Large Steel Research Articles

Construction Technology of Steel Structures in Large Public Buildings

With the continuous development of the Chinese economy and the rapid development of large public buildings, the application of steel structures in large buildings is gradually increasing. The use of steel structures is crucial for meeting the needs of large-span, super high-rise buildings, rapid construction, and achieving sustainable development of buildings. Therefore, studying and analyzing the construction technology of large-scale building steel structures has important practical significance. This study is based on a library construction project, focusing on the installation of embedded bolts, steel columns, steel beams, and high-strength bolts in the construction of large building steel structures, as well as the technical schemes and construction processes of welding, anti-corrosion coatings, and fireproof coatings. I hope to provide reference and suggestions for actual construction.

Splice Length of Large Diameter Reinforcing Bars in Ultra-High-Performance Concrete

Potential exists for construction time savings through replacement of cast-in-place substructure columns, piers, or both, with prefabricated bridge elements and systems. Cast-in-place substructure construction requires forming, placing steel, and pouring concrete at the construction site. Using prefabricated elements would decrease the extent of work required at the site and potentially reduce concrete curing time. This research furthers the effort to use ultra-high-performance concrete (UHPC) as a joining material for prefabricated bridge substructure elements. UHPC has a high early strength, requires less development or splice length than conventional concrete, and has been used previously for accelerated construction projects, such as bridge deck replacement with precast units. UHPC also has a discontinuous pore structure that reduces liquid ingress, significantly enhancing durability compared to conventional concrete. Although UHPC has been researched extensively, previous research for reinforcing bar splice and development lengths has focused on #9 and smaller diameter bars. Typically, larger diameter bars are used for substructures. This research determined the required splice lengths for large diameter steel deformed reinforcing bars embedded in UHPC based on 127 individual tests. Three primary variables were included in the testing matrix: bar size, bar spacing, and concrete cover. To achieve at least 75 kips per square inch (ksi) (517 MPa) reinforcing bar stress in UHPC with an early age strength of 14 ksi (97 MPa), the required embedment length ranges from 8 to 13 times the bar diameter and the corresponding splice length varies from 6 to 11 times the bar diameter, depending on the bar size and concrete cover.

Impacts of Carbon Border Adjustment Mechanism on the Development of Chinese Steel Enterprises and Government Management Decisions: A Tripartite Evolutionary Game Analysis

Upon the implementation of the European Union Carbon Border Adjustment Mechanism (CBAM), substantial challenges are anticipated to impact the international trade of Chinese steel products. To safeguard the competitiveness of Chinese steel products on the global stage, this paper establishes a tripartite evolutionary game model, involving large steel enterprises, small- and medium-sized steel enterprises, and the government. The model integrates collaborative emission reduction and free-riding benefits among enterprises, along with the government’s dynamic subsidies and penalties. First, we calculate the replicator dynamic equations and conduct stability analysis to obtain the evolutionary trends and system equilibrium points in different phases of the CBAM. Then, we validate the evolutionary theoretical analysis of the model through example simulation analysis. Finally, we explore the impact of different parameters on the agents through a sensitivity analysis of parameters. The findings indicate that (1) large enterprises demonstrate greater sensitivity to CBAM, making their production structures more susceptible to changes in CBAM policies; (2) small- and medium-sized enterprises are more prone to free-riding behavior influence; (3) government intervention should be kept within appropriate boundaries, as excessive intervention may lead to strategic oscillation, with passive management being chosen by the government during the strengthening phase of CBAM; (4) elevating the price in the Chinese carbon market would slow down the structural changes in the production of Chinese steel enterprises, serving as an effective measure to counteract the impacts of CBAM. This paper provides theoretical support for how steel enterprises and the government can respond to CBAM, aiding stakeholders in selecting optimal strategies during different implementation stages and mitigating the impacts of the CBAM to the maximum extent possible.

