Dept. of Civil and Environmental Engineering
http://hdl.handle.net/2142/3518
Fri, 17 Apr 2015 23:10:04 GMT2015-04-17T23:10:04ZFlexible transit network design with and without branching under spatially heterogeneous demand
http://hdl.handle.net/2142/73106
Flexible transit network design with and without branching under spatially heterogeneous demand
While public transportation systems are usually designed with fixed routes, this work presents an alternative flexible-route transit system. Flexible transit vehicles do not operate on fixed paths but travel within predetermined areas in response to trip demand in order to provide door-to-door service. The main advantage of this system is that passenger access time to and from transit stops is removed. To design the optimal route layout and service operation, continuum approximation is used to reduce the computation burden and formulate the problem in terms of a few decision variables. Unlike many continuous models, passenger distribution is not assumed to be homogeneous over space. Since travel patterns are typically not uniform in urban and suburban areas, this thesis will consider a heterogeneous passenger distribution. In order to adapt to both global and local demand variations, several transit system designs will be investigated. Thus, the purpose of this thesis is (i) to investigate the benefits of Daganzo (2010a) hybrid structure over grid structure under heterogeneous demand with flexible routes; and (ii) to investigate the benefits of allowing branching local tubes within the transit system. For (i), we derive the agency and user cost metrics of the proposed models and seek optimal network layout, service area of each bus and bus headway, to minimize the total generalized cost. For (ii), we use the framework provided by Ouyang et al. (2014) and the power-of-two concept from Roundy (1985) to design a grid flexible transit network with local tubes. The same cost metrics as in (i) are derived on a local scale. Considering a low-to-moderate demand level and several spatially heterogeneous demand distributions, it is found out that hybrid structure is beneficial over grid structure, and that transit network with local tubes allows a reduction of the system cost, with respect to a homogeneous transit network. A sensitivity analysis is performed on the branching structure design. It is found that branching does not depend on the total number of passengers. Finally several future research leads are presented to enhance the transit network design.
flexible transit; hybrid network; branching
Wed, 21 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2142/731062015-01-21T00:00:00ZAdvancing sustainable wastewater treatment: elucidating tradeoffs among emerging resource recovery technologies through quantitative sustainable design
http://hdl.handle.net/2142/73098
Advancing sustainable wastewater treatment: elucidating tradeoffs among emerging resource recovery technologies through quantitative sustainable design
Anthropogenic activities are negatively impacting the environment through biodiversity loss, altering nutrient cycles, and increases in severe weather events. These impacts are subsequently hindering the ability of wastewater treatment plants (WWTPs) to protect human and environmental health. In addition, the field of wastewater engineering is facing several problems that must be addressed in the coming decades, such as aging infrastructure and stricter effluent discharge requirements. Wastewater treatment is currently primarily based on the cultivation of aerobic heterotrophs and though it provides a high-quality effluent, it is also energy intensive. High energy demand is costly both economically and environmentally. These problems underlie a need to re-envision WWTPs as a resource capable of nutrient and energy recovery while continuing to hold human and environmental health paramount.
In order to compare possible approaches to solving the problems facing wastewater treatment, a critical review was conducted comparing several anaerobic and phototrophic technologies to determine their potential for energy positive domestic wastewater treatment. Phototropic processes were shown to be able to produce 280-400% greater energy than anaerobic processes producing methane (on a per m3 basis). However, phototrophic processes increase chemical oxygen demand (COD), so a downstream process is also necessary. Anaerobic membrane bioreactors (AnMBRs) were found to have the highest consistent COD removal (80-90%) of the anaerobic processes, but also had high energy consumption. Though they are a new technology, AnMBRs show promise for full-scale domestic wastewater treatment, but because there are many different designs available, research on the topic varies greatly. An in-depth examination of AnMBR designs was conducted utilizing quantitative sustainable design to elucidate configurations that limit economic or environmental impacts under the assumption that all designs treat wastewater to the same effluent quality. The results show that certain design decisions have a profound impact on the total net present cost and life cycle environmental impacts. Therefore, recommendations for future research are made that traverse the relative benefits and detriments of different AnMBR configurations.
