Ph.D. - Civil Engineering

Permanent URI for this collectionhttps://hdl.handle.net/10125/880

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Investigating the causes and mechanisms of a concrete pavement distress in Hawaiʻi
(University of Hawai'i at Manoa, 2025) Rahman, Muhammad Abdur; Ooi, Phillip S K; Civil Engineering
The soils underneath a PCC pavement on the island of Oahu, Hawaii were sampled and tested extensively because adjacent slabs had experienced vertical and horizontal separation. Based on the site geology, historical sea level rise and ebb may have caused the alluvial soils of volcanic origin to mix with calcareous fines (calcite), the source of which are the remains of dead coral giving rise to possible cementation in the soil. Hydrochloric acid and XRD tests suggest the presence of calcite in the upper reaches of the soil deposit and halloysite throughout. Index tests criteria proposed by the U.S. Army Corp of Engineers to assess soil collapsibility showed that the soils are collapsible based on dry unit weight, porosity and plasticity index values. However, the liquid limit test criterion was not consistent with the other criteria suggesting that the U.S. Army Corp of Engineers liquid limit criteria may not be as reliable in identifying collapsible tropical soils. The soils in the median are not as collapsible compared to soils directly underneath the pavement possibly due to the fact that the soils in the median have been subjected to a decade more exposure to atmospheric conditions and possibly because the soils below the pavement are constantly moist due to the canopy effect. The matric suction values under the pavement indicate that the soils below the pavement are saturated or nearly saturated. In contrast, the matric suction of the soil in the median fluctuated depending on the precipitation and the weather. Another notable feature is that the moisture content is higher at 0.5 ft than at 2.5 ft below the pavement but the reverse is true in the median . This phenomenon can also be attributed to the canopy effect at the pavement location and conversely, there is no canopy effect in the median. Suction controlled consolidation tests ran using a constant rate of strain consolidometer indicated soil collapse during three different phases of testing: saturation, drying and cyclic loading. A batch of samples collapsed by about 4% to 6% when saturated at a seating stress of only about 5 kPa. This occurred in the topmost samples below the pavement. The samples were first saturated so that the starting point on the soil-water retention curve is known. Since these samples are from the shallows, it can be implied that the shallowest soil is highly collapsible. It is postulated that the collapse in these samples is due to the breaking of calcite cementation bonds upon dissolution. A second batch of samples did not collapse during saturation. Instead, they collapsed by about 1% during suction application. In both samples, the suction applied was 200 kPa. One possible explanation for this is that the halloysite present loses the layer of water molecules in between the kaolinite units upon drying or application of suction. As a result, the soil collapsed when the water layer is removed irreversibly. Admittedly, the collapse due to suction application is smaller than that during saturation. The third batch of samples collapsed due to load-unload-reload cycles on saturated samples. The rationale for this is that PCC pavements heat up during the afternoons causing the pavement slab to curl downwards. They cool down in the early hours of the morning causing the pavement slab to curl upwards. These temperature cycles cause stresses to escalate at the edges and center of the pavement slab during the day and night, respectively. To simulate this in a consolidometer, the soil is loaded to a target vertical stress and then unloaded at a rate of 1 cycle per day for many cycles to simulate the repeated upward and downward curling. It was found that 60 to 80 cycles were adequate to yield the asymptotic strain. The collapse settlement or permanent deformation due to repeated loading and unloading depends on factors such as the number of cycles, duration of loading, and magnitude of stress difference in a cycle. A methodology is presented to estimate the long-term collapse settlement due to this mechanism. A hyperbolic curve can be fitted through each collapse versus cycle number curve, from which the asymptotic value of collapse strain can be estimated. The asymptotic strain can then be plotted versus the stress difference to allow an engineer to easily estimate the long-term load-unload-reload collapse for any value of stress difference. Curling-induced stresses were estimated utilizing first a finite difference analysis to estimate the temperature profile and then applying the temperature profile in a finite element analysis. The diurnal curling-induced subgrade stress can be as high as 25 kPa at the pavement edges with truck loading during the hottest time of the day in relation to an unloaded pavement at the coldest time of the morning. Based on a diurnal cyclic stress difference of 25 kPa and the cyclic consolidation test results, the collapse settlement due to curling-induced subgrade stress cycling is estimated to be about 2%. In sum, the 3 different sources of collapse strains are as follows: a. Collapse Strain due to Curling-Induced Subgrade Stress Cycling ≈ 2%. b. Collapse Strain due to Saturation and Loss of Cementation ≈ 4 to 6%. c. Collapse Strain due to Drying or Loss of Water Between Kaolinite Units ≈ 1%. Summing the 3 sources of collapse strain leads to a total collapse of 7% to 9%. According to Jennings and Knight (1975), the severity of the problem for these values of strain is considered “Trouble.” These stresses induced in a collapsing soil can lend an explanation of why the pavement distress was observed in the concrete pavement. Finally, some methods of mitigating collapse of similar soils are proposed in the Implementation section of the report (Section 5.3). They include dynamic compaction, pre-wetting and pre-loading, partial excavation and replacement, and a variety of soil improvement options.
