Dynamic reliability analysis of Aerial Building Machine under extreme wind loads using improved QBDC-based active learning

Dynamic reliability analysis of slopes based on the probability density evolution method

In civil and offshore engineering, the safety and serviceability of complex structures are of great concern due to the randomness involved in both external excitations and structural properties. Therefore, nonlinear stochastic dynamics of multi-dimensional complex systems plays a central role in the performance assessment of such structures. In the past decade, a new family of probability density evolution method (PDEM) was developed for this purpose. In this method, based on the principle of preservation of probability, a generalized density evolution equation was derived. In contrast to the celebrated FPK and Liouville equations, the dimension of this family of equation depends only on the number of quantities of interest instead of the dimension of the original dimension. In this paper, a newly proposed generalized F-discrepancy (GF-discrepancy) is outlined and adopted as the objective function in point selection of PDEM. By doing so, the efficiency and accuracy of PDEM could be improved and guaranteed for random variables of general distributions. Numerical examples are illustrated. Problems to be further studied are discussed.

An ensemble evolution numerical method for solving generalized density evolution equation

Probability density evolution method for seismic displacement-based assessment of earth retaining structures

This article presents an efficient method for analyzing the dynamic reliability of maglev vehicle-bridge coupled systems by combining a theoretical model with an adaptive surrogate model and the probability density evolution method (PDEM). First, a refined theoretical model of a maglev vehicle-bridge coupling system is established. Next, an adaptive surrogate model of the equivalent extreme value of the system dynamic response is established by combining an adaptive sampling method with radial basis functions. Finally, the adaptive surrogate model and PDEM are combined to further improve the efficiency of the dynamic reliability analysis. In the numerical example, the theoretical model of the maglev vehicle-guideway system was first validated by comparing with the measured data from the Shanghai high-speed maglev line. Then, by treating the controller parameters as normally distributed random variables, the accuracy and efficiency of the proposed reliability method were verified through comparison with the Monte Carlo method and the one-stage sampling surrogate model. Additionally, the impact of the randomness of each controller parameter and the coefficient of variation of the controller parameters on the system’s dynamic reliability was discussed.

Surrogate modeling immersed probability density evolution method for structural reliability analysis in high dimensions

Uncertainty propagation of flutter analysis for long-span bridges using probability density evolution method

Structural design optimization under dynamic reliability constraints based on the probability density evolution method and highly-efficient sensitivity analysis

Wind resistant size optimization of geometrically nonlinear lattice structures using a modified optimality criterion method

Reliability assessment of stochastic dynamical systems using physics informed neural network based PDEM

Active learning approaches require a lot of time investment in student activities and engagement during the class period, which often leads to incomplete coverage of the course syllabus. Furthermore, it requires significant amount of time for the instructor to design and implement active learning strategies. All these shortcomings are often cited as the common hindrance in adopting student active learning. To address these widely recognized inhibiting factors, we recently implemented a new student active learning approach. This approach is based on the students’ presentation and hence termed as student presentation-based active learning (SPAL). Under this approach, students are given a reading assignment to prepare a PowerPoint presentation on well-defined conceptual topics, questions, or chapter modules. Reading assignments on a topic are administered 1–2 weeks before covering them in the class. This allows reasonable time for the self-comprehension of the suggested material for presentation preparation. Students were expected to rehearse the presentation and be prepared to complete it in the suggested time duration. During each lecture, one group of student would present the assigned topic to the class, and their presentations were graded according to the rubric focusing on the coverage of suggested topics, quality of presentation, and after presentation discussions. Peers and instructor provided feedback about the students’ presentation and unclear concepts. To understand the efficacy of this approach, this approach was implemented in Mechanical Engineering Senior Capstone Project I course in Fall 2016. Here the responses and insights garnered from this practice were presented, and discussion on the advantages and challenges associated with the adaptation of this approach in teaching engineering courses as compared to lecture based classroom education system. This paper can provide useful insights for instructors considering this approach or similar student active teaching approach in their courses.

Physics guided wavelet convolutional neural network for wind-induced vibration modeling with application to structural dynamic reliability analysis

Wind-induced dynamic response and wind load factor for flexible roof structures with medium deformation

The joint probability density function (PDF) of different structural responses is a very important topic in the stochastic response analysis of nonlinear structures. In this paper, the probability density evolution method, which is successfully developed to capture the instantaneous PDF of an arbitrary single response of interest, is extended to evaluate the joint PDF of any two responses. A two-dimensional partial differential equation in terms of the joint PDF is established. The strategy of selecting representative points via the number theoretical method and sieved by a hyper-ellipsoid is outlined. A two-dimensional difference scheme is developed. The free vibration of an SDOF system is examined to verify the proposed method, and a frame structure exhibiting hysteresis subjected to stochastic ground motion is investigated. It is pointed out that the correlation of different responses results from the fact that randomness of different responses comes from the same set of basic random parameters involved. In other words, the essence of the probabilistic correlation is a physical correlation.

Recent developments in the field of Information Technology call for a specific reconsideration of the traditional educational methods and facilitate development of new teaching and learning methods and tools, opening it for a wider scope of concerned persons. Active teaching and learning methods as part of educational methodology are widely used at the universities across the European community, putting the larger responsibility of learning at the hands of the learners themselves. One of the major challenges is effective addressing the learning needs of the new generation of students. Postgraduate education in in the field of logistics and supply chain management (LSCM) must keep it in mind in order to promote a suitable answer to the LSCM labor market needs. This is accomplished well by a master programme in LSCM with a European dimension emerged from the synergy of international cooperation between Academia and the professional bodies. This paper shares the empirical study on implementation of Master study programme of Logistics and Supply Chain Management in the Riga Technical University and extensive use of active and innovative learning approach.