Construction Cost Research Articles

Achieving Housing Affordability in the U.S. through Sustained Use of AI and Robotic Process Automation for Prefabricated Modular Construction

The rising housing issues occasioned by high costs in the United States (US) are traceable to the high costs of building materials and construction. This study proposes the combined leveraging of AI and Robotic Process Automation (RPA) for prefabricated modular construction as a strategic means of reducing high costs of housing and increasing efficiency in construction. It argues that doing so would pave way for housing affordability in the US. Deploying descriptive survey and qualitative method alongside the applicable interpretive and descriptive techniques, the study demonstrates in the course of its analysis that AI and RPA are viable means of reducing costs of construction and housing, and increasing efficiency. It submits that amidst the established constraints to the ideal extent of leveraging AI for construction activities, the leveraging of AI and RPA for prefabricated modular construction yields huge positive results among which are reduced costs of construction and housing and increased efficiency in construction. Government and construction organizations are charged to play enabling roles in the adoption and sustainability of AI and RPA in construction activities, including prefabricated modular construction, so as to achieve reduced costs of housing and increase efficiency in construction.

A novel water‐in‐water emulsion drag reducer with instant solubility and viscosity enhancement for slickwater fracturing fluid

AbstractDrag reducers are indispensable components of slickwater fracturing fluids and play a pivotal role in the reconstitution of unconventional oil and gas reservoirs. Water‐in‐water emulsion (W/W) drag reducers have garnered significant attention owing to their rapid dissolution and environmentally benign properties. The solubility and viscosity enhancing ability of W/W drag reducers were further enhanced by synthesizing a novel W/W drag reducer through dispersion polymerization, thereby meeting the requirements of real‐time mixed fracturing construction technology. The solubility, viscosity enhancement, and synthesis state of the synthetic drag reducer were employed as evaluation criteria, whereby the synthetic systems underwent screening and optimization of the synthesis conditions. The final synthetic conditions were determined as follows: the monomer (AM and DMC) had a total mass concentration of 25 wt%, with an AM to DMC molar ratio of 95:5. The dispersion medium (sodium sulfate and sodium chloride) had a total mass concentration of 12 wt%, with a sodium sulfate to sodium chloride mass ratio of 1:2. The dispersion stabilizer PVP K60 had a mass concentration of 7 wt%. The initiator had a total mass concentration of 0.05 wt%, with an ammonium persulfate to sodium bisulfite mass ratio of 1:1. The reaction was conducted at 35°C and a stirring speed of 500 r min−1 for a duration of 8 h. The successful synthesis of the polymer was demonstrated using Fourier transform infrared spectroscopy. Environmental scanning electron microscopy and atomic force microscopy have characterized that the drag reducer has good viscosity enhancement potential. The performance evaluation results show that the solid content of drag reducer was 32.68%, and the residue content was 11.70 mg L−1. The viscosity enhancement rate of 1.3 wt% drag reducer was 93.7%. The dissolution time of 0.1 wt% drag reducer was only 25 s. The drag‐reduction rate of drag reducer reached 73.52%. Experimental results have proved that the drag reducer has the advantages of instant solubility, appreciable viscosity enhancement and drag‐reduction efficiency, fully meeting the real‐time mixing fracturing construction conditions, improving construction efficiency, and reducing construction costs. We expect that this study can broaden the application of W/W drag reducers in unconventional reservoir and provide a theoretical basis for field applications.

Features of mechanization of work during the construction of buildings using low-rise construction technologies

Currently, in Uzbekistan, the low-rise housing construction sector is in a stage of dynamic development and, as a rule, is aimed at developing the territories of suburbs and agricultural areas. First of all, the trend of growth in the volume of low-rise residential construction is due to the fact that the construction of low-rise buildings is much less expensive in comparison with the construction of high-rise residential buildings. In addition, the operating costs of low-rise residential buildings are significantly lower than high-rise ones, since there is no need to install expensive engineering equipment (elevator equipment, high-power pumping equipment, fire protection systems, etc.). State programs in the field of providing the country's citizens with affordable and comfortable housing provide for a comprehensive reduction in its sales value, which is primarily achieved by reducing the cost of construction, including by reducing the consumption of fuel and energy resources (FER) during the construction of buildings.

