The successful quality control and quality assurance of compaction operations are vital for the long-term performance of earth structures. Traditional in situ measurement methods are in practice for assessing compaction project specifications. These...
Intelligent compaction (IC) is a technology that uses non-contact sensors to monitor and record the compaction level of geomaterials in real-time during road construction. However, current IC devices have several limitations: (i) they are unable to v...
Intelligent compaction (IC) is an innovative and modified technology used for quality control in subgrade digital construction. However, current intelligent compaction measurement values (ICMVs) cannot provide accurate measurement of the filling laye...
The use of intelligent compaction (IC) in asphalt overlay includes the use of double-drum IC rollers, a roller measurement system, global position system (GPS) radio/receiver/base station, infrared temperature sensors, and an onboard computer reporti...
The limitations of conventional spot-sampling-based quality inspection in road construction can be effectively addressed by Intelligent Compaction (IC) technology. Acceleration signals acquired from the steel drums of vibratory rollers during the com...
Smart construction technology integrates artificial intelligence, Internet of Things, UAVs, and building information modeling to improve productivity and quality in construction. In road embankment earthworks, ground compaction quality is critical fo...
This study presents a rigorous approach for the extraction of the modulus of soil and unbound aggregate base materials for quality management using intelligent compaction (IC) technology. The proposed approach makes use of machine-learning methods in...
To provide a new method for the evaluation of the compaction quality of asphalt mixture, a real-time data acquisition and processing system (RDAPS) for the motion state of aggregate with a small volume and high precision is developed. The system cons...
Intelligent compaction (IC) has emerged as a breakthrough technology that utilizes advanced sensing, data transmission, and control systems to optimize asphalt pavement compaction quality and efficiency. However, accurate assessment of compaction sta...
Intelligent compaction (IC) technology have been used for quality control and quality assurance (QC/QA) in subgrade construction. The effective regression correlations between Intelligent Compaction Measurement Values (ICMV) and In-situ Measurement V...
The compaction quality of soil–rock mixture (SRM) subgrades critically influences infrastructure stability, but conventional settlement difference methods exhibit high spatial sampling bias (error > 15% in heterogeneous zones) and fail to ch...
In recent years, an intelligent vibratory roller with adjustable mode has become the leading direction for the development of compaction equipment that can obtain the state of the pressed material during the compaction operation and then control the...
To effectively control the deformation of high concrete face rockfill dams, this study proposes an intelligent prediction model (CO–SA–GPR) that integrates the Cheetah Optimizer (CO) and Simulated Annealing (SA) algorithm to optimize Gaus...
The criteria for measuring soil compaction parameters, such as optimum moisture content and maximum dry density, play an important role in construction projects. On construction sites, base/sub-base soils are compacted at the optimal moisture content...
Successful quality control and quality assurance (QC/QA) of earthwork compaction is critical to the long-term performance of roads, railways, airports, dams, and embankments. The purpose of this paper is to provide insights into the current practice,...
Vibratory rollers are mainly used for the near-surface compaction of granular media for a wide variety of construction tasks. In addition to the pronounced depth effect, vibratory rollers have offered the possibility of work-integrated compaction con...
During road construction, the accuracy of compaction work is critical for the structural stability and maintenance of the road. Although the plate load test (PLT) is commonly used for quality inspections, it is impractical to test every section due t...
A software for soil compaction analysis (SCAN) has been developed for evaluating the compaction states using the data from the GPS as well as a compactometer attached on the roller. The SCAN is distinguished from other previous software for intellige...
This work reports a master-slave separate parallel intelligent mobile robot for the fully autonomous transportation of pallets in the smart factory logistics. This separate parallel intelligent mobile robot consists of two independent sub robots, one...
Automated fibre placement (AFP) is a key process for manufacturing advanced polymer–matrix composite aerostructures; however, an uneven compaction-pressure distribution of tows during lay-up reduces the inter-laminar bonding strength and induce...
Currently, one of the topical areas of application of machine learning methods in the construction industry is the prediction of the mechanical properties of various building materials. In the future, algorithms with elements of artificial intelligen...
Self-compacting concrete (SCC) is an innovative building material having special properties such as increased flowability, good segregation resistance and compaction without vibration, etc. Despite the benefits of SCC over conventional concrete, ther...
To address the issues of vibration blind spots and the “black box” of quality control in the vibration process of precast beams caused by dense reinforcement zones and the arbitrariness of manual operation, this paper proposes the develop...
Research on the vibration of concrete mix is ushering in a critical opportunity for theoretical breakthroughs and construction innovations. This review aims to provide a systematic, data-driven overview of the research landscape of concrete mix vibra...
Pigeon-inspired optimization (PIO) is a new type of intelligent algorithm. It is proposed that the algorithm simulates the movement of pigeons going home. In this paper, a new pigeon herding algorithm called compact pigeon-inspired optimization (CPIO...
