The pressing question arises: do we persist with outdated methodologies, or do we allow dynamic natural solutions to inform and augment these failing constructs? Building resilience emerges as a primary objective of this investigation.

In conclusion, Dr. Nairn envisions a future where natural infrastructure takes its rightful place within the engineering toolkit, not as an afterthought but as a central component of planning and design processes. By harnessing the power of nature, we have the opportunity to craft a sustainable and prosperous trajectory for infrastructure development. The echoes of environmental stewardship, economic sustainability, and social equity resonate in his call for a profound paradigm shift: a move to work alongside nature rather than against it.

Subject of Research: Integration of natural infrastructure into engineering practices
Article Title: New Perspectives on Integrating Nature in Infrastructure Development
News Publication Date: October 2023
Web References:
References:
Image Credits: University of Oklahoma

Keywords

Applied Sciences, Natural Resources Management, Sustainability, Environmental Sciences, Engineering, Ecosystem Benefits, Natural Infrastructure Solutions, Climate Change Resilience.

At the core of this research lies the recognition that whistleblowers serve a pivotal intermediary role connecting the public, government agencies, and private enterprises. Traditionally, public participation has been championed for influencing infrastructure projects, with widespread evidence suggesting that citizen opposition can sway project trajectories substantially. However, unlike generic public actors, whistleblowers engage with a calculated rationality — balancing risks, rewards, potential losses, and the complexity of undisclosed factors — to decide whether to expose misconduct or environmental violations. This study advances beyond prior work by mechanistically modeling this decision-making process, capturing the strategic considerations that whistleblowers must weigh.

The model proposes a multi-factorial approach incorporating tangible elements such as financial rewards, the costs associated with supervision and reporting, probabilistic chances of misconduct discovery, government efficacy levels, and the indirect benefits whistleblowers might accrue. By interlinking these variables within a dynamic evolutionary framework, the research provides predictive insights into how whistleblower behaviors evolve over time and subsequently affect infrastructure project sustainability. Such fine-grained analysis offers stakeholders a powerful tool for anticipating shifts in oversight dynamics and improving environmental compliance mechanisms.

Integral to the model’s sophistication is its ability to simulate behavioral trends among rational whistleblowers under varying policy and operational conditions. For example, increasing rewards can incentivize proactive reporting, while elevated supervision costs or risks can deter whistleblowing activities, potentially allowing malpractices to flourish undetected. These interactions underscore the delicate equilibrium between fostering transparency and mitigating whistleblower vulnerability, a balance crucial for effective environmental governance in infrastructure undertakings.

One prominent implication emerging from the study highlights the indispensable role of government institutions in steering sustainable outcomes. By establishing rigorous performance evaluation systems that systematically track environmental compliance metrics—such as green project initiation rates, efficiency in environmental complaint resolution, and adherence to sustainability standards—governments can motivate public officials and departments to prioritize ecological stewardship. Reward mechanisms recognizing outstanding contributions, both materially and spiritually, could become vital levers for encouraging sustained commitment to environmental sustainability goals.

Complementing institutional reforms, the research advocates for a comprehensive, tiered reward scheme tailored specifically for whistleblowers. Such incentives would be calibrated according to the gravity of reported violations and the tangible environmental or social benefits observed following official intervention. Ensuring anonymous reporting channels fortified with digital identity encryption technologies could safeguard whistleblowers from retaliation, thereby fostering a climate of trust and activated participation. Furthermore, the proposal emphasizes stringent legal penalties—including criminal charges and corporate blacklisting—against any forms of harassment or privacy breaches directed at whistleblowers or their families, reinforcing the protective scaffolding necessary for ethical disclosures.

Public awareness also emerges as a critical element in advancing infrastructure sustainability. Educating citizens about the indispensable contributions of whistleblowers to environmental protection can galvanize societal support and cultivate a culture of environmental citizenship. Embedding this education within school curricula may nurture respect, empathy, and active engagement from an early age, laying a durable foundation for collective vigilance. Additionally, legal protections aimed at preventing employment discrimination against whistleblowers and offering job placement assistance can alleviate fears surrounding professional repercussions, encouraging more individuals to come forward without hesitation.

Beyond policy and social dimensions, the study underscores the strategic importance of technological innovation in augmenting environmental sustainability. Governments are encouraged to allocate increased resources towards research and development, particularly focusing on novel and emerging technologies with distinct capabilities for minimizing ecological footprints in infrastructure projects. Such advancements not only accelerate the shift towards green infrastructure but also bolster national innovation ecosystems, creating synergies that reinforce sustainable development paradigms.