Simplification of Concrete Construction Processes and Rational Use of Eco-friendly Building Materials of BIM Technology in the Perspective of Renewable Energy

As the economy and society continue to grow quickly and as the people's living standards gradually rise, the share of building energy consumption in overall societal energy consumption will continue to rise. Sustainable standards need to be assigned top priority in the building business considering limited resources, impact on the environment, and socioeconomic limits. Additional materials are used to make concrete more sustainable. Several environmental, technological, and financial limitations make the selection of supplemental materials difficult. Building construction costs are capable of being decreased and global emissions of carbon can be reduced through the design optimization of concrete reinforced structures. Based on the above limitations, this paper proposes a new framework in BIM technology. This paper presents an approach for support of decisions that take criteria for sustainability related to social, technical, environmental, and economic aspects when ranking concrete supplemental content. The decision framework comprises the short listing of supplemental materials with technological and cost features based on the OSM, and the following use of ANP to prioritize the materials based on sustainable possibility order. By using the technical properties of every technically sound material utilized as concrete, the current study provides a decision support framework. Based on this, proposing a novel optimization strategy that considers both the structural topology and the optimization of specific components to build high-rise reinforced concrete buildings in a low-carbon and cost-effective manner. This technique first involves determining the optimal structural typology and afterwards optimizes the individual member sizes by using the OCLO algorithm. The suggested method is able to be expanded to optimize different building kinds with comparable issues, increasing the built environment's sustainable development and cost-effectiveness.

Optimization strategies for carbon neutrality in a maize-soybean rotation production system from farm to gate

Agricultural food production stands as a primary source of global greenhouse gas emissions, with residue management widely acknowledged as an effective avenue to achieve carbon neutrality. However, there is a lack of comprehensive assessment of the carbon footprint of agricultural residue production, processing, and recycling from farm to gate. Here we conducted a hybrid approach that integrated the DeNitrification-DeComposition (DNDC) model and life cycle carbon footprint to co-optimize water and residue management, targeting carbon neutrality and yield increase. The results revealed that controlled drainage with sub-irrigation (CDSI) served as a potent water management strategy to mitigate greenhouse gas emissions (15.65 %) while increasing yield (24.34 %) compared to free drainage. Regardless of the type of bioproduct, incorporating CDSI with downstream residue utilization exhibited substantial potential for carbon-negative emissions, reducing the average farm carbon footprint to −1538.15 kg CO2 eq yr−1. Among those scenarios, the CDSI with bioethanol scenario particularly stands out with its robust carbon mitigation capability (−1994.94 kg CO2 eq yr−1), driven by the enormous energy demand throughout the agricultural production process and the environmental friendliness of bioethanol, which substantially exceeds that of gasoline. However, challenges such as high plant construction costs and extended investment payback periods associated with residue conversion underscore the need for the urgent establishment of national subsidies and market mechanisms to foster carbon neutrality in agricultural production.

Reinforcement of Concrete Structures with High-Performance Fiber-Reinforced Concrete (HPFRC)

The incorporation of high quality fibers into very high strength concrete matrices leads to materials that are especially suitable to withstand extreme loads. For this reason, these materials are adequate for reinforcement and durability improvement of buildings and infrastructure constructions. The general objective of this work is to numerically study the flexural behavior of concrete structural elements reinforced with HPFRC. This general goal includes the analysis of the effect of the different variables, including the content and type of fibers, as well as the thickness of the reinforcement. The results of this analysis can contribute to improving the efficiency of the intervention techniques. For this purpose, numerical models are calibrated to reproduce the behavior observed in experimental tests carried out on HPFRC elements. Then the models are used to reproduce reinforced concrete beams reinforced with HPFRC under flexural loading. Finally, the effect of the aforementioned design variables on the behavior of reinforced beams is studied using the calibrated models. The results show the efficiency of the intervention increases with the fiber content and thickness of the reinforcement layer. However, the definition of the optimal design should also consider other criteria, such as constructional limitations and cost analysis.