Influence of test methodology on the characterization of the parallel-to-grain timber embedment strength and foundation modulus of dowels

ABSTRACT A reliable determination of the embedment strength and foundation modulus of timber elements is critical for the design and safety assessment of joints in timber structures. However, the existence of various test configurations for characterising the embedding properties of large diameter steel fasteners in timber elements poses challenges in directly comparing and utilising available test data. This paper aims to provide an insight into the influence of embedment property test methods, comparing experimental results from different test setups within the guidelines of the EN 383 and ASTM D 5764-97a standards for European softwood species, Scots pine wood (Pinus sylvestris) and Norway spruce (Picea abies). In addition to the test guidelines, the thickness of the specimen and the application of the load was evaluated within the protocols. A comprehensive statistical analysis was performed to identify statistically significant differences between the groups evaluated. The results of the analysis revealed disagreement between the standards in the evaluation of the strength of the embedding, highlighting the potential bias inserted by the experimental setup and protocol. Furthermore, it was proven that the thickness of the specimens influences both the embedding strength and the foundation modulus of the wood species tested. Finally, no distinctions were observed between tensile and compressive loading within the guidelines of the EN 383 standard.

Vision‐based robust missing and loosened bolt detection for splice plate joints

SummaryVision‐based bolt defect detection methods based on feature changes have been reported. However, the robustness of key feature extraction and bolt detection requires improvement. This paper proposes a robust missing and loose bolt defect detection approach. The key features—reference points for perspective correction and the straight lines of the bolt edges—are extracted from the masks obtained by semantic segmentation models. The true and false bolt discrimination approach based on the mask shape can help improve bolt object detection accuracy. Overlapping between the bolt bounding boxes in the reference and detection images indicates missing bolts. The rotation angles reveal loosened bolts. The proposed approach was tested on fabricated bolted joint specimens and a steel railway bridge. The results suggest that these improvements ensure defect detection accuracy, with a miss rate of only 1% for missing bolt detection. Moreover, a loosened bolt with only 3° rotation is successfully detected. This approach has promising potential applicability in automatically detecting bolt defects in large steel structures.

Investigation of shear response due to variation of fiber volume fraction, transverse steel, and placement method on short span R/UHPC beams

This study investigates the response of small-scale, reinforced ultra high performance concrete beams. Seven specimens were cast and experimentally tested. Steel fiber volume fraction, amount of longitudinal and transverse steel reinforcement, and casting direction varied between specimens. High longitudinal reinforcement ratios of 4.1% and 9.5% were expected to drive relatively large shear demands and low steel fiber volume fractions of 0.5% and 1% were expected to decrease the UHPC’s ability to resist tension, shear, and compression. Specimens were either cast at one end or mid-span. All specimens failed in shear, as expected. R/UHPC beams with only 0.5% fibers and a stirrup spacing equal to half the beam’s depth carried more ultimate load than beams with 1% fibers and twice the stirrup spacing. At a 0.5% fiber volume fraction, UHPC performed well, exhibiting fiber bridging in tension and resisting spalling in compression. As longitudinal reinforcement ratio increased from 4.1% to 9.5%, load carrying capacity generally increased, but not proportional to the increase in steel. Placement method did not influence fiber orientation in the R/UHPC beams when measured in 2D planes transverse or longitudinal to the specimens’ major axis. The longitudinal and transverse reinforcement interrupted fiber flow and prevented significant fiber alignment; combined with the short span of the beams, these factors mitigated the influence of placement method.