Anaerobic MBR (AnMBR); Sustainability; Quantitative Sustainable Design (QSD); Wastewater Treatment; Anaerobic Technologies; Phototrophic Technologies; Resource Recovery; Energy Positive
Wed, 21 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2142/730982015-01-21T00:00:00ZTransit network design for areas with low and/or heterogeneous demand
http://hdl.handle.net/2142/73089
Transit network design for areas with low and/or heterogeneous demand
Low density and spatial heterogeneity in transit demand impose considerable challenges to both transit riders and service agencies. For example, lower demand forces transit agencies to provide sparser and less accessible service so as to stay economical, which however further deteriorates passenger experience and deters patronage. Spatially heterogeneous demand as well as city street characteristics (e.g., network layout) calls for variation in transit service, which often leads to higher system costs and undesirable passenger experience (e.g., transfers) as well.
This dissertation proposes a series of transit network design methods that can be used to improve transit service under these circumstances. It first presents an alternative flexible-route transit system for low demand areas, in which each bus is allowed to travel across a predetermined area to serve passengers, while these bus service areas collectively form a hybrid “grand” structure that resembles hub-and-spoke and grid networks. We analyze the agency and user cost components of this proposed system in idealized square cities and seek the optimum network layout, service area of each bus, and bus headway to minimize the total system cost. We compare the performance of the proposed transit system with that of other conventional systems (e.g., fixed-route transit network and taxi service), and show which system is advantageous under different passenger demand levels. It is found that under low-to-moderate demand levels, the proposed flexible-route system has the lowest overall system cost.
In the second part of this dissertation, a methodological framework is developed so that continuum approximation (CA) techniques can be used to design bus networks for cities where travel demand varies gradually over space. The bus-route configurations consist of (i) a main, city-wide grid with relatively large physical spacings between its parallel routes and the stops along those routes; together with (ii) one or more local grids with more closely-spaced routes and stops that serve neighborhoods of higher-demand densities. The so-called power-of-two concept is borrowed from the field of inventory control, and is enforced so that the local grids can be embedded seamlessly within the main one. Numerical experiments illustrate the value of the resulting heterogeneous route configurations, which have the potential to reduce the costs to both the bus users and the operating agency, as compared against the costs of the optimal homogeneous bus-route grids. Differences of about 5-10% are observed for a set of numerical examples that cover a wide range of demand distribution patterns. Most of the savings are due to the diminished access costs that users incur when high-demand neighborhoods are served by local grids with closely-spaced routes and stops.
The same CA methodology is used to design a simplified grid network system with variable bus spacings that can address spatially heterogeneous demand. The continuum approximation enables us to estimate the cost components of the system locally and design the system layout accordingly. The simplified grid system varies the bus line spacings, which makes the network more responsive to the varying demand. It saves user costs in relatively high demand areas and saves agency costs in lower demand areas. Numerical results show that the design can improve the total cost of the system by between 4% and 6% as compared with traditional grid designs under the chosen demand distribution patterns.
We further extend the network design framework from grid city street networks to a radial one, where buses can travel either radially (from center to outer part and vice versa) or circularly (clockwise and counterclockwise along rings). Using the CA method, we analyze user and agency costs and propose a design framework that minimizes the total system cost. The optimum design provides the bus spacings of the radial and circular lines and the bus headway. Numerical results show that the proposed method can be useful to design an efficient system when the city streets form a ring-radial network.
The last part of this dissertation is devoted to real-world applications of the proposed design methods. We apply the flexible-route transit network to satisfying evening/night demand in the campus area of Urbana-Champaign, which is currently covered by a manually dispatched “Safe-Ride” system. The new transit system is shown to outperform the current system and achieve several improvements. We also design a new transit network for the City of Weihai in China, where the network includes both grid and polar network components to best serve the city’s geographical layout. Numerical experiments also give insights on the influence of key decision variables such as bus line spacing, stop spacing, and headway under different design schemes.
