Fast Construction Research Articles

Experimental research on H-section beam-square steel column joints connected by self-tapping screws

This paper proposes a novel thin-walled steel beam-column joint entirely using self-tapping screws. Compared to bolted and welded connections, its advantages of easy construction, low precision requirements, and fast construction are suitable for low-rise steel structures. Four full-scale H-section beam-square steel column joints connected by self-tapping screws were tested and the force transfer mechanism was investigated. Three of the specimens were loaded monotonically at the beam ends. The effects of the L-shaped connecting plate thickness and the arrangement of stiffening ribs on the bending performance of the joints are analyzed. Monotonic loading tests have demonstrated that the increased thickness and the arrangement of stiffening ribs enhance the common forces in the clusters of self-tapping screws, thereby increasing the bending stiffness of the joints. One of the specimens was tested with cyclic loads. The cyclic loading test revealed that the hysteretic curve of the self-tapping screws connection is relatively full, with high energy dissipation capacity and low degradation of strength and stiffness. Finally, the improved component method proposed the calculation method of bending resistance of self-tapping connection joints. The calculation accuracy is within 10 %, which can be used as a reference for the design of bending resistance.

Intelligent scheduling optimization of prefabricated components for assembly buildings

Prefabricated construction, as an emerging architectural model, has the characteristics of fast construction process and flexible design, and has been widely used in the field of architecture in China. As the core component of prefabricated buildings, the schedule of prefabricated components directly affects the progress and quality of the project. This study extends the volume of prefabricated components from a single building to a group of buildings, designs and solves an intelligent scheduling scheme model based on project construction schedule and procurement plan, and proposes two reference building group scheduling schemes and their applicable conditions. Genetic algorithm is used to optimize vehicle scheduling and transportation paths to achieve intelligent scheduling of prefabricated components in prefabricated building groups, ensuring project progress and quality.

WARM: A wavelet adaptive restoration module for surface anomaly detection

As a key component of lithium-ion batteries, surface defect detection of pole-piece is vital for quality control. Detection methods based on supervised have been used in pole-piece. However, the long cycle for data collection cannot meet the needs for fast construction and application of production line, making self-supervised a promising alternative. Although existing restoration-based methods have been widely studied, it’s still difficult to balance the problem of restoring normal regions and distinguishing abnormalities. We propose a Wavelet Adaptive Reconstruction Module by exploiting the obvious spatial and frequency differences between intra-class normal and abnormal features. Through training, the wavelet coefficients of the inputs are adaptively refined, potently obstructing the identity map from input image to restored image, thus improving the generalization of restoration network. The structure only consists of 2 simple Unets and WARM, it solves the anomaly detection task for pole-piece, and also outperforms other state-of-the-arts on MvTec AD.

Biometric identification on the cloud: A more secure and faster construction

Cloud-assisted biometric identification can benefit data owners with limited resources by offloading their storage and identification tasks to cloud servers with abundant resources. However, the adoption of this computing paradigm is hindered by security and privacy concerns. To solve the dilemma, several privacy-preserving cloud-assisted biometric identification protocols have been proposed. Nevertheless, the existing designs suffer from one or more of the following restrictions: (1) support only for data owner-online query, (2) low security level, and (3) inefficiency. Motivated by these challenges, this paper aims to explore a more secure and efficient construction. Concretely, we initialize the error weighted hashing (EWH)-based data packing technique to replace the time-consuming linear scan search during the identification process. Additionally, to ensure compatibility with the EWH-based search algorithm, we formulate an identity (id)-based scoring strategy and introduce a random split-based data encryption algorithm, which circumvents the costly homomorphic encryption scheme. Within the framework of the two non-colluding servers model, the random split-based one-time pad encryption guarantees provably indistinguishable security against chosen-plaintext attacks. Finally, since only simple hash and xor operations are involved, our novel construction exhibits significantly improved performance compared to prior designs, both in theory and in practice. This superiority is validated through rigorous theoretical analysis and extensive experimental evaluation.

Nickel(II)-Catalyzed Formal [3+2] Cycloadditions between Indoles and Donor-Acceptor Cyclopropanes.

This article describes the development of a nickel-catalyzed regio- and diastereoselective formal [3+2] cycloaddition between N-substituted indoles and donor-acceptor cyclopropanes to synthesize cyclopenta[b]indoles. Optimized reaction conditions provide the desired nitrogen-containing cycloadducts in up to 93% yield and dr 8.6:1 with complete regioselectivity. The substrate scope showed high tolerance to various substituted indoles and cyclopropanes, resulting in the synthesis of six new cyclopenta[b]indoles and the isolation of five derivatives previously reported in the literature. In addition, a mechanistic proposal for the reaction was studied through online reaction monitoring by ESI-MS, allowing for the identification of the reactive intermediates in the Ni(II) catalyzed process. X-ray crystallography confirmed the structure and relative endo stereochemistry of the products. This method enables the fast and efficient construction of fused indolines from readily accessible starting materials.

