Anne Raich

Reliability-based optimal design of electrical transmission towers using multi-objective genetic algorithms

A hybrid methodology for performing reliability-based structural optimization of three-dimensional trusses is presented. This hybrid methodology links the search and optimization capabilities of multi-objective genetic algorithms (MOGA) with structural performance information provided by finite element reliability analysis. To highlight the strengths of the proposed methodology, a practical example is presented that concerns optimizing the topology, geometry, and member sizes of electrical transmission towers. The weight and reliability index of a tower are defined as the two objectives used by MOGA to perform Pareto ranking of tower designs. The truss deformation and the member stresses are compared to threshold values to assess the reliability of each tower under wind loading. Importance sampling is used for the reliability analysis. Both the wind pressure and the wind direction are considered as random variables in the analysis. The research results presented demonstrate the benefit of implementing MOGA optimization as an integral part of a reliability-based optimization procedure for three-dimensional trusses.

Multi-objective genetic algorithms for cost-effective distributions of actuators and sensors in large structures

This paper proposes a multi-objective genetic algorithm (MOGA) for optimal placements of control devices and sensors in seismically excited civil structures through the integration of an implicit redundant representation genetic algorithm with a strength Pareto evolutionary algorithm 2. Not only are the total number and locations of control devices and sensors optimized, but dynamic responses of structures are also minimized as objective functions in the multi-objective formulation, i.e., both cost and seismic response control performance are simultaneously considered in structural control system design. The linear quadratic Gaussian control algorithm, hydraulic actuators and accelerometers are used for synthesis of active structural control systems on large civil structures. Three and twenty-story benchmark building structures are considered to demonstrate the performance of the proposed MOGA. It is shown that the proposed algorithm is effective in developing optimal Pareto front curves for optimal placement of actuators and sensors in seismically excited large buildings such that the performance on dynamic responses is also satisfied.

Multi-objective Optimization of Sensor and Excitation Layouts for Frequency Response Function-Based Structural Damage Identification

Abstract:i¾?The accuracy of many damage identification methods depends significantly on the quality of measurements collected by sensors, such as accelerometers, concerning the response characteristics of a structure. Often the number of sensors used to collect measurements is limited due to available funds, equipment, and access. In addition, the excitation location can significantly affect a sensors ability to collect quality measurement information. Therefore, both the location and number of sensors and the location of the excitation must be optimized to maximize the quality of information collected. A multi-objective optimization approach is presented that minimizes the number of sensors specified while maximizing the sensitivity of the frequency response functions FRFs collected at each specified sensor location with respect to all possible damaged structural elements. The multiple Pareto-optimal sensor/excitation layouts obtained aid in determining the number of sensors required to obtain an effective level of measurement information. The benefit of using Pareto-optimal sensor/excitation layouts is investigated by using the optimized layouts to collect measurement information for a FRF-based structural damage identification method. Trial results confirm that an increase in damage identification accuracy and efficiency is achieved when Pareto-optimal sensor/excitation layouts are used instead of nonoptimal layouts. In addition, the Pareto-optimal layouts improved damage identification accuracy in noisy measurement environments due to increasing the quality of measurements collected.

Multi-objective optimization for actuator and sensor layouts of actively controlled 3D buildings

This paper investigates the multi-objective optimization of active control systems for vibration control of three-dimensional (3D) high-rise buildings under a variety of earthquake excitations. To this end, a novel multi-objective genetic algorithm is developed through the integration of the best features of a non-dominated sorting II (NS2) genetic algorithm (GA) and an implicit redundant representation (IRR) GA. The proposed NS2-IRR GA finds not only minimum distributions of both actuators and sensors within structures, but also minimum dynamic responses of 3D structures. Linear quadratic Gaussian controllers, hydraulic actuators and accelerometers are used for implementation of active control systems within the 3D buildings. To demonstrate the effectiveness of the proposed NS2-IRR GA, two 3D building models are investigated using finite element methods, including low- and high-rise buildings. It is shown that the proposed NS2-IRR GA is effective in finding not only optimal locations and numbers of both actuators and sensors in 3D buildings, but also minimum responses of the 3D buildings. The simulation also shows that the control performances of the proposed approach significantly enhance those of the engineering judgment oriented benchmark layout, which is validated by comparisons of each performance using the same number of actuators.

Implicit representation in genetic algorithms using redundancy

A new representation combining redundancy and implicit fitness constraints is introduced that performs better than a simple genetic algorithm (GA) and a structured GA in experiments. The implicit redundant representation (IRR) consists of a string that is over-specified, allowing for sections of the string to remain inactive during function evaluation. The representation does not require the user to prespecify the number of parameters to evaluate or the location of these parameters within the string. This information is obtained implicitly by the fitness function during the GA operations. The good performance of the IRR can be attributed to several factors: less disruption of existing fit members due to the increased probability of crossovers and mutation affecting only redundant material; discovery of fit members through the conversion of redundant material into essential information; and the ability to enlarge or reduce the search space dynamically by varying the number of variables evaluated by the fitness function. The IRR GA provides a more biologically parallel representation that maintains a diverse population throughout the evolution process. In addition, the IRR provides the necessary flexibility to represent unstructured problem domains that do not have the explicit constraints required by fixed representations.

