Failure Scenarios Research Articles

Flood vulnerability of inland bridges with foundation scour

Extreme floods can cause water level to rise above bridge superstructures. Following worldwide statistics on hydraulic bridge failure, it becomes essential to generate a comprehensive knowledge base to predict probable bridge failure scenarios under future floods and to identify appropriate countermeasures for flood risk mitigation. With this objective, the study here develops a numerical framework for systematic evaluation of forces on vulnerable bridge components during floods and to understand the global response of inland river-crossing bridges under flood hazards. Computational fluid dynamics (CFD) simulations are performed to calculate hydrodynamic forces on superstructure of a representative bridge for different inundation levels and flood velocities resulting from varied intensity flood events. Hydrodynamic forces on piers and scour depths around foundations are estimated for flood cases considered here. Knowing the forces and scour depths, finite element bridge models with and without scour are developed and analyzed to apprehend its global response and progressive failure under various combinations of water height and velocity. Further, regression relations are proposed to project component-level responses based on which damage state of the bridge under future intense flood events and fragility characteristics could be predicted. Thus, results enable identifying key factors to reduce flood vulnerability of inland bridges.

Application of SPH in rheology model for the submerged landslide

The seafloor environment is prone to rapid changes caused by landslides, which can result in significant human, financial, and environmental consequences. Previous research efforts have primarily focused on studying rigid submerged landslides using physical experiments and mesh-based numerical simulations. However, there is a need to investigate deformable soil masses due to their inherent complexity. In the current study, a smoothed particle hydrodynamics (SPH) method was developed to examine the behavior of submerged landslides. Three rheological models, namely Bingham, Herschel–Bulkley (H–B), and μ(I), were applied to characterize the properties of the sediment materials. The SPH governing equations were modified at the interface between the water and sediment phases to account for the density discontinuity between them. The viscosity term at this interface was determined using the Owens equation. The effective pressure, a crucial parameter in rheological models, was appropriately modified to reflect the influence of the water column on the sediment particles, utilizing a simple algorithm. For the μ(I) rheology, separate equations were applied to describe the behavior of dry and saturated conditions. Additionally, the Mohr–Coulomb criteria were utilized in the Bingham and H–B models to determine the yield stress. To validate the effectiveness of the proposed modeling approach, a column failure scenario was first simulated. Subsequently, a rigid submerged landslide was investigated to assess the capability and validity of the proposed framework in accurately capturing surge wave generation and calibrating the boundary friction factor. Finally, two deformable submerged landslides involving different materials, namely sand and glass beads, were simulated and compared with previous experimental and numerical studies at different time steps. Through these comprehensive investigations, the current understanding of the complex behavior exhibited by submerged landslides is enhanced, and valuable insight into landslide dynamics is provided.

National-level resilience: Innovative framework for Energy-Water-Food nexus evaluation

The escalating demand for energy, water, and food (EWF) resources, alongside external stressors such as climate change, is placing significant strain on national systems. Therefore, this study introduces a novel framework for assessing the resilience of interconnected EWF systems at a national level. The framework utilizes a hybrid approach of network systems modeling and optimization models, integrating sectoral and dependency impacts to offer a comprehensive perspective on the interconnected resilience of EWF components. Applied to Qatar's EWF nexus, the framework revealed significant interdependencies, particularly between water and energy components, that led to cascading failures and challenged nexus resilience. Under single failure scenarios, unmet demands for energy and water ranged from 9 to 59 GWh and 97,000 to 359,000 m3, respectively, with resilience indices from 0.86 to 0.99. In double failure scenarios, significantly higher unmet demands caused the resilience index to drop to 0.43. Due to limited freshwater availability, the food sector is highly vulnerable to groundwater supply disruptions, resulting in an 85.6 % reduction in total crop production under extreme scenarios. Furthermore, the study highlighted resilience-enhancement strategies, such as utilizing treated wastewater for agricultural, industrial, and commercial activities and diversifying energy sources to reduce the risk of cascading failures, which increased the nexus's resilience by 17 %. The proposed framework serves as an essential tool for identifying critical components within the EWF nexus and planning strategies to enhance both operational and structural resilience.