Deconstructable variable stiffness shear connectors in FRP deck resting on multigirder bridge system: Analytical model

Deconstructable structures offer great flexibility and reduce material waste. Fiber Reinforced-Polymer (FRP) decks resting on steel girders combine high durability, lightweight, fast construction, and deconstructablility. Composite action between the decks and girders is achieved using shear connectors. Until now, most shear connectors use adhesives or grouts, limiting their maintenance, reuse, or recycling. This paper presents a closed-form solution to analyze the behavior of an FRP deck connected to multi-girders using variable sequential stiffness shear connectors considering partial Degree of Composite Action (DCA). The analytical model, which is verified using Finite Element model and prior experimental studies, is further used to study stress and deflection for various multigirder configurations. Finally, the DCA considering variable stiffness shear connectors is presented and linked to effective width ratios, paving the way for adopting variable stiffness in bridge standards.

Analysis and design of pre-engineered industrial warehouse using IS: 800 and AISC

Pre-engineered construction is one of the new trend-setting technology globally, because of its suitability to the current era demands of fast and flexible construction, economical, sustainable, and ecofriendly construction. The analysis and design of pre-engineering buildings are also attracting the attention of design engineers. In this context, the design of an efficient and economical design is of prime concern. The present paper is an analytical study on the design and analysis of Industrial warehouses as per IS: 800-2007, and AISC design specifications. The analysis is executed under two different cases, out of which in one case optimal cross-sectional details are provided based on critical loading combinations of each code of practice. In other case, similar cross-sections were considered for both codes of practice. The critical load combinations and the locations of the maximum design forces in each case and the relative comparison of these between the two codal practices of IS:800 and AISC are discussed.

Forecasting maximum formwork pressure for self-compacting concrete using ARX-Laguerre machine learning model

Forecasting the maximum pressure exerted by cast-in-place self-compacting concrete (SCC) is a major concern for formwork designers, researchers, and site engineers to accurately design the bearing capacity of the formwork and control the casting rate for safe and fast construction. This article aims to utilize the ARX-Laguerre model, which is a data-driven model to forecast the maximum form pressure. A laboratory instrumented setup was used to cast a 2-m column using SCC made with two different types of cement. A pressure system consisting of four sensors was used to document the pressure during casting. The data were sent to the cloud at every 1-min interval for real-time monitoring. The data were used to develop the model. The results demonstrated that forecasting with the ARX-Laguerre model is highly accurate. The model can forecast the maximum pressure exerted by SCC with less complexity. The model performance was also found to be consistent with insignificant differences between actual experimental results and predicted results. With a recursive and straightforward representation, the resulting model, known as the ARX-Laguerre model, ensures the parameter number reduction. Providing fast prediction of the maximum pressure. The model enables formwork designers to forecast the form pressure to design safe formwork and also helps to control the casting rate when SCC is used.

Fast Impedance Spectrum Construction for Lithium-Ion Batteries Using a Multi-Density Clustering Algorithm

Effectively extracting a lithium-ion battery’s impedance is of great importance for various onboard applications, which requires consideration of both the time consumption and accuracy of the measurement process. Although the pseudorandom binary sequence (PRBS) excitation signal can inject the superposition frequencies with high time efficiency and an easily implementable device, processing the data of the battery’s impedance measurement is still a challenge at present. This study proposes a fast impedance spectrum construction method for lithium-ion batteries, where a multi-density clustering algorithm was designed to effectively extract the useful impedance after PRBS injection. According to the distribution properties of the measurement points by PRBS, a density-based spatial clustering of applications with noise (DBSCAN) was used for processing the data of the lithium-ion battery’s impedance. The two key parameters of the DBSCAN were adjusted by a delicate workflow according to the frequency range. The validation of the proposed method was proved on a 3 Ah lithium-ion battery under nine different test conditions, considering both the SOC and temperature variations.