Structured Flexible Transit System; Low Demand Areas; Continuum Approximation; Spatially Heterogeneous Demand; Grid Network; Polar System
Wed, 21 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2142/730892015-01-21T00:00:00ZDevelopment of algorithms for asphalt pavement compaction monitoring utilizing ground penetrating radar
http://hdl.handle.net/2142/73067
Development of algorithms for asphalt pavement compaction monitoring utilizing ground penetrating radar
The density of asphalt mixture plays an important role in the performance of asphalt pavement. Compaction is critical for achieving the desired density during the construction of asphalt pavement. To ensure successful compaction, the density of asphalt pavement should be monitored in a timely manner, and the information should be fed back to the compactor operator to avoid under-compaction or over-compaction. This study proposes a technique based on ground penetrating radar (GPR) for monitoring the density of asphalt pavement during compaction continuously, non-destructively, and in real time.
The utmost challenge in developing this technique is to eliminate the effect of surface moisture, sprayed by the compactor during compaction, on GPR data. The increase of asphalt pavement density and surface moisture content can cause an increase in the amplitude of the reflection pulse in the GPR signals in time domain. To extract density information without the effect of surface moisture, numerical simulation, laboratory experiments, and field tests were conducted.
First, the difference between the effect of surface moisture variation and the effect of density variation on GPR signal was investigated. Numerical simulation was performed using the finite-difference time-domain (FDTD) method to study the propagation of GPR wave within pavement structure. Both simulation results and laboratory experimental results revealed the fundamental difference between the two effects: In frequency domain, the high frequency components of the GPR pulse is sensitive to density variation and variation of surface moisture content, and the low frequency components are only sensitive to the density variation. The difference between the two effects is referred to as the “frequency-selective effect” in this dissertation.
Second, based on the findings of the “frequency-selective effect”, a “correction algorithm” was developed based on the “reference scan approach” to eliminate the effect of surface moisture and to extract density information. To develop and validate the algorithm, a full-scale test site was constructed with compaction pass number from 0 to 10, and a large amount of GPR data was collected from the pavement with different surface moisture contents. A total of 22 cores were taken for validation purposes. After applying the algorithm, it was found that the average density prediction error was reduced from 3.1% to 0.9%, thus indicating the effectiveness of the algorithm. The GPR system was tested in a field construction site. The system successfully monitored the density change after each roller pass during compaction. The density estimation results obtained from GPR after the final compaction had higher accuracy than the density results obtained from the nuclear density gauge.
Asphalt Compaction; Ground Penetrating Radar (GPR); Compaction Monitoring
Wed, 21 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2142/730672015-01-21T00:00:00ZExperimental evaluation of monotonic and cyclic fracture behavior using disk-shaped compact tension test and released energy approach
http://hdl.handle.net/2142/73043
Experimental evaluation of monotonic and cyclic fracture behavior using disk-shaped compact tension test and released energy approach
This thesis involves the evaluation of fracture behavior of asphalt concrete under monotonic and cyclic loading using the disk-shaped compact tension (DC(T)) test and a released-energy based approach. The standard DC(T) test was revised to facilitate both monotonic and cyclic loading tests, including some modifications of the test geometry and testing modes. The research was motivated to explore possible extensions of the DC(T) test device to consider cyclic fracture phenomena such as cyclic thermal cracking, block cracking and reflective cracking. Five different asphalt concrete mixtures were tested for both loading mechanisms across four test temperatures (-12, 0, 10, and 20oC). After an extensive exploratory stage, the load-controlled testing mode utilizing a sine waveform and a frequency of 0.5 Hz with no rest period were selected as the main testing parameters for this study. In addition, peak load obtained from the monotonic DC(T) test was used as a reference value for determining loading magnitudes of the cyclic DC(T) test for a given mixture and test temperature. For data analysis, the released energy approach was introduced as a key concept to characterize the cyclic fracture data generated in this study. Stemming from this approach, a released energy rate parameter, R2, was identified with the characteristic of mixture and temperature independence. By correlating a fracture energy parameter (Gf) to released energy rate (R2), cyclic loading behavior could be predicted based upon three different data sets deriving from the DC(T) test: one involving a comprehensive cyclic loading testing suite; a slightly simpler method involving a limited number of required cyclic tests, and; a highly simplified approach where cyclic fracture behavior was predicted form monotonic fracture test results alone (standard DC(T) fracture energy). All three prediction methods were shown to be plausible, but as expected, the more rigorous the testing suite, the more accurate the prediction. Furthermore, monotonic and cyclic fracture behaviors were monitored using a webcam-based imaging technique to investigate fracture processes at a macro-scale level. As a result, each stage of cracking, including crack initiation and crack propagation, could be potentially predicted based on the cyclic test data through a relation of the crack initiation to number of cycles to a failure and crack propagation ratios, respectively.