It’s all your fault! restaurant vs. platform blame attribution in food delivery service failures

PurposeWhile third-party food delivery continues to increase in popularity, surveys suggest nearly a quarter of deliveries suffer from service failures. With the limited research on third-party food delivery, we explore the important questions of (1) where customers place blame in the case of service failures with third-party food delivery (i.e. the platform or the restaurant) and (2) does this depend on the type of service failure? Drawing on blame attribution theory, signaling theory, and an exploratory study, we demonstrate that customers typically perceive such mishaps to be the responsibility of the restaurant rather than the delivery platform itself. We also examine the effect of visible service failure preventative actions taken by the restaurant on blame attribution and re-order intention.Design/methodology/approachWe conducted two online scenario-based studies to explore customer blame attribution in the case of third-party food delivery service failure. First, an exploratory study approach (NStudy1 = 512) was taken to provide additional support for the hypothesis development. An experiment (NStudy2 = 252) was then conducted to examine the hypothesized effects.FindingsFirst, the results of an exploratory study demonstrate that customers attribute service failures such as wrong items, missing items, cold food, or leaking containers to restaurants over third-party food delivery platforms. Second, the results of an experimental study suggest inclusion of an observable cue indicating preventative action, such as time-stamp information indicating when an order was received and packaged for delivery, increases customer re-order intention through the underlying mechanism of blame attribution.Originality/valueWe contribute to the underexplored area of third-party food delivery service failure and to our understanding of blame attribution in service failure scenarios. Further, we demonstrate a practical method to shift the blame away from restaurants for service failures that are outside of the establishment’s control.

Do cracked jaws of the four-jaw chuck of a large lathe pose a danger?

Abstract All the jaws of a four-jaw chuck mounted on the faceplate of a large lathe were received by the material testing laboratory to undergo metallurgical failure analysis. Each of the four jaws exhibited cracks in the fillet radius between one of the gripping surfaces and the long horizontal part. The cracks were just visible to the unaided eye und had been discovered by an alert mechanic. One of the jaws was selected for further material analysis for which the crack was opened to undergo fractographic evaluation. The analysis also involved the evaluation of the material using optical emission spectrometry, the preparation of a metallographic sample, and hardness testing. The cracks occurred as a result of repeated overload at the crack initiation sites located in the fillet radius. This was not a single overload event which would not have caused the jaws to crack, but a series of overload events. The situation did not pose a safety hazard to the staff since the soft and tough core of the case-hardened jaws would have retarded, if not stopped, crack growth. A sudden disastrous failure of the jaws by breaking off, for example, and extremely heavy components crashing down as a result were not an imminent threat. This dangerous failure scenario would have been enabled if the jaws had been through-hardened. Instead, casehardening heat treatment had been applied which is the correct choice for this type of component.

Transmission length of multiwire tendon in existing post-tensioned concrete structures

The paper presents unique research on real-scale post-tensioned concrete crane girders dismantled from an existing hall structure. The study aimed to determine the transmission length for bonded prestressing tendons in an anchorage failure situation, a critical factor for proper assessment of the safety of many building structures, mainly those built between the 1950s and 1980s. The results of the tests indicated the feasibility of prestressing force transmission from a 12Ø5 mm Freyssinet-type tendon to the element via bond stress, with implications extendable to the other 18Ø5 mm tendon type prevalent at the time. The key factor affecting transmission efficiency is the quality of tendon duct grouting, with good quality cement injection resulting in transmission length as short as 800 mm. Furthermore, a computational model for the transmission length of prestressing force in post-tensioned concrete members has been developed similarly to the Model Code 2020 for pretensioned concrete. The level I of approximation enables quick transmission length estimation, whereas refined analysis is possible with the level II approach. The developed model and the research findings facilitate a comprehensive assessment of the post-tensioned concrete members in anchorage or tendon failure scenarios. As a result of the analyses carried out, optimal strategies for the further use of the structures can be proposed, fostering a step towards sustainable management.

A three-level robust scenario-based model for resilience-oriented placement of remote-controlled switches in distribution networks

This paper introduces an innovative strategy to improve the resilience of Distribution Networks (DN) following natural disasters. The approach involves a multi-stage model for the strategic placement of Remote-Controlled Switches (RCS) to expedite fault isolation and service restoration. The model integrates various resilience enhancement techniques, such as network reconfiguration and microgrid formation, throughout the pre-disaster, disaster progression, and post-disaster phases. To mitigate uncertainties related to line failures and ensure planning robustness, a novel three-level Robust Scenario-based Model (RSM) is introduced. The RSM optimizes the strategic RCS placement to enhance System Performance Criteria (SPC) in response to anticipated line failure scenarios, considering individual line vulnerabilities and disaster severity. Subsequently, the model identifies the most critical failures from each predicted scenario based on RCS placements and then recalibrates the placements to enhance DN resilience against both anticipated and critical failures. The RSM is formulated as a mixed-integer linear programming problem to maximize SPC by allocating resources optimally to serve maximum weighted loads while adhering to structural and operational constraints. The effectiveness and validity of the proposed model are demonstrated through case studies conducted on a modified IEEE 33-bus test system and a modified real DN.