Levelized Cost and Carbon Intensity of Solar Hydrogen Production from Water Electrolysis Using a Scalable and Intrinsically Safe Photocatalytic Z-Scheme Raceway System

The realization of an environmentally sustainable and widely-adopted hydrogen economy may require lowering hydrogen production costs of production pathways with ultra-low greenhouse gas emissions to $1/kg H2. The allocation of new or existing renewable electricity generation solely to hydrogen production remains contentious due to disputes regarding emissions accounting. Photoelectrochemical (PEC) hydrogen production technologies offer a unique solution, as hydrogen is produced directly from solar energy and water, without the need for electricity generation. However, cost projections for past photoelectrochemical designs have suggested that they are not cost competitive compared to conventional electrolysis systems manufactured at scale. Herein, we offer the first illustrative benchmark of cost and carbon intensity of hydrogen produced in a Type 2 Z-scheme photocatalytic reactor design that employs suspended semiconducting nanoparticles organized in two stacked baggies in a raceway design.To explore the near-term and future cost projection for hydrogen production via Type 2 photocatalytic Z-scheme raceways, the authors developed a bottom-up total installed capital cost model. This project cost model incorporates: 1) raceway reactor cost, derived from a Design for Manufacturing and Assembly (DFMA) process-based cost model, 2) mechanical balance of plant, including process equipment, piping, valves, and instrumentation, derived from equipment quotes, scaling, database values, and Aspen estimates; 3) electrical balance of plant, including wiring, derived from time and material cost correlations; 4) Site Preparation, focused on green field installation; and 5) Construction Overhead, including engineering, procurement, and construction (EPC) costs and project contingency. The capital cost model is fed into a Levelized Cost of Hydrogen (LCOH) discounted cash flow model that accounts for electricity and water consumption, in addition to other operating costs, including labor, maintenance, and raceway replacements.A hybrid life-cycle approach was used to develop an inventory of greenhouse gas emissions from all materials and energy flows associated with the facility life cycle. These flows are converted to emissions based on specific emission factors, or by using physical units-based input–output LCA models associated with the broader economic impacts of fuel and materials production, use, and end use.Estimates for levelized cost of hydrogen suggest that a 50 metric ton H2 per day (MTD) raceway plant can approach $2.50/kg H2 at an 8% solar-to-hydrogen efficiency with further cost improvements possible through increased performance and larger plant scales. Carbon intensity is estimated to be well under clean hydrogen targets for global warming potential of <2-4 kg CO2e/kg H2 produced. The results suggest a highly competitive and scalable technology, that justifies further experimental validation and prototyping in the field. Figure 1

In-Depth Study on the Application of a Graphene Platelet-reinforced Composite to Wind Turbine Blades.

Graphene platelets (GPLs) are gaining popularity across various sectors for enhancing the strength and reducing the weight of structures, thanks to their outstanding mechanical characteristics and low manufacturing cost. Among many engineering structures, wind turbine blades are a prime candidate for the integration of such advanced nanofillers, offering potential improvements in the efficiency of energy generation and reductions in the construction costs of support structures. This study aims to explore the potential of GPLs for use in wind turbine blades by evaluating their impact on material costs as well as mechanical performance. A series of finite element analyses (FEAs) were conducted to examine the variations of mechanical performances-specifically, free vibration, bending, torsional deformation, and weight reductions relative to conventional fiberglass-based blades. Details of computational modeling techniques are presented in this paper. Based on the outcomes of these analyses, the mechanical performances of GPL-reinforced wind turbine blades are reviewed along with a cost-benefit analysis, exemplified through a 5MW-class wind turbine blade. The findings affirm the practicality and benefits of employing GPLs in the design and fabrication of wind turbine blades.

Operational Planning and Design Considerations for Underground Logistics Transportation in Texas

The logistics transportation system is critical to the United States economy. Underground Logistics Transportation (ULT) is a class of automated transportation systems in which vehicles carry freight through pipelines and tunnels between terminals. Being able to use a part of the underground space of existing highways will greatly facilitate the construction of such pipelines and tunnels and reduce their construction costs. Underground Logistics Transportation (ULT) could be the answer to make freight transport more sustainable and competitive. Texas highways and railroads are expected to increase by nearly 207% from 2003 to 2030. Truck tonnage will grow by 251%, while rail tonnage is forecasted to increase 118%. The number of trucks carrying NAFTA goods will increase by 263%, and the number of rail units will grow by 195%. This will have a profound impact on the highway and rail systems. The objective of this paper is to present requirements and operational components for three types of ULT lines: standard shipping containers, a standard crate size, and a standard pallet size. This study examines the use of ULT as a mode of underground transportation with the help of three case studies. This research shows that ULT is financially viable, feasible, greener, cost effective, and can become an important part of intermodal freight mobility.