The model’s design, however, carries inherent limitations. Due to space constraints, the study conducted a focused sensitivity analysis targeting a select few key parameters impacting strategic choices, inviting readers and practitioners to extend this analysis based on project-specific data. Recognizing that individual infrastructure projects exhibit diverse characteristics, the model enables tailored simulation runs that can predict evolutionary trends of environmental sustainability contingent upon localized variables. This modularity enhances the model’s applicability across varied infrastructural contexts, providing customized insights for decision-makers and project managers.

Looking forward, future research directions aim at employing a multi-case comparative methodology to rigorously investigate parameter value distributions across heterogeneous projects. Such endeavours will deepen understanding of the differential risks and challenges whistleblowers face in context-specific scenarios, refining the model’s predictive accuracy and policy recommendations. This trajectory promises to expand the versatility and real-world applicability of evolutionary game theory in safeguarding environmental integrity amid complex infrastructure ecosystems.

The integration of a rational whistleblower perspective into environmental sustainability models marks a paradigm shift in how oversight mechanisms are conceptualized and operationalized. By framing whistleblowers as strategic agents navigating a landscape riddled with uncertainties, incentives, and deterrents, this approach provides a nuanced lens for deciphering the subtle interactions shaping project outcomes. This breakthrough research equips stakeholders with actionable insights to design more robust supervisory systems that empower ethical vigilance, complementing traditional regulatory measures and amplifying collective efforts toward achieving greener infrastructure futures.

In a landscape where urbanization and infrastructure expansion continuously exert pressure on ecosystems, harnessing the latent potential of whistleblowers through informed policies and technological support can transform environmental governance from reactive enforcement to proactive sustainability. This study illuminates how targeted incentive structures, legal protections, and educational initiatives collectively create an enabling environment where whistleblower participation is not only safe but also recognized and valued as an indispensable pillar of ecological stewardship.

As governments worldwide grapple with the challenge of balancing rapid infrastructure development with environmental responsibility, embedding dynamic game-theoretic perspectives within policy frameworks can facilitate adaptive, evidence-based strategies. Such models equip decision-makers with predictive foresight into how stakeholder behaviors evolve in response to shifting institutional designs and external conditions, ultimately fostering resilience and sustainability in public-private partnerships.

The evolutionary approach presented also transcends static assessments prevalent in many traditional management models, embracing complexity and temporal dynamics that better mirror real-world conditions. This sophistication enables continuous recalibration of policies and incentive systems to maintain optimal encouragement for whistleblowers, thereby closing loopholes that may otherwise enable unsustainable practices to persist unchallenged.

The paper’s contribution lies not simply in theoretical innovation but in bridging the gap between abstract modeling and pragmatic policy design. By reflecting China’s current whistleblower supervision policies within its model, it offers transferable lessons for other nations aiming to refine their environmental oversight apparatuses in infrastructure sectors. The insights into whistleblower rationality, reward schemes, and protective legislation have broad applicability, marking a strategic template for global sustainability governance.

Overall, the fusion of evolutionary game theory with a rational whistleblower perspective opens vibrant pathways toward more inclusive, transparent, and effective environmental governance in infrastructure projects. As these frameworks gain traction among academics, policymakers, and practitioners, they hold the promise of shaping a future where infrastructure growth aligns harmoniously with ecological preservation and social justice imperatives, ensuring sustainable development for generations to come.

Subject of Research: Investigation of the dynamic evolution of environmental sustainability strategies in infrastructure projects through a novel evolutionary game model incorporating rational whistleblower behavior.

Article Title: Enhancing environmental sustainability of infrastructure projects through a novel dynamic evolutionary model: a rational whistleblower perspective.

Article References:
Xue, Y., Wang, G., Wu, Z. et al. Enhancing environmental sustainability of infrastructure projects through a novel dynamic evolutionary model: a rational whistleblower perspective. Humanit Soc Sci Commun 12, 1146 (2025). https://doi.org/10.1057/s41599-025-05480-w

Image Credits: AI Generated

The primary objective of the research at the NextGen Infrastructure Lab, which Behnood heads, is to create a new era of infrastructure that is both sustainable and resilient. The fundamental premise hinges on harnessing recycled materials and renewable resources while also minimizing costs across the board; this includes not just monetary expenditure, but also energy consumption and environmental impacts. Such advancements are crucial, especially considering the pressing challenges posed by climate change and urbanization that necessitate innovative approaches to infrastructure.

