Optimum seismic design of reinforced concrete frames according to Eurocode 8 and fib Model Code 2010

Traditional seismic design, like the one adopted in Eurocode 8 (EC8), is force‐based and examining a single level of seismic action. In order to provide improved control of structural damage for different levels of seismic action, the new fib Model Code 2010 (MC2010) includes a fully fledged displacement‐based and performance‐based seismic design methodology. However, the level of complexity and computational effort of the MC2010 methodology is significantly increased. Hence, the use of automated optimization techniques for obtaining cost‐effective design solutions becomes appealing if not necessary. This study employs genetic algorithms to derive and compare optimum seismic design solutions of reinforced concrete frames according to EC8 and MC2010. This is important because MC2010 is meant to serve as a basis for future seismic design codes. It is found that MC2010 drives to more cost‐effective solutions than EC8 for regions of low seismicity and better or similar costs for regions of moderate seismicity. For high‐seismicity regions, MC2010 may yield similar or increased structural costs. This depends strongly on the provisions adopted for selecting the set of ground motions. In all cases, MC2010 provides enhanced control of structural damage. Copyright © 2016 John Wiley & Sons, Ltd.     

A new method of reduced order feedback control using Genetic Algorithms

Genetic Algorithms (GAs) have been applied as an effective optimization search technique in various fields, including the field of control design. In this paper, a new control method using GAs is proposed to attenuate the responses of a structure under seismic excitation. The proposed controller uses the state space reconstruction technique based on the embedding theorem to obtain full state performance from the available reduced order feedback. The parameters of the new controller are optimized using GAs. The proposed GA-based control method is verified on a benchmark problem—active mass driver system—and the results are compared with other control methods. The robustness of the proposed control method is also examined. Copyright © 1999 John Wiley & Sons, Ltd.     

基于遗传算法地震短期综合预报分类系统在祁连山及海原地震带的应用

应用“基于遗传算法的地震预报分类系统”,建立祁连山及海原地震带3个区的以预报未来3个月最大地震为目标的地震短期综合预报模型。结果表明,能预测出5级以上地震,给出的有效重叠震级区间的模型在祁连西段、祁连中东段检验情况较好,而在海原断裂带应用检验较差。另外对较低震级的检验情况一般要好于较高震级。对2003年lO月25日甘肃民乐、山丹间6．1、5．8级地震进行了实际的应用检验。     

Novel coupling Rosenbrock‐based algorithms for real‐time dynamic substructure testing

Real‐time testing with dynamic substructuring is a novel experimental technique capable of assessing the behaviour of structures subjected to dynamic loadings including earthquakes. The technique involves recreating the dynamics of the entire structure by combining an experimental test piece consisting of part of the structure with a numerical model simulating the remainder of the structure. These substructures interact in real time to emulate the behaviour of the entire structure. Time integration is the most versatile method for analysing the general case of linear and non‐linear semi‐discretized equations of motion. In this paper we propose for substructure testing, L‐stable real‐time (LSRT) compatible integrators with two and three stages derived from the Rosenbrock methods. These algorithms are unconditionally stable for uncoupled problems and entail a moderate computational cost for real‐time performance. They can also effectively deal with stiff problems, i.e. complex emulated structures for which solutions can change on a time scale that is very short compared with the interval of time integration, but where the solution of interest changes on a much longer time scale. Stability conditions of the coupled substructures are analysed by means of the zero‐stability approach, and the accuracy of the novel algorithms in the coupled case is assessed in both the unforced and forced conditions. LSRT algorithms are shown to be more competitive than popular Runge–Kutta methods in terms of stability, accuracy and ease of implementation. Numerical simulations and real‐time substructure tests are used to demonstrate the favourable properties of the proposed algorithms. Copyright © 2007 John Wiley & Sons, Ltd.     

Monitoring household upgrading in unplanned settlements with unmanned aerial vehicles

In-situ slum upgrading projects include infrastructural improvements such as new roads, which are perceived to improve the quality of life for the residents and encourage structural improvements at a household level. Although these physical changes are easily visible in satellite imagery, it is more difficult to track incremental improvements undertaken by the residents – which are perhaps more closely linked to the socio-economic development of the households themselves. The improved detail provided by imagery obtained from Unmanned Aerial Vehicles (UAVs) has the potential to monitor these more subtle changes in a settlement. This paper provides a framework which takes advantage of high-resolution imagery and a detailed elevation model from UAVs to detect changes in informal settlements. The proposed framework leverages expert knowledge to provide training labels for deep learning and thus avoids the cost of manual labelling. The semantic classification is then used to interpret a change mask and identify: new buildings, the creation of open spaces, and incremental roof upgrading in an informal settlement. The methodology is demonstrated on UAV imagery of an informal settlement in Kigali, Rwanda, successfully identifying changes between 2015 and 2017 with an Overall Accuracy of 95 % and correctly interpreting changes with an Overall Accuracy of 91 %. Results reveal that almost half the buildings in the settlement show visible changes in the roofing material, and 61 % of these changed less than 1m². This demonstrates the incremental nature of housing improvements in the settlement.     

