Testing Foundations of Biological Scaling Theory Using Automated Measurements of Vascular Networks

Scientists have long sought to understand how vascular networks supply blood and oxygen to cells throughout the body. Recent work focuses on principles that constrain how vessel size changes through branching generations from the aorta to capillaries and uses scaling exponents to quantify these changes. Prominent scaling theories predict that combinations of these exponents explain how metabolic, growth, and other biological rates vary with body size. Nevertheless, direct measurements of individual vessel segments have been limited because existing techniques for measuring vasculature are invasive, time consuming, and technically difficult. We developed software that extracts the length, radius, and connectivity of in vivo vessels from contrast-enhanced 3D Magnetic Resonance Angiography. Using data from 20 human subjects, we calculated scaling exponents by four methods--two derived from local properties of branching junctions and two from whole-network properties. Although these methods are often used interchangeably in the literature, we do not find general agreement between these methods, particularly for vessel lengths. Measurements for length of vessels also diverge from theoretical values, but those for radius show stronger agreement. Our results demonstrate that vascular network models cannot ignore certain complexities of real vascular systems and indicate the need to discover new principles regarding vessel lengths

Vibration Reduction of Mistuned Bladed Disks via Piezoelectric-Based Resonance Frequency Detuning

Recent trends in turbomachinery blade technology have led to increased use of monolithically constructed bladed disks (blisks). Although offering a wealth of performance benefits, this construction removes the blade-attachment interface present in the conventional design, thus unintentionally removing a source of friction-based damping needed to counteract large vibrations during resonance passages. This issue is further exacerbated in the presence of blade mistuning that arises from small imperfections from otherwise identical blades and are unavoidable as they originate from manufacturing tolerances and operational wear over the lifespan of the engine. Mistuning is known to induce vibration localization with large vibration amplitudes that render blades susceptible to failure induced by high-cycle fatigue. The resonance frequency detuning (RFD) method reduces vibration associated with resonance crossings by selectively altering the blades\u27 structural response. This method utilizes the variable stiffness properties of piezoelectric materials to switch between available stiffness states at some optimal time as the excitation frequency sweeps through a resonance. For a single-degree-of-freedom (SDOF) system, RFD performance is well defined. This research provides the framework to extend RFD to more realistic applications when the SDOF assumption breaks down, such as in cases of blade mistuning. Mistuning is inherently random; thus, a Monte Carlo analysis performed on a computationally cheap lumped-parameter model provides insight into RFD performance for various test parameters. Application of a genetic algorithm reduces the computational expense required to identify the optimal set of stiffness-state switches. This research also develops a low-order blisk model with blade-mounted piezoelectric patches as a tractable first step to apply RFD to more realistic systems. Application of a multi-objective optimization algorithm produces Pareto fronts that aid in the selection of the optimized patch parameters. Experimental tests utilizing the academic blisk with the optimized patches provides validation

Development of a Bonner Sphere neutron spectrometer from a commercial neutron dosimeter

Bonner Spheres have been used widely for the measurement of neutron spectra with neutron energies ranged from thermal up to at least 20 MeV . A Bonner Sphere neutron spectrometer (BSS) was developed by extending a Berthold LB 6411 neutron-dose-rate meter. The BSS consists of a 3He thermal-neutron detector with integrated electronics, a set of eight polyethylene spherical shells and two optional lead shells of various sizes. The response matrix of the BSS was calculated with GEANT4 Monte Carlo simulation. The BSS had a calibration uncertainty of ± 8.6% and a detector background rate of (1.57 ± 0.04) × 10−3 s−1. A spectral unfolding code NSUGA was developed. The NSUGA code utilizes genetic algorithms and has been shown to perform well in the absence of a priori information.postprin

Dynamic tailoring of beam-like structures. Application to High Aspect Ratio unitized box-beam and internal resonant structures