One specific area investigated in this study is asphalt pavement—a critical component of road infrastructure that often suffers from moisture-related deterioration. The research involved rigorous testing of various AI algorithms to delineate how effectively these systems could predict the performance of asphalt mixtures containing reclaimed asphalt pavement (RAP) materials. Given the harmful effects of moisture infiltration, which can compromise the integrity of asphalt and lead to severe distress, the stakes are high. This initiative aims to mitigate such risks by identifying material mixtures that can withstand wet conditions.

The findings of Behnood and doctoral student Abolfazl Afshin revealed that AI algorithms exhibited high precision in forecasting moisture damage within asphalt mixtures. These advancements offer contractors and engineers a viable means to optimize material selection strategically and mitigate the likelihood of pavement failure over its lifecycle. This capability could ultimately lead to significant reductions in maintenance costs, which in 2021 alone amounted to more than $206 billion for road upkeep across the United States.

The potential implications of such research are vast. Traditional empirical methods for determining suitable asphalt mixtures can be prohibitively time-consuming and expensive, often consuming considerable resources without guaranteeing satisfactory outcomes. In contrast, AI offers a streamlined, real-time analysis that can help avoid the labor-intensive trials and errors characteristic of conventional methodologies. As such, this represents not merely a methodological improvement but a radical rethinking of how civil engineers and urban planners can approach roadway construction.

Moreover, the application of AI extends beyond asphalt mixtures. Behnood underscores the capacity of AI and machine learning to transform various aspects of infrastructure, including the design of bridges and roads, waste management practices, and even railway fault detection. Each of these sectors stands to gain from enhanced predictive analytics, optimizing both resource allocation and operational efficiencies.

Another crucial aspect of infrastructure where AI can play a pivotal role is disaster management and risk assessment. As natural disasters become more frequent and unpredictable, efficient evacuation routes become critical. Behnood noted that AI could identify optimal pathways tailored to varied evacuation scenarios, thereby enhancing safety and reducing chaos during emergencies.

The expansive potential of AI application in civil engineering necessitates a collaborative approach. Behnood’s methodologies and insights may serve various stakeholders, including governmental bodies, private sector firms, and civil engineers aspiring to foster sustainable construction practices. This level of engagement could significantly hasten the adoption of AI-driven techniques across multiple sectors, facilitating heightened efficacy in infrastructure development.

As sustainability increasingly becomes a primary concern for urban planners and engineers, the use of advanced technologies like AI will be crucial in addressing these global challenges. The research headed by Behnood exemplifies the intersection of technology and civil engineering, illustrating how innovative methodologies can propel society toward a more sustainable future. This ongoing evolution represents a significant opportunity to reassess existing practices and explore new pathways for resilient infrastructure development.

Overall, AI’s potential to revolutionize infrastructure design and management cannot be overstated. As Behnood emphasizes, "There are so many examples of how we can use AI for sustainability in all elements of construction and infrastructure." The convergence of these technologies is poised to yield long-lasting benefits, from enhanced performance and durability in engineering materials to broader implications for public safety and environmental stewardship.

The implications of this research serve as a call to action for policymakers, engineers, and researchers to leverage AI and machine learning as pivotal tools in the sustainability arsenal. Indeed, the adoption of these cutting-edge technologies in infrastructure not only fosters economic viability but also emerges as a cornerstone for resilience in the face of environmental challenges.

To summarize, the marriage of artificial intelligence with civil engineering is not merely an advancement; it is an evolutionary leap forward. Insights gained from Behnood’s experimental methodologies can shape the future landscape of infrastructure while addressing pressing global challenges like climate change and resource depletion. As these technologies continue to mature and integrate into construction and engineering practices, society stands to benefit immensely.

Subject of Research: Application of Artificial Intelligence in Civil Engineering for Sustainable Infrastructure
Article Title: Prediction of Moisture Susceptibility of Asphalt Mixtures Containing RAP Materials Using Machine Learning Algorithms
News Publication Date: October 2023
Web References: International Journal of Pavement Engineering
References: US Department of Transportation report, Urban Institute Highway Expenditures
Image Credits: University of Mississippi

Keywords

Artificial Intelligence, Civil Engineering, Infrastructure, Moisture Susceptibility, Asphalt Pavement, Sustainable Construction, Machine Learning, Reclaimed Asphalt Pavement, Infrastructure Resilience, Predictive Analytics, Disaster Management, Road Maintenance.