New Approach for Reliability-Based Design Optimization: Minimum Error Point

Conventional reliability-based design optimization (RBDO) requires to use the most probable point (MPP) method for a probabilistic analysis of the reliability constraints. A new approach is presented, called as the minimum error point (MEP) method or the MEP based method, for reliability-based design optimization, whose idea is to minimize the error produced by approximating performance functions. The MEP based method uses the first order Taylor\u27s expansion at MEP instead of MPP. Examples demonstrate that the MEP based design optimization can ensure product reliability at the required level, which is very imperative for many important engineering systems. The MEP based reliability design optimization method is feasible and is considered as an alternative for solving reliability design optimization problems. The MEP based method is more robust than the commonly used MPP based method for some irregular performance functions

Robust Design Optimization Involving Interval Parameters Based on Robust Performance Variations

This paper present a hew robust design optimization method based on robust performance variation estimation, in which only the known ranges of design parameters were required without presumed probability distributions. the robust performance variation was used to represent the robustness of design instead of the robustness index, the robustness of objective value and the robustness of feasibility in the formulation of robust design optimization. the new robust design optimization involving interval parameters included three levels. Upper level optimized objective function subject to the robustness constraints, which output a design solution and receipted the robust performance variations of objective functions and constraint functions from the middle level. the middle level conducted the search for the robust performance variations using an iterative approach, which output robust performance variations and receipted the design solution for the upper level, and output the performance variation and obtained the robustness index for the lower level. Lower level performed the search for the robustness index at a given performance variation by means of an optimization approach. by using analytical interpretation and providing illustrative examples, the RPV method shows its advantages that its process and results are easier to be understood by designers and that it enables designers to easier achieve the robustness of a design solution by simultaneously optimizing the mean performance, minimizing the performance variation and maintaining feasibility robustness and to carry out a trade-off analysis between the objective values and the robustness of design solutions because the robust performance variation is of the same physical significance as the performance function

Predicting the Integrated Fire Resistance of Wildland–Urban Interface Plant Communities by Spatial Structure Analysis Learning for Shanghai, China

Fire is a prevalent hazard that poses a significant risk to public safety and societal progress. The continuous expansion of densely populated urban areas, exacerbated by global warming and the increasing intensification of urban heat islands, has led to a notable increase in the frequency and severity of fires worldwide. Incorporating measures to withstand different types of calamities has always been a crucial aspect of urban infrastructure. Well-designed plant communities play a pivotal role as a component of green space systems in addressing climate-related challenges, effectively mitigating the occurrence and spread of fires. This study conducted field research on 21 sites in the green belt around Shanghai, China, quantifying tree morphological indexes and coordinate positions. The spatial structure attributes of different plant communities were analyzed by principal component analysis, CRITIC weighting approach, and stepwise regression analysis to build a comprehensive fire resistance prediction model. Through this research, the relationship between community spatial structures and fire resistance was explored. A systematic construction of a prediction model based on community spatial structures for fire resistance was undertaken, and the fire resistance performance could be quickly judged by easily measured tree morphological indexes, providing valuable insights for the dynamic prediction of fire resistance. According to the evaluation and ranking conducted by the prediction model, the Celtis sinensis, Sapindus saponaria, Osmanthus fragrans, Koelreuteria paniculata, and Distylium racemosum + Populus euramericana ‘I-214’ communities exhibited a high level of fire resistance. On the other hand, the Koelreuteria bipinnata + Ligustrum lucidum, Ginkgo biloba + Camphora officinarum + Ligustrum lucidum, and Ligustrum lucidum + Sapindus saponaria communities obtained lower scores and were positioned lower in the ranking. It is emphasized that the integration of monitoring and regulation is essential to ensure the ecological integrity and well-being of green areas in the Wildland–Urban Interface

An On-Site-Based Opportunistic Routing Protocol for Scalable and Energy-Efficient Underwater Acoustic Sensor Networks

With the advancements in wireless sensor networks and the Internet of Underwater Things (IoUT), underwater acoustic sensor networks (UASNs) have attracted much attention, which has also been widely used in marine engineering exploration and disaster prevention. However, UASNs still face many challenges, including high propagation latency, limited bandwidth, high energy consumption, and unreliable transmission, influencing the good quality of service (QoS). In this paper, we propose a routing protocol based on the on-site architecture (SROA) for UASNs to improve network scalability and energy efficiency. The on-site architecture adopted by SROA is different from most architectures in that the data center is deployed underwater, which makes the sink nodes closer to the data source. A clustering method is introduced in SROA, which makes the network adapt to the changes in the network scale and avoid single-point failure. Moreover, the Q-learning algorithm is applied to seek optimal routing policies, in which the characteristics of underwater acoustic communication such as residual energy, end-to-end delay, and link quality are considered jointly when constructing the reward function. Furthermore, the reduction of packet retransmissions and collisions is advocated using a waiting mechanism developed from opportunistic routing (OR). The SROA realizes opportunistic routing to choose candidate nodes and coordinate packet forwarding among candidate nodes. The scalability of the proposed routing protocols is also analyzed by varying the network size and transmission range. According to the evaluation results, with the network scale ranging from 100 to 500, the SROA outperforms the existing routing protocols, extensively decreasing energy consumption and end-to-end delay

Genetic connection between mud shale lithofacies and shale oil enrichment in Jiyang Depression, Bohai Bay Basin

By using microscope, argon ion polishing technology, nuclear magnetic resonance (NMR), scanning electron microscopy, and hydrocarbon generation and expulsion simulation, reservoir properties, oiliness and shale oil mobility of different mud shale lithofacies were examined with the mud shale in Jiyang Depression, Bohai Bay Basin as the example. The relationship between lithofacies type and shale oil enrichment was analyzed. Based on the rock composition, sedimentary structures and abundance of organic matter, a mud shale lithofacies classification standard for the upper submember of the 4th Member to the lower submember of the 3rd Member of Paleogene Shahejie Formation (Es4s-Es3x) was established. Six lithofacies are developed in the target formation, in which the laminar organic-rich lithofacies formed in the alternating mechanical transportation deposition and chemical deposition, not only has the highest TOC, S1, oil saturation, movable oil saturation, content of low-carbon light components and oil generation and expulsion rate, but also has various types of reservoir space, abundant pores, and organic network system and interlayer micro-fracture system which can serve as high-speed channels for shale oil and gas migration, so this lithofacies is favorable for shale oil enrichment. Key words: mud shale, shale oil, lithofacies, oiliness, reservoir properties, organic network, microcracks, Jiyang Depression, Bohai Bay Basi