Numerical Simulation and Application of Radial Steel Gate Structure Based on Building Information Modeling under Different Opening Degrees

The safe and stable operation of the radial gate is highly essential for hydropower stations. As the dynamic load of gate, water flow generally causes the irregular distribution of strength, stiffness, and the stability of the gate structure. Traditional simulation technology is usually used to investigate the impact of water flow on gate structure; however, there is a lack of integration and interaction of building information modeling (BIM) and numerical simulation technology to study this issue. Therefore, this paper proposed a computational framework combing BIM and numerical simulation to calculate and analyze the large complex hydraulic radial steel structure. Firstly, the 3D model of the radial gate was established by MicroStation2020, then, the finite element model was output by using it. Secondly, the change laws of strength, stiffness, and stability of the radial gate were analyzed by Ansys-Workbench2020R2 under different opening degrees. The numerical simulation results show that the maximum equivalent stress value was 142.19 MPa, which occurred at the joint between the lower longitudinal beam and the door blade. The maximum deformation was 3.446 mm, which occurred at two longitudinal beams’ middle in the lower part of the panel. When the opening degree is 0.0 m–9.0 m, the natural vibration frequency increases irregularly with the increase in the opening of the gate. Three main vibration modes of the gate vibration were obtained. It proves that it is feasible to analyze the structural performance of radial gates by using BIM and numerical simulation. Finally, the BIM and numerical simulation information management process was established to make the simulation results more valuable. This study expands the application value of BIM and provides a new research idea for large complex hydraulic steel structural analysis. The information management process described in this research can serve as a guide for gate operation and maintenance management.

Nudging safety behavior in the steel industry: Evidence from two field studies

The practice of nudging received much attention in different domains of human behaviour (e.g. finance, health, traffic safety and sustainability), but its relevance has not been systematically investigated for safety in the process industry. This study aimed to investigate the effectiveness of nudge interventions in promoting safety behavior in the steel industry through field experiments in a large steel plant, particularly in relation to gas hazards and falling from stairs The results of both experiments showed that the nudge interventions were very effective in promoting safety behavior among workers. An icon reminding of the gas dangers on work jackets effectively increased gas detector compliance, while hand print cues were able to promote workers holding onto handrails. Related organizational implications for a safety nudging approach are discussed. Overall, these findings suggest that nudge interventions can be a cost-effective approach to promote safety behavior in the steel industry. The suggested nudge framework should be implemented as part of a holistic safety approach to promote safety behavior among workers and prevent severe accidents.

Mathematical model for bale-density prediction in large steel roller-type round balers during bale rolling

To realize the intelligent production of straw bales and improve their economy, the density of straw bales in the working process of large-scale steel roller-type round balers must be measured in real time. Therefore, this study analyzes the forces acting on steel rollers and bales in the bale rolling process, constructs a mathematical model to predict the density of molded bales, and proposes a method for dynamically measuring the density of bales in a round bale machine. Sunflower straw was selected as the test material, and a bale density model validation test was conducted at a test stand. The results showed that the accuracy of the measured bale density of the data acquisition system ranged from 93% to 97%, verifying that the mathematical model for bale density prediction had good accuracy. This study provided an effective strategy for round baler design.

High Resolution Emission Inventory of Greenhouse Gas and Its Characteristics in Guangdong，China

Based on the typical city survey data and statistics of Guangdong Province， a 2018-based 3 km×3 km gridded greenhouse gas emissions inventory was developed for Guangdong Province using the combination of top-down and bottom-up emission factor methods. The inventory covered the CO2， CH4， and N2O emissions from energy， industrial processes， agriculture， land use change and forest， waste management， and indirect sources. The results showed that estimates for CO2， CH4， and N2O in Guangdong Province for the year 2018 were 8.5×108， 1.9×106， and 1.1×105 t， respectively， and 8.5×108， 4.0×107， and 3.4×107 t by equivalent carbon dioxide， totaling 9.2×108 t. CO2 was the main greenhouse gas in Guangdong Province， accounting for 92.0% of the total emissions. Energy and indirect sources were the main emission sources， accounting for 77.9% and 7.6%， respectively， totaling 85.5%. Spatial distributions illustrated that most grids were greenhouse gas emissions， whereas some others were greenhouse gas sinks； the greenhouse gas emissions were distributed mainly in the Pearl River Delta region and had certain characteristics of distribution along the road network and channels. The greenhouse gas grids of high emission were mainly the locations of high energy-consuming enterprises such as large power plants， steel mills， and cement plants.