Mesoscale eddies off Peru in altimeter records: Identification algorithms and eddy spatio-temporal patterns

Relatively little is known about coherent vortices in the eastern South-Pacific along the Peruvian coast, even with regard to basic facts about their frequency of occurrence, longevity and structure. This study addresses these issues with nearly 15 years of relatively high-resolution satellite altimetry measurements.We first compare two distinct automated methods for eddy identification. The objective validation protocol shows that the rarely-used geometrical or “winding-angle method”, based on the curvature of the streamline functions, is more accurate than the commonly-used “Okubo–Weiss algorithm”, which defines a vortex as a simple connected region with values of Okubo–Weiss parameter weaker than a given threshold.We then investigate vortices off Peru using more than 20,000 mesoscale eddies identified by the winding-angle method. Coherent eddies, characterized by a high ratio of vorticity to deformation rate, are typically formed along the coast and propagate westward at 3–6 cm s⁻¹. The vortices have a mean radius of 80 km, increasing northward, and are most frequently observed off of Chimbote (9°S) and south of San Juan (15°S). The mean eddy lifetime is about 1 month, but if eddies survive at least 2 months, the probability for surviving an additional week (or month) is constant at 90% (or 67%). Anticyclonic eddies tend to propagate northwestward whereas cyclonic vortices migrate southwestward. In general, cyclones and anticyclones are similar, except for eddies surviving at least 6 months. In this case, after a similar 3–4 months of radius and amplitude growth, amplitudes (or sizes) decay particularly rapidly for anticyclonic (or cyclonic) eddies. In terms of intensity, cyclonic eddies show a rapid decay during the first 3 months before arriving at a quasi-constant value, whereas anticyclones exhibit steady decline. Finally, eddy temporal variations were examined at seasonal and interannual scales in the “coastal” region favorable to the formation of energetic mesoscale structures. On seasonal scales, eddy activity is maximal in fall and minimum in spring. At interannual scales, the eddy activity index was maximal during the strong El Niño of 1997–1998 but another strong maximum of eddy activity also occurred late in 2004. These temporal variations are probably associated with the intensification of the upwelling thermal front and with the passage of coastal-trapped waves which generate baroclinic instabilities. Further investigation of the mechanisms involved on the eddy genesis is needed.     

Renovated controller designed by genetic algorithms

A novel smart control system based on genetic algorithms (GAs) is proposed in this paper. The system is comprised of three parts: the fiber Bragg grating (FBG) sensor‐based sensing network for structural health monitoring, the GA‐based location optimizer for sensor arrangement, and the GA‐based controller for vibration mitigation under external excitation. To evaluate the performance of the proposed system, an eight‐story steel structure was designed specifically to represent a structure with large degrees of freedom. In total 16 FBG sensors were deployed on the structure to implement the concept of a reliable sensing network, and to allow the structure to be monitored precisely under any loading. The advantage of applying a large amount of information from the sensing system is proven theoretically by the GA‐based location optimizer. This result greatly supports the recent tendency of distributing sensors around the structure. Two intuitive GA‐based controllers are then proposed and demonstrated numerically. It is shown that the structure can be controlled more effectively by the proposed GA‐strain controller than by the GA‐acceleration controller, which represents the traditional control method. A shaking table test was carried out to examine the entire system. Experimental verification has demonstrated the feasibility of using this system in practice. Copyright © 2008 John Wiley & Sons, Ltd.     

基于灰色最小二乘支持向量机的边坡位移预测

利用边坡实测位移序列预测边坡未来时间的位移,可以有效地判断边坡的稳定性。在分析了灰色预测方法和最小二乘支持向量机各自的优缺点的基础上,提出了将二者相结合的一种新的预测模型--灰色最小二乘支持向量机预测模型。新模型既发挥了灰色预测方法中“累加生成”的优点,弱化了原始序列中随机扰动因素的影响,增强了数据的规律性,又充分利用了最小二乘支持向量机求解速度快、易于描述非线性关系的优良特性,避免了灰色预测方法及模型存在的理论缺陷。同时,采用遗传算法进行了模型的参数优化,通过2个工程实例说明灰色最小二乘支持向量机模型预测边坡位移的有效性,具有较高的精度。     

运用遗传算法求解土钉支护结构的整体稳定性系数

以土钉支护结构整体稳定性计算的圆弧滑动简单条分法为基础,运用遗传算法对北京某大厦基坑的土钉支护结构最危险滑移面的位置进行了动态搜索与确定,并计算了其稳定系数。结果表明基坑边坡在实施土钉支护后,其最危险滑移面将后移,同时表明遗传算法能够较准确地确定土钉支护结构最危险滑动面及其相应的整体稳定性系数,且可在优化设计中避免陷入局部最小值,证明了该方法的有效性和准确性。     

实测坑透资料的层析成像特殊处理效果

用坑透层析成像特殊处理算法对4个工作面的实测资料进行了处理,处理结果检测了算法的可行性、分辨率,检验了算法的稳定性和抗噪能力。