Integrated Simulation Modeling Approach for Investigating Pore Water Pressure Induced Landslides

Soil pore water pressure analysis is crucial for understanding landslide initiation and prediction. However, field-scale transient pore water pressure measurements are complex. This study investigates the integrated application of simulation models (HYDRUS-2D/3D and GeoStudio–Slope/W) to analyze pore water pressure-induced landslides. The proposed methodology is illustrated and validated using a case study (landslide in India, 2018). Model simulated pore water pressure was correlated with the stability of hillslope, and simulation results were found to be co-aligned with the actual landslide that occurred in 2018. Simulations were carried out for natural and modified hill slope geometry in the study area. The volume of water in the hill slope, temporal and spatial evolution of pore water pressure, and factor of safety were analysed. Results indicated higher stability in natural hillslope (factor of safety of 1.243) compared to modified hill slope (factor of safety of 0.946) despite a higher pore water pressure in the natural hillslope. The study demonstrates the integrated applicability of the physics-based models in analyzing the stability of hill slopes under varying pore water pressure and hill slope geometry and its accuracy in predicting future landslides.

Validating a Traffic Conflict Prediction Technique for Motorways Using a Simulation Approach

With the ever-increasing advancements in the technology of driver assistant systems, there is a need for a comprehensive way to identify traffic conflicts to avoid collisions. Although significant research efforts have been devoted to traffic conflict techniques applied for junctions, there is dearth of research on these methods for motorways. This paper presents the validation of a traffic conflict prediction algorithm applied to a motorway scenario in a simulated environment. An automatic video analysis system was developed to identify lane change and rear-end conflicts as ground truth. Using these conflicts, the prediction ability of the traffic conflict technique was validated in an integrated simulation framework. This framework consisted of a sub-microscopic simulator, which provided an appropriate testbed to accurately simulate the components of an intelligent vehicle, and a microscopic traffic simulator able to generate the surrounding traffic. Results from this framework show that for a 10% false alarm rate, approximately 80% and 73% of rear-end and lane change conflicts were accurately predicted, respectively. Despite the fact that the algorithm was not trained using the virtual data, the sensitivity was high. This highlights the transferability of the algorithm to similar road networks, providing a benchmark for the identification of traffic conflict and a relevant step for developing safety management strategies for autonomous vehicles.

Integrated modelling method of bonding strength and residual life prediction for selective repair structure of aluminium alloy

To accurately describe and predict the overall strength and residual life of selective repair bonded structures, an integrated simulation model of crack propagation including bonding strength is established. Based on two methods, an integrated simulation model including a cohesive zone method model for predicting the residual life of a selective repair structure is established. By comparing the computational efficiency and accuracy of both the stress intensity factor and residual life of selective repair structures using different calculation methods, the modelling scheme is optimised. Based on this optimised scheme, the effect of adhesive thickness on the stress intensity factor and residual life of the repair structure is analysed. FM94 adhesive measuring 0.2–0.4 mm thickness is used to decrease the stress intensity factor and improve the remaining life such that material utilisation efficiency is guaranteed.

A multi-method integrated simulation system for water resources allocation

Water resources allocation is an important technical tool to alleviate the conflict between water supply and demand, improve the water resources utilization efficiency, and achieve the control target of total water resources utilization. However, the current water resources allocation theory is immature, and there are few objective and quantitative allocation methods, which leads to the relatively backward allocation practice. Moreover, the amounts of allocable water resources change dynamically, which makes the static and single traditional allocation scheme difficult to adapt to changes. To address the above issues, this research comprehensively integrated multiple types of allocation models to build a multi-method integrated simulation system for water resources allocation. The results show that the system supports visually generated schemes and dynamically simulates water resources allocation. The application of the simulation system enhances the reliability of results. And the dynamic adaptability of allocation results supports allocation decisions.

Integrated and Control-Oriented Simulation Tool for Optimizing Urban Drainage System Operation

With the management and operation of urban drainage systems (UDS) becoming more complicated and difficult, integrated models aiming to control and manage the entire drainage system are under enormous demand. Ideally, integrated models, as a potential tool for meeting the increasing demands, should combine both conceptual and mechanistic models that merge all UDS components and balance simulation accuracy with time constraints. Within this context, our study introduces an innovative modeling software, Simuwater, which couples multiple principles, simulates multiple components, and combines optimized control functions, playing a role in the integrated simulation and overflow control application of UDS. The software has been utilized in a real-time case-control study in one city of China, and it obtained significant optimized operation results to reduce combined sewer overflow (CSO) by making full use of the storage facilities and actuators. As the Simuwater model continues to improve in depth and breadth, it will play an increasingly important role in more application scenarios of UDS.

DEVS-Based Building Blocks and Architectural Patterns for Intelligent Hybrid Cyberphysical System Design

The DEVS formalism has been recognized to support generic open architectures that allow incorporating multiple engineering domains within integrated simulation models. What is missing for accelerated adoption of DEVS-based methodology for intelligent cyberphysical system design is a set of building blocks and architectural patterns that can be replicated and reused in system development. As a start in this direction, this paper offers a notional architecture for intelligent hybrid cyberphysical system design and proceeds to focus on the decision layer to consider DEVS models for basic behaviors such as choice of alternatives, perception of temporal event relations, and recognition and generation of finite state languages cast into DEVS time segments. We proceed to describe a methodology to define DEVS-based building blocks and architectural patterns for design of systems employing fast, frugal, and accurate heuristics. We identify some elements of this kind and establish their status as minimal realizations of their defined behaviors. As minimal realizations such designs must ipso facto underlie any implementation of the same cognitive behaviors. We discuss architectures drawn from the cognitive science literature to show that the fundamental elements drawn from the fast, frugal, and accurate paradigm provide insights into intelligent hybrid cyberphysical system design. We close with open questions and research needed to confirm the proposed concepts.