Predicting mechanical properties lower upper bound for cold-rolling strip by machine learning-based artificial intelligence

The mechanical properties serve as crucial quality indicators for cold-rolled strips. For a long time, the mechanical properties mechanism and data-driven models can't comprehensively consider sufficient factors to achieve high-accuracy prediction due to the "data-isolated island" between production lines. In this research, we introduce a multi-process collaborative platform based on the industrial internet system. This platform is designed to enable real-time collection of diverse and heterogeneous data from both upstream and downstream processes of cold rolling. On this basis, a novel mechanical properties interval prediction model is proposed using the sparrow search algorithm to optimize fast learning network under the LUBE framework. We trained the model by using a dataset collected from a large steel plant. Based on the rolling theory and Pearson correlation coefficient, 25 features are selected as the inputs of the prediction model. The experimental results and comparison show that the proposed model is feasible and outperforms other machine learning models, such as the artificial bee colony algorithm optimized extreme learning machine and back propagation neural network model.

The Influence of Natural and Anthropogenic Environmental Pressures on European Eel Abundances in French Estuaries

The aim of this study was to investigate the influence of environmental characteristics and anthropogenic pressures on the abundance of estuarine European eels (Anguilla anguilla L.) during their continental growth phase. European eels were collected with fyke nets from spring to autumn in twenty-nine estuaries along the French English Channel and the Atlantic coast. Eel abundance (catch per unit effort, CPUE) was assessed for all eels and by size class for small (total length < 300 mm), intermediate (≥300 to <450 mm), and large (≥450 mm) eels. The environmental characteristics of the French estuaries were described by twelve descriptor variables, mainly related to hydro-morphological and sedimentary factors. Based on principal component analysis and hierarchical clustering analysis, estuary size was identified as the main explanatory variable and used to compare eel abundance. Eel abundance differed significantly according to estuary size, with higher abundances observed in small estuaries (7.22 to 13.00 ind. fyke nets 24 h−1) compared to large estuaries (0.13 to 0.71 ind. fyke nets 24 h−1). Spatial variation in eel abundance was correlated with differences in estuary size for all eel size classes. The influence of anthropogenic pressures on eel abundance was assessed by nine anthropogenic estuarine pressure indicators. The results indicate that high values of the anthropogenic pressure indicators were correlated with low eel abundance. This study highlights that large French estuaries subject to stronger anthropogenic pressures were less favourable habitats than small estuaries with less anthropogenic pressure.

Study on copper-stainless steel explosive welding for nuclear fusion by generalized interpolated material point method and experiments

The thick copper stainless steel composite plate is an important component of the cooling coil terminal box of international nuclear fusion reactors. The composite rate, tensile strength, shear strength, and interface waveform of the metal plate are also far higher than the requirements of conventional explosive welding technology. It is difficult to obtain the best technical process parameters in a short time solely relying on conventional explosive welding tests. In order to solve the above-mentioned technical difficulties in explosive welding, this article applies the generalized interpolation material point method (GIMP) based on the explosive welding window, metal elastic-plastic mechanics, and explosive detonation theory to conduct macroscopic three-dimensional and microscopic two-dimensional numerical simulations of the copper stainless steel explosive welding process and the composite interface wave formation process, respectively. The experimental results demonstrate that the GIMP has significant advantages in numerical calculation and analysis for the explosive welding problem of high-speed impact collision of metal plates driven by explosive detonation, and it can effectively solve the technical problems of high technical specifications, low explosive processing composite rate, and low interface strength of large thickness copper stainless steel composite plates used in nuclear fusion.