Multi-Objective Optimization of the Seawall Cross-Section by DYCORS Algorithm

The purpose of this research is to develop a new method for automatically optimizing the seawall cross-section with composite slopes and a berm, considering both overtopping discharge and construction cost. Minimizing these competing multi-objectives is highly challenging due to the intricate geometry of seawalls. In this study, the surrogate model optimization algorithm DYCORS (Dynamic COordinate search using Response Surface models) is employed to search for the optimal seawall geometry, coupled with the ANN (Artificial Neural Network) model for determining the overtopping discharge. A total of 20 trials have been run to evaluate the performance of our methodology. Even the worst-performing Trial 7 among these 20 trials shows a satisfactory performance, with a reduction of 17.67% in overtopping discharge and a 12.1% decrease in cost compared to the original solution. Furthermore, compared to other optimization schemes using GAs (Genetic Algorithms) with the same decision vectors, constraints, and multi-objective functions, the methodology has been proven to be more effective and robust. Additionally, when facing different combinations of wave conditions and water levels, there was a 27.8% reduction in objective function value compared to the original solution. The optimal results indicate that this method can still be effectively applied for optimizing the seawall cross-section as it is a general method.

Artificial Neural Network Application in Construction and the Built Environment: A Bibliometric Analysis

Over the past decade, there has been a dramatic increase in the use of various technologies in the Architecture, Engineering, and Construction sector. Artificial intelligence has played a significant role throughout the different phases of the design and construction process. A growing body of literature recognizes the importance of artificial neural network applications in numerous areas of the construction industry and the built environment, presenting a need to explore the main research themes, attributes, benefits, and challenges. A three-step extensive research method was utilized by conducting a bibliometric search of English language articles and conducting quantitative and qualitative analyses. The bibliometric analysis aimed to identify the current research directions and gaps forming future research areas. The scientometric analysis of keywords revealed diverse areas within the construction industry linked to ANNs. The qualitative analysis of the selected literature revealed that energy management in buildings and construction cost predictions were the leading research topics in the study area. These findings recommend directions for further research in the field, for example, broadening the application ranges of ANNs in the current Construction 4.0 technologies, such as robotics, 3D printing, digital twins, and VR applications.

Investigation of the effect of re-refined engine oil bottom on asphalt mixture performance and ecological implications

ABSTRACT This study explores the use of re-refined engine oil bottom (REOB) as an alternative to bitumen in asphalt mixtures for flexible pavement structures. REOB is considered due to its low cost, availability, large production volume, and eco-friendliness. This paper investigates the effects of adding 5, 9, and 14 wt% of REOB to neat bitumen on the asphalt mixture’s characteristics, mechanical behaviour, and ecological implications. The findings reveal significant reductions in indirect tensile strength by up to 51%, moisture resistance by up to 17%, rutting resistance by up to 79%, and cracking resistance at intermediate and low temperatures, especially when 14 wt% of REOB is added. While the heavy metal concentrations in both bitumen and REOB exceed permissible limits, the leached metal concentrations from the asphalt mixture remain within the safe range. Despite the potential environmental benefits of using REOB, the economic evaluations suggest that incorporating REOB into asphalt mixtures slightly increases the construction cost. Therefore, careful economic consideration should be performed for each project.

Experimental study on the pullout behavior of steel rebars in masonry shotcreted layer

Unreinforced masonry (URM) buildings are quite popular worldwide due to their low construction costs, despite being susceptible to significant damage even from moderate earthquakes. In many cases, reconstruction may not be the most viable option due to financial and time constraints. Among the available retrofit solutions, steel-reinforced shotcrete (SRS) proves to be a cost-effective, straightforward, yet effective method for repair/retrofitting. This paper presents the results of an experimental study aimed at evaluating the effects of various construction conditions on the rebar pullout resistance of steel-reinforced shotcrete used as a retrofit method for URM walls. To achieve this, a total of 46 full-scale URM specimens were manufactured and tested, each consisting of a one-sided 50 mm-thick shotcrete layer with a single 8 mm steel rebar. The variables examined included the condition of the URM surface before the shotcrete application (wet/dry, with/without finishing including plaster/scratched plaster/oil paint), the condition of the rebar surface (rusty/clean), the type of rebar (plain/ribbed), rebar cover in the shotcrete layer (20/25/30 mm), and the URM substrate temperature before application of shotcrete (20 °C/-16 °C). The results indicate that there is an increase in pullout resistance of the specimens under the following conditions: when the wall's finishing is removed, the wall's surface is wetted before shotcrete application, ribbed steel rebar is utilized, and the temperature of URM before shotcrete application is 20 °C, there is an increase in pullout resistance of the specimens by 58 %, 56 %, 32 %, and 13 %, respectively. Additionally, when the steel rebar cover is sufficient, ribbed steel rebar is utilized, and this rebar is rusted, there is an increase in pullout resistance of the specimens by 55 %, 10 %, and 6 %, respectively.