RC FRAME RESISTANCE TO PROGRESSIVE COLLAPSE CONSIDERING CRACK OPENING EFFECTS

In this paper, an approach is developed to account for the effect of discrete cracks on the response of reinforced concrete building frames under a column failure scenario. The approach implies the introduction of traditional finite element models of discrete ties that take into account the relationship between moments and rotations, considering the specifics of the performance of materials, sections, and structures under conditions of redistribution of forces as a result of initial local failure in the structural system of a building. Validation of the proposed approach is performed on the experimental data. Also, it is compared with the modeling results of the existing approaches. The effect of discrete cracking on the deformed state of reinforced concrete building frames under the scenario of column failure is established. The discrete cracks practically did not affect the values of axial forces in the elements. However, for bending moments within the proposed method, a decrease was observed in comparison with the traditional approach. The analysis of the diagrams shows that for reinforced concrete frames with 3 and 5 stories, there is an excess of tensile axial forces in the beam over the values according to the traditional calculation method.

An assessment of nature-inspired metaheuristic algorithms for resilient controller placement in software-defined networks

Software-defined Networking (SDN) offers flexibility and programmability, making it a desirable option for modern network architecture. SDN provides numerous benefits to network administrators due to its centralized control architecture. This allows network administrators to manage and configure the network from a single location, making it easier to manage and automate network tasks. In a network of multiple controllers, the control plane’s resiliency may impact the overall system’s performance. In a controller failure scenario, switches must be reassigned to other active controllers with adequate capacity. Thus, we define a resilient controller placement (RCP) as an optimization problem. The aim is to design physically distributed and redundant controllers to manage switches with varying resilience levels. The propagation latency may increase due to the reassignment, increasing the network cost. The objective is to determine the number of controllers required, their positions, and the allocation of the network nodes to a particular controller while reducing the average propagation latency and cost in meeting the capacity constraint of the controller. Due to the wide area network (WAN) structure, four nature-inspired metaheuristic algorithms are proposed namely, simulated annealing (RCP-SA), moth-flame optimization algorithm (RCP-MFO), particle swarm optimization (RCP-PSO), and grey wolf optimization algorithm (RCP-GWO). These algorithms are evaluated on three network datasets to determine the optimum controller number and their positions. The experimental results show that RCP-GWO performs better than RCP-SA, RCP-MFO, RCP-PSO, and the Random methods.

A methodology for ranking of critical links in transportation networks based on criticality score distributions

Criticality of transportation networks links is calculated through utilizing criticality metric(s) for various disruption scenarios that generally include one link removal/degradation at a time or simultaneous removal/degradation of multiple links. As also shown in this paper, single link removals do not reveal the actual criticality of link(s) due to network dependencies. Multiple simultaneous link removal scenarios can capture the network interactions; however, the results relate to the criticality ranking of scenarios than the links, e.g., the links in scenario-1 are more critical than the links in scenario-2. This paper addressed the need for a methodology that provides individual link criticality rankings based on failure scenarios. The proposed approach utilizes the distribution of the criticality scores for each link based on running traffic assignment for each failure scenario, e.g., the distribution for link #X is composed of the criticality scores of all link failure combinations that include link #X. The criticality ranking for each link is identified based on its criticality distribution's mean, coefficient of variation and skewness. The use of the proposed approach is illustrated on test networks to show that it provides robust link criticality rankings that accounts for network interactions across varying scales of link failure scenarios.

Fire performance of steel reinforced concrete column to reinforced concrete beam planar frames: Experiment

This paper investigates the fire performance of large-scale steel reinforced concrete (SRC) column to reinforced concrete (RC) beam planar frames by a series of fire resistance tests. The testing parameters included beam load ratio, column steel ratio and column dimension. The test results indicated that, in fire condition, the SRC column to RC beam frame exhibited two primary failure modes: beam shear failure and column compression failure. In the case of beam shear failure, the fire resistance of frame specimens increased as the beam load decreased. In the scenario of column compression failure, out-of-plane failure occurred due to the weak axis of the SRC column being located outside the frame plane. Concurrently, the RC beam displayed significant shear deformation at the ends and notable bending deformation in the middle. The test results indicated that the column cross-sectional size notably influenced the fire resistance of SRC column to RC beam frame, however, the influence of column steel ratio was minimal.