Minor rotor tines and knives soil interaction. Total power calculation for minor rotor drive

Introduction. The problem of fast and high-quality road construction, when economic facilities and settlements are spatially separated, located at a considerable distance from each other, cannot be solved without the use of a complex of continuous units. An important element of the continuous unit forming the ditch and the unit for tunneling is the direct-flow rotary ripper. Current theoretical studies are not sufficient to calculate the interaction with the soil of the elements of a direct-flow rotary ripper. The lack of theoretical justification for the parameters of direct-flow rotary rippers hinders their use. Therefore, there is a need for theoretical research to identify the geometric, kinematic, dynamic and energy parameters of structural elements.The method of research. Methods for calculating the required power to drive the teeth, to separate the seam from the soil mass with knives and divide it into fragments, to overcome the inertia force of the incoming soil on two small rotor knives, to accelerate the soil towards the large rotor, to move the soil towards the large rotor, to overcome the friction force of the soil on the front surface of the knives have been developed. The total power required to drive the small rotor corresponds to the sum of the powers: for the introduction of a cone with a spiral knife into the ground, for the drive of the teeth and for the drive of the knives.Results. On the basis of the developed methods, the parameters were calculated. From the flat and spatial model of the forces of interaction with the ground of the elements of the small rotor, their resultant, their components, and normal forces are revealed. The friction force of the soil on the front surface of the knife is calculated. The total power for the drive of the small rotor and the volumetric energy for the introduction of the small rotor into the ground are calculated.Conclusion. The energy costs for driving small rotor knives include: energy for separating the reservoir and dividing it into fragments, energy for overcoming the pressure of the soil on the front surface of the knife, energy for accelerating the soil, energy for moving the soil, energy for overcoming the friction force of the soil on the front surfaces of the knives. The total energy cost of the small rotor drive includes the energy required to introduce the spiral knife cone, teeth and knives of the small rotor into the ground. As a result of the calculations, the power to drive the teeth of the small rotor is 735 W, the total power required to drive the small rotor is 2.2 kW. The volumetric energy for the introduction of a small rotor into the ground is 33.1 kJ / cubic meter.

High-throughput screening of catalytically active inclusion bodies using laboratory automation and Bayesian optimization

BackgroundIn recent years, the production of inclusion bodies that retain substantial catalytic activity was demonstrated. These catalytically active inclusion bodies (CatIBs) are formed by genetic fusion of an aggregation-inducing tag to a gene of interest via short linker polypeptides. The resulting CatIBs are known for their easy and cost-efficient production, recyclability as well as their improved stability. Recent studies have outlined the cooperative effects of linker and aggregation-inducing tag on CatIB activities. However, no a priori prediction is possible so far to indicate the best combination thereof. Consequently, extensive screening is required to find the best performing CatIB variant.ResultsIn this work, a semi-automated cloning workflow was implemented and used for fast generation of 63 CatIB variants with glucose dehydrogenase of Bacillus subtilis (BsGDH). Furthermore, the variant BsGDH-PT-CBDCell was used to develop, optimize and validate an automated CatIB screening workflow, enhancing the analysis of many CatIB candidates in parallel. Compared to previous studies with CatIBs, important optimization steps include the exclusion of plate position effects in the BioLector by changing the cultivation temperature. For the overall workflow including strain construction, the manual workload could be reduced from 59 to 7 h for 48 variants (88%). After demonstration of high reproducibility with 1.9% relative standard deviation across 42 biological replicates, the workflow was performed in combination with a Bayesian process model and Thompson sampling. While the process model is crucial to derive key performance indicators of CatIBs, Thompson sampling serves as a strategy to balance exploitation and exploration in screening procedures. Our methodology allowed analysis of 63 BsGDH-CatIB variants within only three batch experiments. Because of the high likelihood of TDoT-PT-BsGDH being the best CatIB performer, it was selected in 50 biological replicates during the three screening rounds, much more than other, low-performing variants.ConclusionsAt the current state of knowledge, every new enzyme requires screening for different linker/aggregation-inducing tag combinations. For this purpose, the presented CatIB toolbox facilitates fast and simplified construction and screening procedures. The methodology thus assists in finding the best CatIB producer from large libraries in short time, rendering possible automated Design-Build-Test-Learn cycles to generate structure/function learnings.