Utilisation of Coir Fiber as Reinforcement in M20 Concrete Mix

Sustainability is a wide accepted concept in modern construction scenario. Even though the construction industry is revolutionizing in a significant manner in terms of both equipment and materials used, the cost of construction has skyrocketed along with the deteriorative impact on environment. This resulted in the adoption of a more balanced approach with the environment as its nerve centre to create a better world to live in. This has led to the adoption of a natural fiber like Coconut for the strength enhancement in concrete. Concrete needs to be reinforced in order to improve its engineering qualities. Coconut fibers were employed for this study since they are widely accessible and come in big numbers. The study includes a comparison of the qualities of regular concrete and concrete reinforced with coconut fiber based on laboratory experimentation. Concrete with different fiber contents was evaluated with conventional concrete or prestressed concrete and different strengths parameters such as bending, compression and tensile strength of coconut fiber of length 25, 50, and 75 mm were added with proportions (0.5%, 1%, 1.5% and 2%) of total weight of the volume of concrete coconut fibre is carried out. The various strength aspects analysed are the flexural, compressive and tensile strength of the coconut fibre reinforced concrete.

Research on the Cost Control of Green Building Project Based on the Application of Renewable Energy

Promoting and optimizing green building projects based on renewable energy applications means that green building projects require more investment than traditional buildings. Green buildings using renewable energy are different from conventional construction cost control. Full-life cycle cost management is a way to analyze and manage the planning, construction, operation, maintenance, and residual costs of construction projects. It would be best if you had the law. This study uses mathematical models combined with relevant accounting theories and research methods to analyze the overall situation of green building cost control based on the application of renewable energy.

Assessing the Impact of Climate Comfort on Labor Productivity in Hydropower Engineering Construction in Southwest China

Labor productivity exerts a significant influence on the construction cycle and investment in hydropower projects. Consequently, it is a crucial factor in the estimation of the cost of hydropower project construction. The mechanisms that are modulated by subjective factors have been extensively studied. However, the assessment of labor productivity in objective environments with regular changes is usually considered using a single factor, especially in special environments where the influence of environmental factors is of greater concern. As the most extensive region of China’s water-energy resources, the Southwest region has a lengthy tradition of using altitude or oxygen as an inherent criterion for the assessment of labor productivity. However, the applicability of inherent standards is limited. Therefore, we tried to assess the spatial and temporal changes in labor productivity based on the changes in meteorological conditions in Southwest China, employing climate comfort indicators in this study. The result identified five distinct regions of climate change in Southwest China (R-I to R-V). In particular, there is minimal variation in labor productivity as assessed by climate comfort indicators and the elevation between R-I and R-II. R-III and R-IV are influenced by oxygen, temperature, and humidity, while R-V is affected by a multitude of factors. Our findings indicate that temporal and spatial variations in meteorological conditions can result in up to a threefold difference in productivity at the same altitude in different regions. Importantly, our study provides valuable theoretical insights for engineering project management. In particular, it can be concluded that altitude is not a reliable indicator for evaluating labor productivity in high-altitude construction.

Applicability and chemical mechanism of lightweight cement composite containing fly ash and sand for sustainable embankment

Lightweight embankment is an effective method for soft foundation treatment, while decreasing its cement usage can protect environment, save resource and reduce cost. This study aims to develop a lightweight cement composite (LC) containing fly ash and sand to provide guidance for filling the sustainable embankment. The chemical mechanism, micro-morphology, mechanical strength and workability of lightweight cement composites were evaluated through macro-micro tests, as well as life cycle assessment was performed to analyze the sustainability, and determine the optimal mixing ratio. The results showed that the moderate amount of fly ash was beneficial to enhance the mechanical strength of LC, while adding sand further improved its ductility, toughness, workability and sustainability. When the replacement rate of fly ash and sand were 10 % and 20 %, the energy absorption and fluidity of LC increased by 57 % and 7 %, and its ductility index, carbon emission and construction cost decreased by 34 %, 46 % and 35 %, respectively. Fly ash reacted with calcium hydroxide produced by cement hydration to generate more calcium silicate gels, which reduced the large pore of LC and improved its internal structure, while sand played a certain skeleton role.