Theoretical Research and Shaking Table Test on Nominal Aspect Ratio of the Isolated Step-Terrace Structure

With the installation of rubber isolation bearings in the upper and lower ground layers, an isolated step-terrace structure was created. Considering the ultimate bearing capacity of the rubber bearing under tension as the critical condition, a comprehensive framework was established to evaluate the overturning failure mechanisms present in isolated step-terrace structures. The bound of nominal aspect ratio was identified as the principal control index within this framework, which incorporates critical parameters such as height ratio (α), width ratio (β), vertical tensile stiffness to compressive stiffness ratio (γ), seismic coefficient (k), and nominal vertical compressive stress (σ0) to provide a thorough analysis of the structural responses and potential failure scenarios. In order to further investigate this matter, a scaled model of an isolated step-terrace concrete frame structure featuring two dropped layers and a single span within an 8° seismic fortification zone was meticulously crafted at a 1:10 similarity ratio. Subsequently, a series of shaking table tests were conducted to analyze the structural response under seismic excitation. The findings indicate that: utilizing the bound of nominal aspect ratio as a metric to gauge the anti-overturning capacity of isolated step-terrace structures is a justified approach. In instances where the height ratio remains constant, the bound of nominal aspect ratio for both positive and negative overturning trended upward with an increase in the width ratio. Notably, the bound of nominal aspect ratio for positive overturning consistently registered lower values compared to that of the negative overturning, underscoring the heightened susceptibility of step-terrace structures to positive overturning. Moreover, in scenarios characterized by higher height and width ratios, the structural integrity remained unscathed by any overturning effects arising from insufficient tensile strength in rubber bearings. Furthermore, the bound of nominal aspect ratio exhibited an ascending trend as the seismic coefficient, nominal vertical compressive stress, and vertical tensile stiffness to compressive stiffness ratio decreased. The outcomes derived from the shaking table test not only confirm the impressive seismic performance of the structure, but also, by closely examining the instantaneous stress variations within the upper and lower isolation layers of the model, substantiate the existence of a positive overturning hazard in scenarios marked by higher seismic coefficients (k). This observation aligns seamlessly with the theoretical projections, thereby substantiating the efficacy of the structural overturning failure theory through direct empirical verification.

A Framework for Condition Survey and Structural Health Monitoring of Masonry Arch Bridges

Masonry arch bridges are essential elements of the road and railway networks of Europe, as they pertain to cultural heritage and play an important role in transportation. The integrity and safety of these centuries-old structures must be ensured. Therefore, there is great interest in understanding the behavior of masonry arch bridges and monitoring their health. Efficient methods for assessing the condition of structures, including inspections and monitoring, constitute a fundamental element of structural health monitoring (SHM) applications. Given the multitude of surveying techniques available, it becomes crucial to establish cost-effective sensor placement strategies capable of detecting structural failures. These strategies can involve identifying particularly sensitive areas, optimizing the number of sensors used, as well as refining the number and duration of monitoring setups, among other considerations. As part of the PONT3 project, which aims to develop a comprehensive and cost-effective approach to anticipate failure propagation in ageing bridges, this research focusses on developing interoperability-driven inspection and monitoring strategies to provide data that will allow anticipating the evolution of possible failure scenarios. In this regard, an extensive summary of the key characteristics of inspection and monitoring technologies, and typical system configurations in existing literature for masonry arch bridges will be provided. Then, the measurable physical parameters of interest for a specific failure propagation scenario will be identified using numerical simulations and applicable monitoring techniques for each of the physical parameters will be determined. Monitoring requirements in terms of measurement locations, accuracy, range, and temporal resolution will also be identified. The recommendations for interoperability-driven data collection to exchange and employ acquired information for the purpose of structural diagnosis will conclude the framework. The study will finally discuss a future outlook on the development of integrated SHM-oriented digital twins.