Monotonic Fracture; Cyclic Fracture; Released Energy; disk-shaped compact tension (DC(T)) Test; Fatigue Test
Wed, 21 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2142/730432015-01-21T00:00:00ZFate and transport of Asian carp eggs in spawning rivers
http://hdl.handle.net/2142/73041
Fate and transport of Asian carp eggs in spawning rivers
In recent years the population of Asian carp has increased exponentially in the Mississippi River Basin. This invasive species are filter feeders that consume phytoplankton and zooplankton thus competing directly with native species as their diets overlap. Asian carp can lay thousands of eggs and have the potential to spawn up to three times per year. Moreover, there is a growing concern about Asian carp invading the Great Lakes, which could cause negative ecological and economic impact. Asian carp eggs are semi-buoyant and must remain suspended in the water column to survive, supported by the turbulence of the flow, until they hatch and develop the ability to swim. Determining if Asian carp will use a given river for spawning and recruitment is typically determined by comparing a river to those where spawning and recruitment were observed. This observation-based technique has led to general guidelines about the river length and hydraulic characteristics required for Asian carp spawning and recruitment. Previous estimates of the minimum river length or stream velocities required to keep eggs in suspension have not consider the non linearity of the hatching dynamics of different river systems. In reality, minimum river length (drifting time) required for egg hatching depends primarily on water temperature and the river's hydrodynamics. Today, there is no a clear understanding and consensus about the hydrodynamic conditions at which eggs are transported and remain in suspension.
In this thesis, we developed the Fluvial Egg Drift Simulator (FluEgg), a three-dimensional Lagrangian model to simulate the transport dynamics of Asian carp eggs. FluEgg tracks individual virtual eggs as they drift through the current during the life stages before hatching. The FluEgg model incorporates information about Asian carp egg development and river hydrodynamics to provide insights regarding: (i) the likelihood of a river to be suitable for spawning, (ii) the potential of a river to transport Asian carp eggs in suspension until hatching, and (iii) the identification of the location of Asian carp eggs at different developmental stages. This research contributes valuable information about the transport, and dispersal patterns of Asian carp eggs, and assists in the identification of critical hydrodynamic conditions that maintain eggs in suspension. The FluEgg model was applied to two Great Lakes tributaries to predict transport and dispersion of Asian carp eggs in two different river systems. Results depict the dynamic component associated with egg transport and dispersion, and egg-hatching risk due to the interactive relation between river length, hydrodynamic characteristics, and water temperatures. Results indicate that drifting distances to enable hatching depend strongly on the river hydrodynamics and on the water temperature. Therefore, depending on the environmental and hydrodynamic characteristics of the river, drifting distances can be much shorter than the 100 km previously assumed to be adequate based on the observation of native spawning rivers. However, as the developmental rates of Asian carp eggs depend on water temperature, small changes in temperature might result in longer river reaches to support egg hatching.