The theory of physical degrees of freedom (DoF) developed by Franceschetti–Migliore–Minero (FMM) establishes a fundamental phase transition in the singular-value spectrum of electromagnetic radiation operators under maximal rotational sym...
As artificial intelligence (AI)- or deep-learning-based technologies become more popular, the main research interest in the field is not only on their accuracy, but also their efficiency, e.g., the ability to give immediate results on the users&rsquo...
In the 2030s, a new era of gravitational wave (GW) observations will dawn as multiple space-based GW detectors, such as the Laser Interferometer Space Antenna, Taiji, and TianQin, will open the millihertz window for GW astronomy. These detectors are...
Reliable estimation of maximum dry density (MDD) is essential for compaction quality control of expansive soils. However, existing machine learning approaches mainly focus on overall accuracy metrics and rarely assess the reliability of individual pr...
The California bearing ratio (CBR) value of subgrade is the most used parameter for dimensioning flexible and rigid pavements. The test for determining the CBR value is typically conducted under soaked conditions and is costly, labour-intensive, and...
A compact electrohydraulic actuator (C-EHA) is an innovative hydraulic system with a wide range of applications, particularly in automation, robotics, and aerospace. The actuator provides the benefits of hydraulics without the expense and space requi...
Conventional and emerging paradigms of urbanism require new responses under the current circumstances, especially in relation to the integration of sustainability dimensions and technology advances. The escalating rate of urbanization, coupled with t...
Asphalt pavement has become a vital component of modern highway construction due to its high wear resistance, short construction period, economic viability, and excellent skid resistance. However, increasing traffic volume has heightened the structur...
This research deals with the critical issue of credit card fraud, a problem that has escalated in the last decade due to the significant increase in credit card usage, largely driven by advances in international trade, e-commerce, and FinTech. With g...
Everyday, a large number of complex scientific and industrial problems involve finding an optimal solution in a large solution space. A challenging task for several optimizations is not only the combinatorial operation but also the constraints of ava...
This study develops an interpretable machine learning framework for predicting the 28-day compressive strength of recycled aggregate concrete containing supplementary cementitious materials and validates it experimentally using metakaolin and spent f...
The compaction of asphalt pavement is a crucial step to ensure its service life. Although intelligent compaction technology can monitor compaction quality in real time, its application to individual asphalt surface courses still faces limitations. Th...
In order to provide a new method to study the migration behavior of coarse aggregates in the compaction process of asphalt mixtures, the “Intelligent Aggregate Attitude Acquisition System (IAS)” is developed based on 3D printing technology and wirele...
Very often, constructors and designers of intelligent building and building automation systems have a choice: to create a compact system with a limited configuration and modifying the system’s behavior possibilities or provide a fully configurable so...
Compaction quality of railroad subgrade relates directly to the stability and safety of train operation, and the core problem of the Intelligent Compaction of railroads is the transmission and evolution characteristics of vibration wave. Aiming at th...
With the advancement of intelligent compaction technology, real-time quality control has been widely investigated on the subgrade, while it is insufficient on asphalt pavement. This paper aims to estimate the real-time compaction quality of hot mix a...
Research on the dynamic characteristics of roadbeds has primarily focused on traffic loads and foundation treatment responses during the operation and maintenance phase. However, there remains a lack of in-depth exploration into vibration compaction...
The current evaluation models for earth-rock dam compaction quality seldom incorporate parameter uncertainty considerations. Additionally, the existing models frequently demonstrate constrained prediction accuracy and generalization capabilities. To...
Compaction quality control in earthworks and pavements still relies mainly on density-based acceptance referenced to laboratory Proctor tests, which are costly, time-consuming, and spatially sparse. Lightweight dynamic cone penetrometer (LDCP) provid...
Because of their simple design structure, end-to-end deep learning (E2E-DL) models have gained a lot of attention for speech enhancement. A number of DL models have achieved excellent results in eliminating the background noise and enhancing the qual...
The electric power equipment industry is rapidly advancing toward “informationization,” with the swift progression of intelligent sensing technology serving as a key driving force behind this transformation, thereby triggering significant...
This paper targets the area of optimizing machine learning (ML) training data by constructing compact data. The methods of optimizing ML training have improved and become a part of artificial intelligence (AI) system development. Compact data learnin...
Ballast compaction is a critical factor influencing ballast bed condition and the operational safety of heavy-haul railways. However, existing quantitative evaluation methods often suffer from overly idealized simulation models and limitations in sig...
Compaction quality governs asphalt pavement durability, but conventional density checks are intermittent. Reliable compaction control of asphalt mixtures requires real-time information on internal responses rather than relying solely on endpoint dens...
This paper proposes a physics-informed neural network (PINN)-based design optimization framework for a compact smart actuator motor in physical artificial intelligence (Physical AI) robotic systems, where artificial intelligence is integrated with se...
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