Stress-strain state of building structures taking into account possible local failure of the element

The issue of choosing a structural design and material for supporting structures is an important technical and economic task at the stage of developing a design solution. It depends on a number of factors: consequence class of the structure, reliability of the design solution, savings in basic building materials. The publication provides a classification of design schemes and types of load-bearing structures used in the corresponding solutions. The disadvantages and advantages of using prefabricated and monolithic structures for the installation and subsequent operation of the structural scheme of buildings and structures are considered. Modern design requirements include ensuring the ability of a damaged structure to adapt to new conditions while continuing to function while ensuring the integrity of human life, property and equipment. New conditions mean the consequences of the occurrence of a certain emergency situation, accompanied by weakening or overloading of the load-bearing structures of a structure or soil foundation: a change in the structural design, a combination of new existing loads and a redistribution of internal forces. The publication reflects the results of assessing the redistribution of the stress-strain state of the elements of the “base - foundations - load-bearing structures” system as a result of the implementation of a hypothetical emergency situation with the exclusion of the load-bearing structure from operation. The case of the collapse of one of the vertical load-bearing elements (local failure of the pylon) of an underground floor, which can be used as a dual-use structure, is considered. Calculations for the stability of the structure against progressive collapse were carried out by numerical modeling in the LIRA SAPR-2019 software using a quasi-static calculation and the method of direct integration of dynamics over time. It has been demonstrated that the method of numerical modeling the joint work of a building with a soil base affects the results of a calculation of the progressive collapse of the building frame. The influence of local collapse of a vertical load-bearing element on the redistribution of stresses and strains in the foundation structures of a building section is assessed. The load on the piles under the pylons around the element removed under the local failure scenario is expected to increase by 15...25%.

Sampling and active learning methods for network reliability estimation using K-terminal spanning tree

Network reliability analysis remains a challenge due to the increasing size and complexity of networks. This paper presents a novel sampling method and an active learning method for efficient and accurate network reliability estimation under node failure and edge failure scenarios. The proposed sampling method adopts Monte Carlo technique to sample component lifetimes and the K-terminal spanning tree algorithm to accelerate structure function computation. Unlike existing methods that compute only one structure function value per sample, our method generates multiple component state vectors and corresponding structure function values from each sample. Network reliability is estimated based on survival signatures derived from these values. A transformation technique extends this method to handle both node failure and edge failure. To enhance efficiency of proposed sampling method and achieve adaptability to network topology changes, we introduce an active learning method utilizing a random forest (RF) classifier. This classifier directly predicts structure function values, integrates network behaviors across diverse topologies, and undergoes iterative refinement to enhance predictive accuracy. Importantly, the trained RF classifier can directly predict reliability for variant networks, a capability beyond the sampling method alone. Through investigating several network examples and two practical applications, the effectiveness of both proposed methods is demonstrated.

A graph-based method for identifying critical pipe failure combinations in water distribution networks

ABSTRACT Water distribution networks (WDNs) are critical infrastructures prone to vulnerabilities which lead to failures. Identifying vulnerable components, especially multiple pipe failure combinations, is crucial for effective management and ensuring high reliability. Hydraulic simulations are commonly used for analysing the criticality of WDN, but are time-consuming and highly data-reliant, limiting the number of testable combinations. To address these limitations and constraints, a graph-based method is proposed to quantify the impact magnitude of multiple pipe failure scenarios on performance, enabling the identification of critical combinations. The proposed graph-based approach utilizes structural and topological characteristics of WDNs as well as spatial demand distribution to replicate hydraulic behaviour. The accuracy of the approach is assessed by testing it on three case studies with various pipe failure combinations, and the results are compared with hydraulic analyses. The results demonstrate a strong correlation (Spearman coefficient > 0.75) between graph-based ranking and state-of-the-art hydraulic-based ranking. Additionally, the method exhibits a significant computational gain factor of greater than 30 compared with the hydraulic-based method, rendering it valuable for actively exploring a wide range of critical pipe failure combinations and devising countermeasures. Furthermore, a hybrid-based method that integrates both the graph and hydraulic-based methods is proposed for enhanced accuracy and robust assessments.