Going one step further from the numerical modeling of the transport and dispersion of Asian carp eggs, laboratory experiments using surrogate eggs mimicking the physical properties of water-hardened eggs, were performed in a temperature controlled recirculatory flume with a sand bed. Surrogate eggs were allowed to drift under different velocity conditions. Egg drifting behavior, and suspension and settling dynamics were observed. It was observed that at high velocities (V≥ 0.2 m/s) eggs were suspended and distributed throughout the water column, eggs that touched the sand bed were re-entrained by the flow. At lower velocities (V≥ 0.57m/s) some settling of the eggs was observed. Egg settling zones were located in the sand bed near the walls of the flume and in the lee side of the bedforms.
In summary, my research explains the dynamics of the transport and fate of Asian carp eggs in spawning rivers by using numerical simulations performed by the FluEgg model together with laboratory experiments using surrogate eggs. Results from this thesis are useful for scientists, managers, and stakeholders both to improve their understanding of drifting behavior of Asian carp in early life stages, that is before the eggs hatch and develop the ability to swim, and to facilitate their decision making processes. Finally, the FluEgg model can not only be used as a tool to evaluate the transport of Asian carp eggs but also to simulate the transport of eggs of other fish species, and assess the transport of other passive particles.
FluEgg; Asian carp; Eggs, Lagrangian model; Spawning; Turbulence; Individual-based model (IBM); Synthetic eggs; Laboratory experiments; Suspension; Settling
Wed, 21 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2142/730412015-01-21T00:00:00ZOn-line model updating in earthquake hybrid simulation
http://hdl.handle.net/2142/73040
On-line model updating in earthquake hybrid simulation
Hybrid simulation has emerged as a relatively accurate and efficient tool for the evaluation of structural response under earthquake loading. In the conventional hybrid simulation, the responses of few critical components are obtained by testing while the numerical module is assumed to follow an analytical idealization. Where there is a much larger number of analytical components compared to the experimental parts, the overall response may be dominated by the idealized parts hence the value of hybrid simulation is diminished. It is proposed to update the behavior of the material constitutive relationship of the numerical model during the test, based on the data obtained from the physically tested component.
Identifying the parameters that govern the constitutive relationship behavior from the experimental module is a challenging task. Hence, an approach based on optimization tools is developed to determine the model parameters that minimize the error between the numerical and experimental modules. Interior point methods and genetic algorithms are adopted as gradient and non-gradient optimization tools, respectively. Each of which provides different features that are suitable for various types of applications in earthquake response assessment. On the other hand, neural network is utilized as an alternative identification approach. Neural network is advantageous in case the analytical constitutive relationships are not suitable to represent the actual model behavior, as it can be trained independent from analytical guidance to find the mathematical formulas that correlate the input strain to the output stresses.
UI-SIMCOR the platform utilized to conduct the hybrid simulation analyses. It can communicate with several finite element programs. Amongst others, ZeusNL is used to analyze the numerical modules due to its efficiency in representing cases of extreme loading and non-linear problems. For model updating purposes, the source codes and the communication protocols between UI-SIMCOR and ZeusNL are modified to be able to exchange the stress-strain information during the hybrid simulation test. Several steel and concrete constitutive models included in ZeusNL library are implemented in the proposed approach. In addition, the components required for the neural network procedure are introduced to the program.
The scope of the work also includes verifying the model updating concept through analyzing several numerical problems. These problems include the assessment of regular and irregular structural systems. Moreover, it is shown that through updating the parameters of a simple constitutive model, it can capture the behavior of a more advanced one. Additionally, a number of previously conducted experiments are investigated. A procedure is presented to determine the constitutive model information from the tested component. This procedure is implemented to identify the constitutive model parameters representing a steel beam-column connection and a multi-bay concrete bridge subjected to combined loading. The identified parameters are then utilized to update the analytical model incrementally. The results of both examples show the effectiveness of model updating in minimizing the errors, compared to the pure analytical solution. The proposed approach is expected to enhance the capability of conventional hybrid simulation test to assess structures with several critical components such as high-rise buildings and multi-bay bridges.