Development of Pervious Concrete Pile Ground-Improvement Alternative and Behavior under Vertical Loading

Permeable granular columns are used to increase the time rate of consolidation, reduce liquefaction potential, improve bearing capacity, and reduce settlement. However, their behavior depends on the confinement provided by surrounding soil, which limits their use in very soft clays and silts, and organic and peat soils. This research effort aims to develop a new ground-improvement method using pervious concrete piles. Pervious concrete piles provide higher stiffness and strength that are independent of surrounding soil confinement while offering permeability comparable to granular columns. This proposed ground-improvement method can improve the performance of different structures supported on poor soils. To achieve the goal of the research project, four vertical load tests were performed on one granular column and three pervious concrete piles. In this paper, the material properties of pervious concrete, the developed installation method, and the vertical load response of pervious concrete and aggregate piles are presented, and the variation of soil stresses and displacement during pile installation are briefly discussed. The experimental test results show that the ultimate load capacity of the pervious concrete pile was 4.4 times greater than that of an identical granular column. In addition, the ultimate load capacity of a pervious concrete pile installed using the developed technique was 2.6 times greater than a precast pervious concrete pile. The used installation method created nonuniform lateral soil displacement and increased vertical and horizontal soil stresses.

Soil-Pile Interaction for a Small Diameter Pile Embedded in Granular Soil Subjected to Passive Loading

AbstractThe soil-structure interaction of piles used to stabilize failing slopes (i.e., subjected to lateral soil movement known as passive piles) was experimentally investigated using a state-of-the-art soil-structure interaction facility. A 102-mm diameter, 1.58-m-long precast concrete pile was installed in well-graded sand. The pile was instrumented with displacement and tilt gauges at the pile head and strain gauges, a flexible shape acceleration array, and thin tactile pressure sheets along the pile length. Furthermore, the three-dimensional (3D) movements of the soil surface and the top of the pile were monitored using two stereo digital image correlation (DIC) systems. By monitoring the relative movement of the soil surface and pile top, the DIC systems track the progression of the soil-pile interaction that occurs as the lateral displacement of the soil increases. The use of advanced sensors allows simultaneous measurement of the pile lateral movement and the soil-pile interaction pressures along ...

Behavior and Soil–Structure Interaction of Pervious Concrete Ground-Improvement Piles under Lateral Loading

AbstractGranular column ground-improvement methods are widely used to improve bearing capacity and provide a drainage path. However, the behavior of granular columns depends on the confinement provided by the surrounding soil, which limits their use in poor soils. A new ground-improvement method is proposed using pervious concrete piles to provide high permeability while also providing higher stiffness and strength, which are independent of surrounding soil confinement. Building on prior research on the behavior of vertically loaded pervious concrete piles and granular columns, this paper investigates the behavior of laterally-loaded pervious concrete piles and the effects of installation on their response. Two fully-instrumented lateral load tests were conducted on a precast and cast-in-place pile using different installation methods. Advanced sensors measured the soil–structure interaction during installation and under lateral loading. Test results confirmed that laterally-loaded pervious concrete groun...

Modeling of User Design Preferences in Multiobjective Optimization of Roof Trusses

AbstractMany conceptual design programs determine optimality by relying on quantifiable design objectives such as minimizing weight and deflection. Qualitative design criteria related to architectural or constructability requirements, however, are not typically considered. This paper presents a preference-prediction model that evaluates user preference as an explicit design objective in the topology and geometry optimization of roof trusses. During optimization, each truss design is characterized by using a set of nine quantifiable features. A trained neural network inputs the characteristic truss feature values for each proposed design and outputs an integer value that indicates the user’s preference for that design. To reduce the number of user interactions required to collect the required neural network training data, a Kohonen self-organizing map clusters designs into groups on the basis of feature similarities. Clustering allows users to indicate preferences for groups of similar trusses instead of f...

Measured Soil-Pile Interaction Pressures for Small-Diameter Laterally Loaded Pile in Loose Sand

The Soil-Structure Interaction (SSI) facility at Lafayette College, which was funded by the National Science Foundation, was recently used to investigate the soilpile interaction for laterally loaded piles with the main focus on the interaction pressure between the pile and surrounding soil. A precast concrete pile, that was 101.6 mm in diameter and 1.17 m long, was reinforced with one No. 4 rebar (diameter = 12.7 mm) located at the center of the pile cross-section. The pile was instrumented with strain gauges along the length of the pile, displacement and tilt gauges at the point of loading, displacement sensors along the length of the pile, and thin pressure sensors wrapped around the pile. The soil, which was rained around the pile, was classified as well-graded sand. This paper focuses on measuring the soil-pile interaction pressure for a laterally loaded pile. The paper also describes the installation procedure, the soil properties, the measured pile force-displacement relationship and the measured strain along the length of the pile. Measured interaction pressures present the first step to develop the soil force-displacement relationship (i.e., the soil reaction or the p-y curve) based on direct measurements. The experiment described in this paper presents the initial effort of the research team, which will be followed by further experimental work focusing on the behavior of laterally loaded piles in soft soils.