ce/papers最新文献

Nonlinear analysis of reinforced concrete structures is becoming a standard tool for both the assessment of existing structures and the design of new ones. This trend is supported by new safety formats for nonlinear analysis introduced in the fib Model Code 2010 and incorporated in the new Eurocode (prEN 1992-1-1:2022). A key challenge is the evaluation and management of uncertainties. This paper focuses on the model uncertainty in ultimate and serviceability limit states, including crack width estimation. The significant insights into modeling uncertainty are provided by the recent blind prediction competitions, which offer a practical benchmark for assessing the robustness and reliability of nonlinear models and software tools. This paper highlights the findings from several such competitions. A key limitation is that the material uncertainties are typically neglected, meaning that the most accurate predictions often result from a chance rather than from the consistently reliable modeling.

In structural safety assessments, the selection of suitable parameters for stochastic models of component properties — such as concrete compressive strength or geometric dimensions — is a prime requirement. During their production, several quality control strategies are adopted to verify the specified value of diverse properties of structural members. Bayesian statistics form a suitable basis for updating the statistical distribution parameters when input from quality control is available. Previous work in the field of concrete compressive strength has demonstrated that such strategies introduce a filtering effect on the stochastic description of concrete strength distribution, which may have a positive influence on the resulting safety level. However, a generic approach applicable to a wider scope of properties remains to be established. This paper offers a methodology to update the distributional parameters based on input from quality control and further integration in safety assessments. By considering the filtering effect of quality control on the distributions of material properties, the proposed methodology aims to assist practitioners to unlock existing safety margins in structural design and, thus, propose more material and resource efficient solutions.

Conveying risk and reliability metrics to non-experts is hard because probabilities and expected monetary losses often lie far outside everyday intuition. This paper looks at interactive web-hosted tools as a means to alleviate this problem by comparing three existing tools to distil design guidance: a digital handbook for reliability predictions in space applications, a cloud inspection-planning app for deteriorating structures, and a municipal fire-risk platform. Each tool is evaluated against six recurrent themes: visualisation, interactivity, accessibility, maintainability, gamification, personalisation. Findings show that rich graphics plus direct parameter control are the entry ticket for engagement, while responsive web delivery and automated versioning keep analyses current and traceable. Light gamified cues (progress bars) and context-aware content (local response times) further motivate users but must be applied sparingly to preserve credibility and privacy. We outline an evolutionary path from searchable digital handbooks through parameter-driven calculators to map-centred dashboards and demonstrate that well-crafted interactivity transforms static risk reports into exploratory tools that enable genuinely risk-informed decisions across diverse engineering domains.

Experimentally determined number of cycles to failure of concrete specimens exhibit significant scatter due to various influencing factors. Previous studies have identified the scatter in compressive strength as a primary factor affecting the scatter of the number of cycles to failure. To address this issue, a statistical approach was applied to correct the stress levels to account for the influence of the compressive strength scatter. This correction significantly reduced the scatter in the number of cycles to failure, improving the reliability of fatigue assessments.

A database of fatigue tests from the literature was compiled, and the stress levels were corrected, resulting in a significant reduction in the scatter of the number of cycles to failure. A normal distribution was assumed for the logarithmic number of cycles to failure. In addition to the normal distribution, the log-normal distribution and the Weibull distribution were also found to be suitable. The choice of distribution function had only a minor influence on the corrected stress levels. This is shown by the comparison of confidence intervals. These findings contribute to a more precise fatigue assessment methodology, facilitating more sustainable and economical structural design.

Given the increasing demand for mechanized tunneling, effective risk awareness and management have become crucial. Tunnel Information Modeling (TIM) has the potential to offer significant advantages in enhancing efficiency during the planning phase. This study aims to leverage the TIM model in combination with pre identified risk scenarios to accelerate risk identification and streamline mitigation efforts. A risk/scenario matrix, along with a ground model containing geological and geotechnical data along a specified alignment, is used to outline potential failure scenarios. The proposed approach integrates a deterministic model to evaluate the cost-effectiveness of various risk mitigation strategies, including the implementation of immediate measures and the adoption of preventive measures for potential occurrence zones. The outcome of the study is presented in a dynamic dashboard of the various scenarios and their associated costs.