Model Updating; Hybrid Simulation; Earthquake Engineering; Optimization; Neural Networks
Wed, 21 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2142/730402015-01-21T00:00:00ZStochastic prediction of collapse of building structures under seismic excitations
http://hdl.handle.net/2142/73033
Stochastic prediction of collapse of building structures under seismic excitations
Modern seismic design provisions help enhance life safety of building occupants during a strong earthquake-shaking event by ensuring acceptably small likelihood of structural collapse. Therefore, accurate estimate of collapse likelihood of buildings under seismic excitations has recently become critical in efforts to promote hazard-resilience of the society, especially in developing national building codes, regional emergency response plans, and risk management strategies. Despite recent advances in static and dynamic nonlinear constitutive modeling of such structures, accurate prediction of structural collapse with systematic incorporation of uncertainty still remains a question, especially for structural evaluation and design of actual structures.
The most commonly used approach to assess the collapse capacity of structures under extreme earthquakes is based on the concept of incremental dynamic analysis (IDA; Vamvatsikos and Cornell, 2002). Uncertainties in structural properties and applied ground motions can be integrated into probabilistic description of structural collapse performance by adopting the probabilistic basis of performance–based earthquake engineering (PBEE) framework together with IDA. The maximum inter-storey drift ratio (IDR) is often selected as the measure to represent the global behavior of structural system in the PBEE framework (Cornell et al., 2002). Likewise, assumed threshold values based on IDR or on slope of IDA curve between IDR and elastic spectral acceleration are most commonly used limit-states to identify structural collapse capacity. However, collapse assessment approaches based on IDR may not accurately represent the overall collapse behavior of structural systems due to redistribution and variation of damage within the structure. Moreover, collapse prediction is found to be sensitive to such subjective collapse limit-states based on the assumed threshold values.
Characterization of overall cumulative (i.e., load-path dependent) collapse performance of structures considering aforementioned uncertainties is needed for accurate and reliable collapse risk assessment. Since energy parameters at system-level are aggregated quantities considering redistribution and variation of each individual component-damage within the structural system, they can be excellent indicators to represent total severe structural damage history due to cyclic-loading just before collapse. This paper therefore focuses on energy-based collapse analysis of structures to assess seismic collapse risk of structures. A new energy-based collapse limit-state is first defined to predict collapse in terms of dynamic instability due to loss of structural resistance against the gravity loads, instead of the behavior of the IDA curves. Using the new collapse limit-state, key descriptors that govern collapse capacity are identified for more effective risk assessment. Moreover, a probabilistic approach in collapse assessment is presented for systematic treatment of uncertainties in the ground motion time histories and integration with performance-based earthquake engineering (PBEE) framework.
First, nonlinear dynamic analyses are performed for experimental case studies reported in the literature (Kanvinde, 2003; Rodgers and Mahin, 2004; Lignos et al., 2008) by use of OpenSees, an object-oriented software framework developed by Pacific Earthquake Engineering Center (PEER). Using OpenSees computational models validated by corresponding experimental results, new dynamic-instability-based collapse limit-state is developed in terms of energy from the input ground motions and the gravity loads. The selected case studies are then used to test the new collapse limit-state and to identify key parameters that govern the collapse of a structural system. Next, the most effective collapse descriptor representative of structural global behavior history is developed as an equivalent velocity ratio of the system’s dissipated energy to input seismic energy. Using the developed collapse limit-state and new velocity-ratio collapse descriptor, a new method is established to construct collapse fragility models for reliable probabilistic evaluation of structural collapse, considering the uncertainties in both global demand and capacity of the structural system. Finally, the effect of earthquake characteristics and structural parameters on the collapse capacity is investigated for the purpose of estimating and improving structural reliability against collapse.