Failure Analysis of a Suspended Inter-Array Power Cable between Two Spar-Type Floating Wind Turbines: Evaluating the Influence of Buoy Element Failure on the Cable

The suspended configuration of inter-array power cables between floating offshore wind turbines necessitates using various ancillary equipment, such as buoy elements and bend stiffeners, to maintain the desired cable geometry. The failure analysis is an important step in the design of an inter-array dynamic power cable layout. This study investigates the impact of buoy element failures on the structural integrity and fatigue life of inter-array power cable configurations in offshore environments, focusing on four environmental conditions representative of the North Sea. Utilizing numerical simulations and fatigue analysis in OrcaFlex, static and dynamic analyses are conducted to assess maximum tension, minimum bend radius (MBR), and fatigue life under single and two failure scenarios of buoy elements. The results indicate that single buoy failures significantly increase maximum tension at hang-off points. At the same time, MBR is found to be the smallest at the failure position, aiding in failure point identification. In addition, for the two buoy element failure scenarios, the maximum tension increase poses risks to structural integrity, while MBR and fatigue life have high sensitivity to the applied environmental conditions.

A probabilistic approach to optimal emergency shutdown valve configuration for pressurised CO2 pipelines

This study presents a multi-objective optimisation technique for determining the optimal number of in-line Emergency Shutdown Valves (ESDVs) for pressurised CO2 pipelines, aiming to balance risk associated with pipeline failure against the valve cost based on treating the risk as a probabilistic variable. Using standard Probability Density Functions (PDFs) to model the uncertainties inherent in pipeline characteristics and operating conditions, we perform a Monte Carlo simulation involving the random sampling from these PDFs to derive a probabilistic distribution of risk. This method contrasts with traditional deterministic methods that rely on assuming the worst-case failure scenario or pre-determining an averaged expected risk level — typically calculated by summing the products of failure frequencies and consequence magnitudes for various representative failure scenarios. The proposed approach integrates the risks of all possible failure scenarios directly into the optimisation process without such assumptions or pre-determinations, assessing them collectively based on their individual probabilities of occurrence. Our findings illustrate that the proposed technique allows for more reliable and effective ESDV configurations compared to the traditional methods. This approach not only facilitates safer CO2 transport within the context of Carbon Capture, Utilisation and Storage but also offers a framework for optimising pipeline ESDV configurations in general.

Finding influential nodes in complex networks based on Kullback–Leibler model within the neighborhood

As a research hot topic in the field of network security, the implementation of machine learning, such as federated learning, involves information interactions among a large number of distributed network devices. If we regard these distributed network devices and connection relationships as a complex network, we can identify the influential nodes to find the crucial points for optimizing the imbalance of the reliability of devices in federated learning system. This paper will analyze the advantages and disadvantages of existing algorithms for identifying influential nodes in complex networks, and propose a method from the perspective of information dissemination for finding influential nodes based on Kullback–Leibler divergence model within the neighborhood (KLN). Firstly, the KLN algorithm removes a node to simulate the scenario of node failure in the information dissemination process. Secondly, KLN evaluates the loss of information entropy within the neighborhood after node removal by establishing the KL divergence model. Finally, it assesses the damage influence of the removed node by integrating the network attributes and KL divergence model, thus achieving the evaluation of node importance. To validate the performance of KLN, this paper conducts an analysis and comparison of its results with those of 11 other algorithms on 10 networks, using SIR model as a reference. Additionally, a case study was undertaken on a real epidemic propagation network, leading to the proposal of management and control strategies for daily protection based on the influential nodes. The experimental results indicate that KLN effectively evaluates the importance of the removed node using KL model within the neighborhood, and demonstrate better accuracy and applicability across networks of different scales.

On the optimization of green multimodal transportation: a case study of the West German canal system

AbstractIn this study, we address a biobjective multimodal routing problem that consists of selecting transportation modes and their respective quantities, optimizing transshipment locations, and allocating port orders. In the objective functions, we minimize total transportation costs and use the EcoTransit methodology to minimize total greenhouse gas emissions. The optimization model selects the transportation mode and transshipment port where quantities are transshipped from one mode to another. We compare inland waterway transportation and trucks encountering infrastructure failures that require rerouting or modal shifting in a real-life case study on the supply of goods for the chemical industry in the West German canal system. We propose a population-based heuristic to solve large instances in a reasonable computation time. A sensitivity analysis of demand, of varying lock times, and of infrastructure failure scenarios was conducted. We show that compared with inland waterway transportation, multimodal transportation reduces costs by 23% because of longer lock times. Our analysis shows that the use of inland waterway transportation only during infrastructure failures imposes nearly 28% higher costs per day depending on the failure location compared to that of the case of no failures. We also show that the use of a multimodal transportation system helps to reduce this cost increase in lock failure scenarios.