Non-structural components (NSC) are an important part of reinforced concrete (RC) buildings. Their damage constitutes a large portion of the losses encountered by these structures after moderate-severe earthquakes, as well as after more frequent ones. Most, if not all, of the current standards for the design of acceleration-sensitive NSC make use of floor acceleration response spectra, thereby neglecting the influence of the anchorage hysteresis behaviour on their response. Only a few studies have included such an effect on the numerical evaluation of the maximum acceleration reached by NSC anchored to RC buildings. These studies showed that, for single-anchor connections, if the shear hysteresis of the anchorage is included, the maximum acceleration of the NSC and the maximum force of the anchor itself can significantly exceed the design demands computed with design codes. Moreover, the latest study on this topic showed that a very large degree of variability is encountered in the results, depending on the earthquake record used, and of the type of anchor considered. This paper focuses on such a variability – threated as epistemic uncertainty - in the predicted numerical results, showing how, for achieving a given probability of exceedance threshold, the design values might be much larger than those anticipated by the codes or even than the average numerical results. It is shown that if the tolerance gap of the anchorage is reduced or filled in, such a variability/uncertainty decreases considerably.

This paper presents a systematic pipeline for the segmentation of LiDAR data. The LiDAR data is specifically acquired using the LiDAR sensor of a BLK2GO and stored in a PLY format. The presented pipeline uses common post-processing steps for point cloud processing. First, a RANSAC algorithm is used to remove the indoor point cloud scene from the walls, using plane detection for dominant structures. Subsequently, the indoor scene is clustered by a DBSCAN algorithm. The clustered indoor scene objects are then briefly classified manually. After the manual step, the pipeline is using a Gaussian Mixture Model (GMM). The GMM classifies the objects based on their probabilistic distributions of the geometric dimension. Preliminary results indicate that this workflow enables an efficient object detection with a minimal manual effort. Furthermore, the paper investigates uncertainties of process steps and gives new approaches for dealing with the uncertainties. This pipeline aims to establish a practical approach for generating input data for Scan2BIM applications.

One of the first goals of earthquake protection is reducing the building weight. Less weight means less inertial forces and so less seismic energy for the structure to deal with. On the other hand, constructions of the future should reduce their environmental impact as much as possible. During almost 2 years a shaking table test at CEA Paris was planned. Financial support was offered by the Engineering Research Infrastructures for European Synergies (ERIES) program. Tests took place end of October 2024 on the AZALÉE shaking table. The specimen was a two stories structure having two spans in both main directions and a square plan shape. It was built almost entirely out of lightweight materials: lightweight concrete for slabs and beams and autoclaved aerated concrete (AAC) exterior and partition walls. Only the columns were built out of normal weight concrete. Multipurpose AAC blocks were used, joining thermal insulation properties, formwork for circular end columns and structural behavior. Several uncertainties were encountered during the specimen building stage and the establishment of the structural model. These uncertainties are presented and discussed in this paper.

Climate change introduces significant challenges for civil engineering, especially concerning heat resilience in buildings. This study investigates the susceptibility of buildings to heat waves and explores the transferability of adaptation strategies between Germany and Iran. Building resilience is shaped by factors such as architectural design, materials, and construction methods, requiring advanced thermal simulation models to understand building performance. The analysis integrates dynamic building performance simulations, accounting for physical properties, room usage schedules, and ventilation effects, along with meteorological data like temperature, wind, and solar radiation.

By comparing the climatic conditions of Germany and Iran, the study reveals key differences in temperature patterns and their implications for building design. While both countries experience rising temperatures, Iran's climate is more stable, while Germany faces more significant seasonal fluctuations. The study also demonstrates how hourly temperature data can guide heat adaptation strategies, focusing on passive cooling in Germany and minimizing cooling energy demands in Iran. These findings underscore the importance of tailored adaptation measures, including urban planning, shading, and ventilation improvements, to enhance heat resilience in response to local climate conditions.

In the following paper, the influence of uncertainties is investigated for the dynamical behavior of structures improved by tuned mass dampers. Typically, the performance in terms of maximum displacements or accelerations can be improved significantly by additional damper devices. However, the tuning is very sensitive to the physical properties of the structure and dampers. Within this paper, we investigate the uncertainty propagation by an efficient linearization approach within an optimization of the nominal damper parameters. The extension for multi-degree-of-freedom systems is realized by a simplified decoupled solution of the steady-state vibration. The uncertainty propagation is investigated with the introduced linearization approach and regression-based sensitivity analysis is applied to quantify the degree of nonlinearity and the contribution of the input parameters.