Extraction of Feature Information from Point Cloud of Large Volume Steel Truss Members

In order to address the issues pertaining to the subjective nature and limited precision associated with selecting feature points in the point cloud of a large steel truss structure, this study proposes a batch automatic extraction approach for identifying key feature information, including boundaries, corner points, and bolt holes of large steel truss components. This method relies on the nested application of established processing algorithms such as Euclidean clusters, regional growth clusters, and random sampling consensus. In addition, a novel approach is suggested for validating the precision of feature information extraction through the utilization of standard theoretical models. The results of the experimental and large-scale lower chord tests demonstrate that our approach is not dependent on specialized software, exhibits excellent efficiency, and possesses an acceptable degree of automation. The findings of this study can provide accurate data support for reverse modeling, virtual trial assembly, and dimensional inspection of steel truss components.

Daily Load Forecasting and Data-Driven Strategies for Steel Industry Based on Random Forest Modeling

Abstract As a large power consumer, the iron and steel industry urgently needs to improve productivity, reduce energy consumption, and save costs by revolutionizing energy management. In this study, we design a power demand management system for the iron and steel industry, and around the load management module, we propose a data-driven strategy based on daily load situational awareness and introduce the random forest model into daily load forecasting in the iron and steel industry. At the same time, the projection principle is applied to improve the traditional gray correlation similar day selection algorithm, and a combination method of daily load forecasting based on the gray projection improved random forest algorithm is proposed. The electric load data of the iron and steel industry in a specific region is utilized as an experimental sample to investigate the model’s forecasting performance and the impact of the data-driven strategy. The model for daily load forecasting in this paper has an average relative error of 1.18%, which is better than other models. The application of the data-driven strategy brought about 6.99% and 6.69% reductions in load demand and basic electricity cost. The data-driven strategy for the steel industry based on the Random Forest model can predict electric loads more accurately and reduce energy costs, as shown by the results.

Use of equivalent interface samples during fracture mechanics investigations for the design of adhesively bonded composite reinforcements on steel structures

During an international Joint Industry Project called SBO (Strength Bond Offshore), a design strategy of adhesively bonded composite reinforcements for steel structures was developed and assessed. It relied on the use of fracture mechanics. Yet, an adaptation of the characterization tests was needed to reduce the number of samples while remaining representative of the studied reinforcement. This adaptation was called “equivalent interface samples”.This paper aims at presenting the proposed adaptation of fracture mechanics tests for mode I, mode II and mixed mode, and its use during the design strategy. First, the geometry of the samples will be presented. Then, the obtained results during the fracture mechanics experimental campaign will be introduced. Those investigations relied on the use distributed optical fiber sensor to monitor the crack propagation during the tests. The obtained toughness characterizations allowed us proposing a design strategy that was assessed in regards with experimental tests conducted on large size steel samples reinforced with adhesively bonded composite.

A fronteira do carvão: siderurgia e floresta em Minas Gerais (Brasil) no século XX

Abstract Focusing on the charcoal-fired steel industry in the Doce River Valley (rural eastern Brazil), this article sets out to understand the relationship between industrial-scale mining and the transition from iron factories to large steel mills. At the same time, it addresses the further destruction of the Atlantic Forest. Studies on the steel industry that highlight the pressure exerted on the Atlantic Forest by charcoal plants are almost nonexistent, however. Turning to technical reports, official statistics, journals, and other media sources and centering attention on Belgo-Mineira company, it highlights a set of data that enables us to measure the impacts of the charcoal-fired steel industry on forests. In order to get a deep insight, the main aim was to estimate the amount of forest extraction to serve the steel industry from 1936 to 1954. The data from this research show that the charcoal-fired steel industry gave a distinctive cast to the phenomenon of the agricultural frontier.