Fast and Automatic Parametric Model Construction of Antenna Structures Using CNN–LSTM Networks

Fast and Automatic Parametric Model Construction of Antenna Structures Using CNN–LSTM Networks

Fragility Assessment of a Long-Unit Prestressed Concrete Composite Continuous Girder Bridge with Corrugated Steel Webs Subjected to Near-Fault Pulse-like Ground Motions Considering Spatial Variability Effects

Prestressed concrete composite girder bridges with corrugated steel webs (PCCGBCSWs) are extensively employed in bridge construction because of their low dead weight, fast construction, and high prestressing efficiency. Moreover, PCCGBCSWs will experience deformation and failure of the corrugated steel webs, including steel fatigue and fracture, during earthquakes. These changes will introduce safety hazards, which can be addressed via bridge disaster prevention and mitigation. Because near-fault pulse-like ground motions (NFPLGMs) have high peak accelerations, these motions can easily cause damage to a bridge. Therefore, in this study, a seismic fragility assessment is performed for long-unit PCCGBCSWs subjected to NFPLGMs considering spatial variability effects, and a sensitivity evaluation of the seismic fragility is conducted considering girder type, bearing type, ground motion type, and apparent wave velocity to offer a point of reference for seismic design. The results show that PCCGBCSWs are less vulnerable than concrete bridges. The shock absorption effect of the friction pendulum bearing is better than that of the viscous damper. The impact of NFPLGMs on bridges is greater than that of near-fault non-pulse-like ground motions (NFNPLMs) and far-fault ground motions (FFGMs). The seismic fragility under nonuniform excitation conditions is greater than that under uniform excitation conditions, showing an increasing trend with decreasing apparent wave velocity.

Aerosol characterization and peculiarities of source apportionment in Moscow, the largest and northernmost European megacity

High population and a wide range of activities in a megacity lead to large-scale ecological consequences which require the assessment with respect to distinct characteristics of climate, location, fuel consumption, and emission sources. In-depth study of aerosol characteristics was carried out in Moscow, the largest megacity in Europe, during the cold period (autumn and winter) and in spring. PM10 chemical speciation based on carbonaceous matter, water-soluble ions, and elements was carried out to reconstruct the PM mass and evaluate the primary and secondary aerosol contribution. For the whole study period organic matter, mineral dust, and secondary inorganic/organic accounted for 34, 24, and 16 % of PM10 mass, respectively. PM10, OC, and EC approached a maximum in spring and decreased in winter. Mineral dust seasonal fraction increased from spring (17 %) to autumn (32 %), and then decreased in winter (22 %). Secondary inorganic aerosols (SIA) in opposite showed the maximum 27 % in winter. K+ marked the residential biomass burning in the region surrounding a megacity in spring and autumn, agriculture fires in spring. In winter primary aerosol contribution dropped down 56 % while secondary approached practically equal 44 %. Source factors with the relative contributions are quantified, namely city dust (26 %), traffic (23 %), industrial (20 %), biomass burning (12 %), secondary (12 %), and de-icing salt (7 %); they were significantly varying between the cold heating period and springtime. The relevance of sources to meteorological parameters and mass transportation is investigated by using both bivariate polar plots and Lagrangian integrated trajectory (HYSPLIT) model. Trajectory clustering demonstrates regional sources being crucial contributors to PM10 pollution. Aerosol speciation and source apportion factors identify the differences of the Moscow urban background among large European and Asian cities due to northern climate conditions, fast construction, long-range transport from industrial-developing area surrounding a city, regional biomass burning preferably in spring and autumn, and winter road management.

The role of advanced nuclear reactors and fuel cycles in a future energy system.

Nuclear power has been an important part of the US electricity system since the 1950s and continues to be a major source of low-carbon electricity today. Despite having low emissions, high grid reliability, and an excellent track record of safety, nuclear power also demands significant time and upfront capital to deploy, can struggle to compete economically with other generation sources, has intrinsic proliferation risk by relying on fissile material for fuel, and generates radioactive waste for which there are currently no disposal sites. Given the emissions and energy security benefits of having nuclear as part of the energy mix, advanced nuclear technologies have garnered significant interest and investment in recent years. Advanced reactor designs differ from the current operating fleet and have several potential advantages, including lower cost, faster construction, smaller size, inherent safety features, and lower waste yields. Yet, many challenges related to their deployment remain, and overcoming them will dictate whether or not new nuclear technologies become a material element of the future energy infrastructure. This article synthesizes the opportunities and barriers to deploying advanced nuclear reactors and their associated fuel cycles as described in two National Academies consensus reports. It highlights the consensus recommendations that could allow these new technologies to reach commercial success as part of a long-term decarbonization strategy.

