Long-term performance of reinforced concrete under a de-icing road environment

In the middle of 1990, over 30 different mixes of concretes with eight different binders and water-binder ratios of 0.3 to 0.75 were exposed to a highway environment with a heavy de-icing salt spread for the examination of long-term performance, including chloride penetration, reinforcement corrosion and frost attack. This paper presents the results from this long-term study regarding chloride penetration and reinforcement corrosion. The results show that the chloride penetration in concretes under a de-icing salt road environment is much weaker than that in concretes under marine splash environment in Sweden. The estimated critical chloride content for the corrosion initiation is about 0.3 % by mass of binder for rebars with uncracked concrete cover. Considering the chloride redistribution in the surface zone, ClinConc model has been modified so that it can present a better description of the chloride profiles in the concretes at such an exposure site

Improving the performance of alkali-activated slag mortar with electro/chemically treated carbon fiber textile

Alkali-activated slag is a widely used low-carbon binder. Incorporation of textile can mitigate the brittle weakness of alkali-activated composites. The bonding between fibers and matrix is critical for the performance of textile reinforced mortar. This paper is focused on the effect of different treatment methods on the bonding properties of carbon fiber in alkali-activated slag. The interfacial shear strength of fiber bundles in matrix was determined by the pull-out test. The flexural strength of the reinforced mortar was evaluated by a repeated bending. A scanning electron microscopy test was performed to characterize the interfacial properties of the fiber bundles. The results show that the interfacial shear strength of carbon fibers in matrix is improved by the electroplating with calcium silica slurry (CSS), impregnation in different solutions, and plasma treatments. An electroplating in CSS has the best improvement in the bonding strength with an increase by 620%. The CSS treatment increases the maximum flexural strength of CFT reinforced mortar with 22.5% and 30% at 7 and 28 d respectively, and it significantly inhibits the crack growth under the cyclic loading. This effect becomes more significant after a longer curing age. The electroplating treatment eliminates the cracks in the interface of fiber yarns. Slag reacts with the plated portlandite to strengthen the bonding between mortar and fiber bundles, so it has a better inhibiting effect on the crack growth after a longer curing

New insights into the reaction of tricalcium silicate (C3S) with solutions to the end of the induction period

Although dissolution theory is widely used, in certain circumstance, it seems to be unable to explain the hydration of C3S. In this article, more attention is paid to the nucleation of hydration products. We find that the precipitation of C-S-H is a nonclassical nucleation process. It starts with nucleation of primary particles and then grows by particle attachment. A sharp increase in the reaction rate after induction period may come from the accelerating growth rate of C-S-H instead of dissolution of etch pits. The duration of induction period relates to the size of primary floc. Potassium salts influence the primary globule floc size and mitigate the effect from Al. The pH impacts ion species in solution to affect the dissolution and precipitation. A hypothesis regarding the dissolution of C3S and nucleation of C-S-H within the near-surface region may narrow the gap between dissolution theory and protective layer theory

Distribution and dynamics of water in the blended pastes unraveled by thermoporometry and dielectric properties

Water distribution in hardened paste and its dynamics determine many properties related to durability. Moisture distribution was determined by thermoporometry combined with vacuum drying. Dynamics of confined water were measured by broadband dielectric spectroscopy. Water in pores <2.4 nm cannot form tetrahedral ice structure due to geometrical constraints. The volume of unfrozen water (in interlayer and gel pores) decreases after the drying at all relative humidity levels. An evident coarsening of gel pores occurs with drying between 75 % and 55 % RH. 35 % fly ash and slag have limited effects on relaxation processes of silanol hydroxyl groups and interlayer water. However, they slow down the dynamics of water in small gel pores, thereby enhancing interactions between water and the solid interface. This study clarifies the microstructural changes during the drying and reveals the sensitivity of water dynamics to the chemical environment in C-S-H of blended pastes

Real-time monitoring the electrical properties of pastes to map the hydration induced microstructure change in cement-based materials

The effect of the supplementary materials (SCMs) on the moisture content and ion diffusivity at different hydration time is important for the service life modelling of modern concrete. This study designed a simple but valid method to monitor the microstructure change in pastes during hydration. A procedure easy to implement was proposed to detect the water content in pastes. The electrical conductivity of pore solution was evaluated by the evaporable water content in pastes and chemical composition in the binders. Results show that the electrical properties of pastes (conductivity, formation factor and its growth rate) can effectively indicate the hydration reactivity of binder, pore connectivity and volume of pore solution in the hardened pastes. The effect of waterbinder ratio and SCMs on the structure of pastes are effectively indexed by the formation factor which is the conductivity of pore solution divided by that of paste. The inflection point of average growth rate of formation factor is a good index for the final setting of pastes. The relation between volume of evaporable water and formation factor is well demonstrated by the extended percolation theory. The real-time monitored electrical conductivity and formation factor of pastes can be used to calculate the chloride migration coefficient in hardened cement pastes