Structural Collapse; Collapse Experiments; Collapse Prediction; Collapse Probability; Fragility Curves; Uncertainty; Incremental Dynamic Analysis; Seismic Analysis; Earthquake; Performance–Based Earthquake Engineering; Damage Measure; Intensity Measure; Ground Motions; Energy Analysis; Collapse Criterion; Collapse Limit-State; Gravity Energy; Seismic Energy
Wed, 21 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2142/730332015-01-21T00:00:00ZAn implementation of the ground structure method considering buckling and nodal instabilities
http://hdl.handle.net/2142/73030
An implementation of the ground structure method considering buckling and nodal instabilities
The ground structure method is used to find an optimal solution for the layout optimization problem. The problem domain is discretized with a union of highly connected members, which is called a ground structure. The objective typically is to minimize the total volume of material while satisfying nodal equilibrium constraint and predefined stress limits (plastic formulation). However, such approach may lead to very slender members and unstable nodes that might cause instability issues. This thesis presents the implementation of the ground structure method involving instability consideration. The plastic formulation is implemented considering buckling constraint and nodal instability constraint either in isolation or in combination. The Euler buckling criteria is taken as the buckling constraint in the implementation with local instability consideration. The nominal lateral force method is used in the implementation involving nodal instability consideration. Moreover, the efficiency of the nonlinear programming is addressed. Several numerical examples are presented to illustrate the features of the implementation.
Ground structure; Topology optimization; Buckling; Nodal instability
Wed, 21 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2142/730302015-01-21T00:00:00ZNew methodologies for multi-scale time-variant reliability analysis of complex lifeline networks
http://hdl.handle.net/2142/73002
New methodologies for multi-scale time-variant reliability analysis of complex lifeline networks
The cost of maintaining existing civil infrastructure is enormous. Since the livelihood of the
public depends on such infrastructure, its state must be managed appropriately using quantitative
approaches. Practitioners must consider not only which components are most fragile to hazard,
e.g. seismicity, storm surge, hurricane winds, etc., but also how they participate on a network
level using network analysis. Focusing on particularly damaged components does not necessarily
increase network functionality, which is most important to the people that depend on such
infrastructure. Several network analyses, e.g. S-RDA, LP-bounds, and crude-MCS, and
performance metrics, e.g. disconnection bounds and component importance, are available for
such purposes. Since these networks are existing, the time state is also important. If networks
are close to chloride sources, deterioration may be a major issue. Information from field
inspections may also have large impacts on quantitative models.
To address such issues, hazard risk analysis methodologies for deteriorating networks subjected
to seismicity, i.e. earthquakes, have been created from analytics. A bridge component model has
been constructed for these methodologies. The bridge fragilities, which were constructed from
data, required a deeper level of analysis as these were relevant for specific structures.
Furthermore, chloride-induced deterioration network effects were investigated. Depending on
how mathematical models incorporate new information, many approaches are available, such as
Bayesian model updating. To make such procedures more flexible, an adaptive importance
sampling scheme was created for structural reliability problems. Additionally, such a method
handles many kinds of system and component problems with singular or multiple important
regions of the limit state function.
These and previously developed analysis methodologies were found to be strongly sensitive to
the network size. Special network topologies may be more or less computationally difficult,
while the resolution of the network also has large affects. To take advantage of some types of topologies, network hierarchical structures with super-link representation have been used in the literature to increase the computational efficiency by analyzing smaller, densely connected networks; however, such structures were based on user input and subjective at times. To address this, algorithms must be automated and reliable. These hierarchical structures may indicate the structure of the network itself. This risk analysis methodology has been expanded to larger networks using such automated hierarchical structures.
Component importance is the most important objective from such network analysis; however, this may only provide the information of which bridges to inspect/repair earliest and little else. High correlations influence such component importance measures in a negative manner. Additionally, a regional approach is not appropriately modelled. To investigate a more regional view, group importance measures based on hierarchical structures have been created. Such structures may also be used to create regional inspection/repair approaches. Using these analytical, quantitative risk approaches, the next generation of decision makers may make both component and regional-based optimal decisions using information from both network function and further effects of infrastructure deterioration.
Structural reliability; adaptive importance sampling; bridge networks; group importance measures; network hierarchical structures; multi-scale analysis; deteriorating networks; risk analysis
Wed, 21 Jan 2015 00:00:00 GMThttp://hdl.handle.net/2142/730022015-01-21T00:00:00Z