This work is a journey into the dynamic tailoring of beam-like structures which aims to exploit unconventional couplings and nonlinearities to enlarge the design space and improving the performances of engineering systems. Particularly, two examples pertaining dynamic tailoring of aerospace and mechanical systems are investigated in depth. In the first case, the work aims to attain a desired structural performance exploiting typical nonlinear structural phenomena and unconventional couplings offered by the unitized structures. As for the unitized structures, the present work, derives two equivalent plate models of curvilinear stiffened panels namely, constant (or homogenized) stiffness model and variable stiffness model. The models are assessed through finite element analysis. In the spirit of CAS (Circumferentially Asymmetric Stiffness), the equivalent plate stiffness’s are used to determine the cross- sectional beam stiffness’s. The governing equations for the Euler-Bernoulli, anisotropic beam with variable stiffness are derived and then used to address the optimization problem. The objective of the optimization is to attain a desired static or dynamic performance of the unitized beam exploiting the enlarged design space which arises from the stiffness variability and the unconventional couplings. In the second type of system analyzed, the aim is synthesize meaningful topologies for planar resonators. The topology optimization is addressed using as initial guess a ground structure. Motivated by the results of the optimization, a generalized reduced order model is derived for multi-members beam structures. The generalized model have been then specialized for three cases namely, V- Y- and Z-shaped resonators. The analytical solution for the V-shaped resonator is also derived along with the electro-mechanical equations of motion. Different solutions are studied aiming at investigating the effect of the folding angle on to the performances of a V-shaped harvester. Beside the study of the static and dynamic behavior of the systems, the thesis presents two novel optimization algorithms namely, the Stud^P GA and the GERM. The Stud^P GA, is a population based algorithm conceived to enhance the exploration capabilities, and hence the convergence rate, of classical GA. The Stud^P GA has been preliminary assessed through benchmark problems for composite layered structure and then used for the optimization of the stiffeners' path aiming at attaining a desired static or dynamic performances. The GERM (Graph-based Element Removal Method), is a double filtering technique conceived for the topology synthesis of planar ground structures. The GERM has been used, in combination with a standard GA, to address the topology optimization problem of the two types of system namely, planar resonator and compliant structures. The work introduces also the concept of trace-based scaling for predicting the behavior of anisotropic structures. The effectiveness of the trace-based scaling is assessed through comparison between scaled and analytical performances of anisotropic structures

Performance-Based Economical Seismic Design of Multistory Reinforced Concrete Frame Buildings and Reliability Assessment

As the next generation of seismic design methodology, performance-based seismic design (PBSD) method requires a structure satisfy multiple preselected performance levels under different hazard levels. Optimal PBSD methods provide different strategies to design the numerous variables, including strength, stiffness and ductility of each structural component. The overall goal of this study is to develop a new optimal PBSD method for multi-story RC moment frames. This method is capable of overcoming the deficiencies of existing optimal PBSD methods and can be implemented by the U.S. design practice. The proposed method minimizes construction cost and takes the limit of member plastic rotation and optionally inter-story drift as optimization constraints. Other seismic design requirements reflecting successful design practice are also incorporated. Simplification is made by reducing design variables into two, one for the overall system stiffness and the other for the overall system strength. The optimization contains two stages, the determination of feasible region boundary in normalized strength and stiffness domain and optimization in the material consumption domain. Capacity spectrum method, which jointly considers nonlinear static analysis and inelastic design spectrum, is used to estimate the global and local deformation demands at the peak dynamic response. The proposed optimization approach is applied to the design of a six-story four-bay reinforced concrete frame. The optimal design results indicate that 30% of needed flexural strength and 26% of the cross-sectional area can be reduced from the initial strength-based design of this prototype structure. Nonlinear time-history analyses are conducted on the optimized structure using ten historical ground motions scaled to represent three levels of seismic hazard. In general, the average peak dynamic response meets the target performance requirements under the three levels of seismic hazard. Structural reliability analyses are applied on the optimal structure, the original structure and other 26 structures with different overall system stiffness and strength. The effects on nonperformance probability are determined based on the nonperformance contours, which is generated based on the reliability analyses results of all the 28 structures. To ensure the probabilities of nonperformance due to either plastic hinge or inter-story drift rotation is lower than the limits of all three preselected performance levels, the prototype structure should be design based on the relative overall system stiffness larger than 0.84 and the relative overall system strength larger than 0.4. To ensure that the probabilities of nonperformance only due to plastic hinge is lower than the limits of all three preselected performance levels, the prototype structure should be design based on two cases of relative strength and relative stiffness: (1) the relative overall system stiffness is larger than 0.75 and the relative overall system strength is larger than 0.4, and (2) the relative overall system stiffness is larger than 0.65 and the relative overall system strength is larger than 0.45. To ensure that the probabilities of nonperformance only due to inter-story drift rotation is lower than the limits of all three preselected performance levels, a structure should be design based on the relative overall system stiffness larger than 0.85 and the relative overall system strength larger than 0.6

Competent Program Evolution, Doctoral Dissertation, December 2006

Heuristic optimization methods are adaptive when they sample problem solutions based on knowledge of the search space gathered from past sampling. Recently, competent evolutionary optimization methods have been developed that adapt via probabilistic modeling of the search space. However, their effectiveness requires the existence of a compact problem decomposition in terms of prespecified solution parameters. How can we use these techniques to effectively and reliably solve program learning problems, given that program spaces will rarely have compact decompositions? One method is to manually build a problem-specific representation that is more tractable than the general space. But can this process be automated? My thesis is that the properties of programs and program spaces can be leveraged as inductive bias to reduce the burden of manual representation-building, leading to competent program evolution. The central contributions of this dissertation are a synthesis of the requirements for competent program evolution, and the design of a procedure, meta-optimizing semantic evolutionary search (MOSES), that meets these requirements. In support of my thesis, experimental results are provided to analyze and verify the effectiveness of MOSES, demonstrating scalability and real-world applicability