Seasonal large-scale thermal energy storage in an evolving district heating system – Long-term modeling of interconnected supply and demand

Given the strong seasonal nature of heating demands, peak heat is important during colder seasons. Instead of peak heat plants, seasonal large-scale thermal energy storage (TES) could be utilized. These can be charged during warmer seasons and discharged when required, decreasing the need for peak heat plants. Systems modelling studies on seasonal TES are lacking. Thus, a long-term local energy system model is applied under different scenarios to investigate the potential roles of seasonal TES in an evolving heating system. The results show that seasonal TES is economically viable for: all future electricity price cases for low TES construction costs, corresponding to repurposing of underground oil storages, and for most electricity price cases for mid- and high construction costs, corresponding to new underground excavations. Seasonal TES mainly decrease the investments in and usage of electric boilers or biogas boilers, while increase the utilization of heat pumps. Other technologies may be affected depending on the future trajectory of electricity price developments. The size of the TES is between 3 and 7% of the annual district heating heat demand, depending on construction cost and electricity price development. The expansion of district heating into new housing is mostly unaffected by the availability of TES.

Real-time monitoring of disc cutter wear in tunnel boring machines: A sound and vibration sensor-based approach with machine learning technique

Large portions of the tunnel boring machine (TBM) construction cost are attributed to disc cutter consumption, and assessing the disc cutter's wear level can help determine the optimal time to replace the disc cutter. Therefore, the need to monitor disc cutter wear in real-time has emerged as a technical challenge for TBMs. In this study, real-time disc cutter wear monitoring is developed based on sound and vibration sensors. For this purpose, the microphone and accelerometer were used to record the sound and vibration signals of cutting three different types of rocks with varying abrasions on a laboratory scale. The relationship between disc cutter wear and the sound and vibration signal was determined by comparing the measurements of disc cutter wear with the signal plots for each sample. The features extracted from the signals showed that the sound and vibration signals are impacted by the progression of disc wear during the rock-cutting process. The signal features obtained from the rock-cutting operation were utilized to verify the machine learning techniques. The results showed that the multilayer perceptron (MLP), random subspace-based decision tree (RS-DT), DT, and random forest (RF) methods could predict the wear level of the disc cutter with an accuracy of 0.89, 0.951, 0.951, and 0.927, respectively. Based on the accuracy of the models and the confusion matrix, it was found that the RS-DT model has the best estimate for predicting the level of disc wear. This research has developed a method that can potentially determine when to replace a tool and assess disc wear in real-time.

Simulation of flow characteristics in open channels with inflatable dam

Abstract Inflatable dams are structure cylindrical inflatable and deflated bile structures made of rubberized material placed on top of a rigid base and inflatable by air, water, or a combination of both. The present paper aims to measure the water surface elevation, and depth of flow in Shatt Al Ibrahim and comparison with design depth and study the flow state according to design discharge and also according to scarce discharge. The study effect of the height of the dam filled with water on upstream and downstream water depth and analyzed numerically by using HEC-RAS program one–one-dimensional flow in two states, steady flow and unsteady flow under different variables such as changing of discharge. Good results were obtained in two flow states. The results show that the proper solution for maintaining the required water levels is to construct inflatable dams, due to lower construction and maintenance costs, easy and simple of operation, simple and easy to inflate and deflate quickly to prevent upstream flooding. The results of the current study indicated an increase in the water surface height (WS) and water depth (Wd) across the channel after the implementation of inflatable dams compared to natural conditions. Specifically, the data indicate a significant increase in (WS) and (Wd) at “station 52”, where (WS) increased by 0.45 m with a 0.5 m dam and 1.43 m with a 1.5 m dam compared to the basic scenario. This confirms the adaptability of inflatable dams in adapting water levels to real-time requirements, underscoring their potential as a cost-effective solution to mitigate upstream floods and improve water resource management practices.