Load transfer of small-diameter GFRP and stainless steel doweled-joints in slabs-on-ground

Large diameter steel and glass fiber-reinforced polymer (GFRP) dowel bars are commonly used in rigid concrete pavements in highways for load transfer across joints to combat the concrete deterioration due to corrosion of steel dowels. Small-diameter GFRP dowel bars can be used at the expansion joints in slabs-on-ground, walkways, industrial floors and concrete-lined channels, which are not subjected to heavy traffic loads. This study investigated the performance and behavior of small-diameter GFRP dowels. GFRP dowels with three diameters (14 mm, 16 mm, and 38 mm) and stainless steel dowels (12 mm dia.) were embedded across a 25 mm-wide joint in a test slab with overall dimensions of 1500 × 750 × 200 mm3. The variables of the study were the type of dowel material (GFRP and stainless steel), the diameter of GFRP dowels, the spacing of the dowels (200 mm and 250 mm c/c), and the type of loading (monotonic and cyclic). The slabs were loaded up to the failure of the joints under a concentrated load applied at the edge of the joint. The performance of the dowel-jointed slab specimens was investigated based on the cracking and ultimate loads, modes of failure, and load-displacement response. The ability of the small-diameter dowel bars to transfer displacements across the joint was quantified using the quantitative measures of joint effectiveness (E), load transfer efficiency (LTE), and relative deflections (Δ). Failure of the specimens with 14 mm and 16 mm diameter dowels occurred predominantly due to shear failure of the dowels before the cracking of concrete. However, for the specimens with large-diameter GFRP dowels and the stainless steel dowels, failure was associated with cracking of the concrete. A smaller spacing of the GFRP dowels and a longer embedment length gave a stiffer load-displacement response. Reducing the spacing from 250 mm to 200 mm resulted in a 4.1-fold reduction in relative deflection under the AASHTO H10 design wheel load (∼35.6 kN). Increasing the dowel length had no significant effect on the load-carrying capacity of the dowel-jointed slabs. Cyclic load tests on the specimens revealed that the joint effectiveness (E) and the load transfer efficiency (LTE) of GFRP dowels were within the AASHTO and ACPA limits up to a concentrated load higher than the AASHTO HL93 dual tandem-axle wheel load (∼55.6 kN).

Automatic Verticality Monitoring and Securing System for Large Circular Steel Pipes

Securing the verticality of foundations is a crucial factor for ensuring safety in offshore construction. The repeated intrusion-pulling method is generally used to ensure verticality in suction bucket foundation construction processes. However, it relies heavily on the experience and skills of field workers and is relatively time-consuming. To address this problem, we propose an automatic verticality securing system for large circular steel pipes based on a verticality monitoring system. This system adjusts cables at locations where verticality correction is required without changing the existing suction pile–penetration–construction process. It includes a monitoring component that provides real-time data on pipe alignment and an automatic lifting cable control system that maintains perpendicularity using data acquired from the monitoring system. The monitoring system comprises a sensor, an embedded controller, and a display program that displays the vertical information of circular steel pipes. The automatic lifting cable control system includes a controller with an algorithm for adjusting the length of the actuator. We showed that the system operates satisfactorily and secures the verticality of less than 0.2° in the suction bucket-based model experiment. Furthermore, the testbed experimental results show that our monitoring system can efficiently measure verticality information in real time.

Electromagnetic-Shocking-Induced Interface Healing and Mechanical Properties Improvement in Pre-Bonded Stainless Steel

Hot-deformation pre-bonding is a newly developed method to avoid smelting defects in large stainless steel billets, in which the high-quality interfacial connection needs to be realized as a key guarantee. In this work, a novel electromagnetic shocking treatment (EST) method, as a special way to apply an external physical field, was proposed to introduce the hot-deformation pre-bonded austenitic stainless steel. It is demonstrated that EST can efficiently optimize the hot-deformation pre-bonded interface and restore the tensile properties of pre-bonded stainless steel within several seconds. The interface healing behaviors induced by EST were analyzed via the in situ observation of an optical micrograph, scanning electron micrograph, as well as electron backscattering diffraction. The optimization of the interface connection is mainly attributed to the fact that EST can act on the interface locally, leading to the healing of voids at the interface accompanied by a reduction in stress and the decomposition of oxide. In addition, EST plays another important role in adjusting the texture difference at both ends of the interface, which can further improve the mechanical properties. The results suggest that EST exhibits great potential in promoting the hot-deformation pre-bonding of large billets.