Construction quality control of concrete structures in architectural engineering—A case in Shanghai, China

<p>Architectural concrete provides diverse patterns, colors, and forms, offering extensive structural and aesthetic possibilities. In China, advanced techniques such as prefabricated and precast concrete structures are increasingly utilized, delivering benefits like faster construction, reduced resource use, and improved quality control. Recent studies in China have highlighted the environmental benefits and practical considerations of incorporating recycled materials and moderate-heat Portland cement into concrete, which offer promising sustainability advantages. This study, through a case analysis in China, explored the usability, durability, manufacturing costs, and economic implications of architectural concrete. It emphasizes the critical role of architectural concrete in modern structural engineering, financial planning, and design, aiming to reduce variability in strength and uniformity between concrete batches, ensure consistent material quality, and lower maintenance costs while accelerating production. Focusing on quality control in concrete construction in Heqing, Pudong, Shanghai, this research identified unique challenges and provided insights. In Shanghai's architectural context, continuous monitoring of concrete quality is essential for structural stability and durability. This study also addressed the resilience of concrete structures in saltwater and freeze-thaw conditions, underscoring the need to consider environmental factors in quality assurance. Laboratory experiments demonstrated that composite members and deep beams of steel and concrete exhibit notable deformation and shear resistance, highlighting the importance of meticulous material selection and structural design for effective quality control.</p>

Fast Construction of Measurement Matrix and Sensing Matrix with Dual Adaptive Cross Approximation

Fast Construction of Measurement Matrix and Sensing Matrix with Dual Adaptive Cross Approximation

Transfer learning of hyperparameters for fast construction of anisotropic GPR models: design and application to the machine-learned force field FFLUX.

The polarisable machine-learned force field FFLUX requires pre-trained anisotropic Gaussian process regression (GPR) models of atomic energies and multipole moments to propagate unbiased molecular dynamics simulations. The outcome of FFLUX simulations is highly dependent on the predictive accuracy of the underlying models whose training entails determining the optimal set of model hyperparameters. Unfortunately, traditional direct learning (DL) procedures do not scale well on this task, especially when the hyperparameter search is initiated from a (set of) random guess solution(s). Additionally, the complexity of the hyperparameter space (HS) increases with the number of geometrical input features, at least for anisotropic kernels, making the optimization of hyperparameters even more challenging. In this study, we propose a transfer learning (TL) protocol that accelerates the training process of anisotropic GPR models by facilitating access to promising regions of the HS. The protocol is based on a seeding-relaxation mechanism in which an excellent guess solution is identified by rapidly building one or several small source models over a subset of the target training set before readjusting the previous guess over the entire set. We demonstrate the performance of this protocol by building and assessing the performance of DL and TL models of atomic energies and charges in various conformations of benzene, ethanol, formic acid dimer and the drug fomepizole. Our experiments suggest that TL models can be built one order of magnitude faster while preserving the quality of their DL analogs. Most importantly, when deployed in FFLUX simulations, TL models compete with or even outperform their DL analogs when it comes to performing FFLUX geometry optimization and computing harmonic vibrational modes.

Study on Elevated Interval Evacuation of Metro Train considering the Influence of Fire, Railings, and Track Bed

Elevated metro is a typical type of urban rail transit that operates on viaducts. Due to its fast construction speed and low cost, it plays an important role in transportation systems with dense concentrations of people. Once a fire accident occurs in rush hour, it will cause high casualty and enormous injuries. In this regard, studying the characteristics of fire smoke spread and passengers’ evacuation is of profound significance. In this paper, Pyrosim and Pathfinder software was utilized to simulate metro fire and evacuation process. The variation of temperature, CO concentration, and visibility inside carriage and outside walkaway were studied to explore the characteristic of fire and smoke. Evacuation time, speed, density, and path were analyzed for six cases considering the influence of railing settings on evacuation walkaway and the use of track bed. The impact of smoke on movement speed reduction and temperature on the available door numbers were taken into consideration. Results revealed that the temperature of accident carriage rose to tenability limit after 50 s and the visibility decreased to 5 m within 150 s. CO concentration was below safety criteria due to sufficient oxygen. Temperature was the most important factor that leads to the risk of evacuation, especially inside the accident carriage. The length of evacuation walkaway could highly reduce evacuation time and density. Railings had a negative impact on evacuation while the usage of track bed had a positive effect. Besides, the impact of railings was not as significant as the usage of the track bed. Research results can provide decision‐making reference for fire protection and evacuation design to alleviate congestion and improve safety management.

Iodine-dependent oxidative regioselective aminochalcogenation of indolines.

A directing-group-free strategy for oxidative regioselective aminochalcogenation of indolines with amines and dichalconides is presented. This strategy combines tandem coupling sequences and oxidative dehydrogenation methods in a multi-component reaction, enabling the fast construction of a series of C2,3- or C2,5-aminochalcogenated indole derivatives. Moreover, the application of this synthetic approach is demonstrated through the late-stage modification of pharmaceuticals and the derivatization of the products, highlighting its potential and significance.