Detector Guidance for Multi-Object Text-to-Image Generation

Diffusion models have demonstrated impressive performance in text-to-image generation. They utilize a text encoder and cross-attention blocks to infuse textual information into images at a pixel level. However, their capability to generate images with text containing multiple objects is still restricted. Previous works identify the problem of information mixing in the CLIP text encoder and introduce the T5 text encoder or incorporate strong prior knowledge to assist with the alignment. We find that mixing problems also occur on the image side and in the cross-attention blocks. The noisy images can cause different objects to appear similar, and the cross-attention blocks inject information at a pixel level, leading to leakage of global object understanding and resulting in object mixing. In this paper, we introduce Detector Guidance (DG), which integrates a latent object detection model to separate different objects during the generation process. DG first performs latent object detection on cross-attention maps (CAMs) to obtain object information. Based on this information, DG then masks conflicting prompts and enhances related prompts by manipulating the following CAMs. We evaluate the effectiveness of DG using Stable Diffusion on COCO, CC, and a novel multi-related object benchmark, MRO. Human evaluations demonstrate that DG provides an 8-22\% advantage in preventing the amalgamation of conflicting concepts and ensuring that each object possesses its unique region without any human involvement and additional iterations. Our implementation is available at \url{https://github.com/luping-liu/Detector-Guidance}

Chat-3D v2: Bridging 3D Scene and Large Language Models with Object Identifiers

Recent research has evidenced the significant potentials of Large Language Models (LLMs) in handling challenging tasks within 3D scenes. However, current models are constrained to addressing object-centric tasks, where each question-answer pair focuses solely on an individual object. In real-world applications, users may pose queries involving multiple objects or expect for answers that precisely reference various objects. We introduce the use of object identifiers to freely reference objects during a conversation. While this solution appears straightforward, it presents two main challenges: 1) How to establish a reliable one-to-one correspondence between each object and its identifier? 2) How to incorporate complex spatial relationships among dozens of objects into the embedding space of the LLM? To address these challenges, we propose a two-stage alignment method, which involves learning an attribute-aware token and a relation-aware token for each object. These tokens capture the object's attributes and spatial relationships with surrounding objects in the 3D scene. Once the alignment is established, we can fine-tune our model on various downstream tasks using instruction tuning. Experiments conducted on traditional datasets like ScanQA, ScanRefer, and Nr3D/Sr3D showcase the effectiveness of our proposed method. Additionally, we create a 3D scene captioning dataset annotated with rich object identifiers, with the assistant of GPT-4. This dataset aims to further explore the capability of object identifiers in effective object referencing and precise scene understanding

Pitfalls in Using Electrical Conductivity to Monitor the Chloride Ingress of Concrete

Chloride ingress in the field structure is influenced by many factors. A non-destructive monitoring is a useful tool for assessing the health of reinforced structures. This study used array sensors to measure the temperature and electrical conductivity of concrete at depths from 10 mm to 140 mm. The electrical conductivity in concrete showed a continuous decrease during the exposure to 3% NaCl solution. A numerical modelling of multi-ion species migration in pore solution can explain the evolution of conductivity profile over exposing time. By comparing with several previous investigations, this study identified the pitfalls in using electrical conductivity or resistivity to monitor the chloride ingress in the exposed concrete. To obtain a correct information from the electrical monitoring system, the experimental and analysing process should consider the saturation degree of concrete, the hydration induced structure change, the leaching of ions, the ingress of chloride and composition of binders

Moisture and ion transport properties in blended pastes and their relation to the refined pore structure

This paper presents a study of the\ua0moisture transport\ua0properties in blended pastes measured by a new procedure and setup. The dependence of moisture transport coefficient on relative humidity (RH) is confirmed. The differences in the moisture dependency may be due to discrepancies in the critical RH for the\ua0percolation\ua0of liquid. Fly ash and slag increase the percentage of mesopores or “ink-bottle” pores with a\ua0mesoscale\ua0neck and they strongly reduce the pore connectivity in pastes. These effects cause the evident reduction in the moisture and chloride diffusivity. The additional replacement with\ua0limestone filler\ua0has little effect on the pore connectivity. The formation factor controls the moisture transport at the high RH interval, but the volume of small pores (middle capillary and mesopores) is the major determinant at a low RH interval. The relationship between water-binder ratio,\ua0pore structure\ua0and moisture transport or chloride migration coefficient is discussed

Extending Multi-modal Contrastive Representations

Multi-modal contrastive representation (MCR) of more than three modalities is critical in multi-modal learning. Although recent methods showcase impressive achievements, the high dependence on large-scale, high-quality paired data and the expensive training costs limit their further development. Inspired by recent C-MCR, this paper proposes Extending Multimodal Contrastive Representation (Ex-MCR), a training-efficient and paired-data-free method to flexibly learn unified contrastive representation space for more than three modalities by integrating the knowledge of existing MCR spaces. Specifically, Ex-MCR aligns multiple existing MCRs into the same based MCR, which can effectively preserve the original semantic alignment of the based MCR. Besides, we comprehensively enhance the entire learning pipeline for aligning MCR spaces from the perspectives of training data, architecture, and learning objectives. With the preserved original modality alignment and the enhanced space alignment, Ex-MCR shows superior representation learning performance and excellent modality extensibility. To demonstrate the effectiveness of Ex-MCR, we align the MCR spaces of CLAP (audio-text) and ULIP (3D-vision) into the CLIP (vision-text), leveraging the overlapping text and image modality, respectively. Remarkably, without using any paired data, Ex-MCR learns a 3D-image-text-audio unified contrastive representation, and it achieves state-of-the-art performance on audio-visual, 3D-image, audio-text, visual-text retrieval, and 3D object classification tasks. More importantly, extensive qualitative results further demonstrate the emergent semantic alignment between the extended modalities (e.g., audio and 3D), which highlights the great potential of modality extensibility.Comment: Our code is available at https://github.com/MCR-PEFT/Ex-MC