Comprehensive approach to vulnerability assessment of structures and communities under tsunami hazards
(University of Hawai'i at Manoa, 2025) Abdelhafeez, Mostafa Hassan Fathi; Moon, DoSoo; Civil Engineering
Coastal regions face significant threats from tsunamis, which cause severe damage to infrastructure and human life. Due to their infrequent occurrence, accurately assessing tsunami hazards remains challenging, complicating risk evaluation despite their potentially catastrophic impact. This dissertation aims to enhance the understanding of structural and community vulnerability to tsunamis by developing advanced assessment methodologies. The research first evaluates structural fragility under tsunami loads and then expands to community-level vulnerability, offering insights for risk mitigation and resilience enhancement. A key component of this study is the use of fragility and vulnerability curves, which quantify the probability of structural failure under tsunami forces. These curves, based on cumulative log-normal distributions, provide critical insights for risk assessment and disaster management decision-making. This dissertation develops a comprehensive analytical approach for evaluating the fragility of structures subjected to tsunami loads. Through advanced numerical simulations, it examines structural behavior under extreme tsunami conditions, providing critical insights into their response. The proposed simulation approach is applied to selected structures, with the results analyzed to enhance understanding of structural fragility under tsunami loading, supporting the development of more resilient infrastructure in tsunami-prone regions. This dissertation presents three studies focused on the vulnerability of structures subjected to tsunami waves. The first study focuses on the tsunami vulnerability analysis of a reinforced concrete (RC) building classified as Tsunami Risk Category II. It examines the impact of different load distributions on the structural response during a tsunami event. The study also defines the inundation depth and flow velocity for dynamic assessments of the structural model. To quantify the effects of tsunamis on building performance, fragility relationships are derived from nonlinear dynamic response history analysis, utilizing a novel structural reliability method. The findings highlight that the number of tsunami cycles significantly influences the vulnerability of reinforced concrete structures, with a uniform load distribution being recommended for its conservatism. The second study examines the tsunami vulnerability of structures through numerically simulated tsunami waves, analyzing their propagation and impact on coastal dynamics and structural fragility. This study investigates the effects of various factors, including bathymetric features, alongside tsunami wave parameters. The simulation tool FUNWAVE-TVD is employed to model tsunami propagation and inundation. These tsunami intensity measures are then used to develop fragility curves to evaluate the structural probability of failure under different tsunami conditions. The study shows that higher Manning coefficients, steeper slopes, and longer wave periods reduce fragility, while more tsunami cycles and higher crest amplitudes significantly increase vulnerability, providing valuable insights for coastal resilience. The third study focuses on assessing the vulnerability of structures to 2D tsunami waves, with the goal of enhancing resilience in the coastal community of Kahului, Maui. A numerical simulation approach is developed to evaluate the fragility of selected structures under various tsunami scenarios through nonlinear dynamic time history analyses. The study aims to develop fragility curves for commercial, residential, and industrial buildings within the community, specifically examining the effects of wave amplitude, wave period, and other structural parameters. The findings indicate that both offshore tsunami amplitude and wave period significantly influence structural vulnerability, while building characteristics, such as design and materials, further impact the vulnerability of individual structures. Emphasizing the importance of estimating structural vulnerability, the study seeks to improve the accuracy of risk assessments and inform decision-making in disaster management. In conclusion, this research aims to advance the resilience of structures subjected to tsunami loads and to develop methods for assessing the vulnerability and performance of these structures. It highlights the importance of accurate vulnerability evaluation under varying tsunami wave conditions, considering factors such as bathymetric changes, wave characteristics, and structural types, to enhance risk assessment and decision-making in disaster management. The findings provide critical insights into the behavior of structures under tsunami loads and contribute to improved designs for both new and existing structures, including commercial, residential, and industrial buildings in coastal areas. Ultimately, these studies offer the potential to mitigate the economic and societal impacts of tsunami-related damage and inform effective coastal planning and disaster mitigation strategies.
Development of a numerical model for tsunami-driven debris transport and hazard assessment in a coastal community
(University of Hawai'i at Manoa, 2025) Koh, Myung Jin; Park, Hyoungsu; Civil Engineering
Tsunamis pose a critical risk to coastal communities, not only through inundation but also via debris transport, which intensifies damage by impacting infrastructure, blocking evacuation routes, and creating damming effects. This dissertation introduces a Debris Impact Hazard Assessment (DIHA) Framework to systematically evaluate tsunami-driven debris hazards at a community scale. The DIHR integrates numerical modeling and experimental data to generate actionable hazard metrics, including debris dispersion ratios, maximum impact loads, and intensity mapping. These metrics provide critical insights into vulnerable zones and high-risk areas, supporting disaster resilience planning and infrastructure design. The framework is applied to Honolulu Harbor, Hawai‘i, under a hypothetical 2,500-year tsunami scenario, demonstrating its effectiveness in identifying hazard hotspots.The newly developed numerical model has two key features. First, it introduces a semi-analytical solution for debris transport (tracking) model enabling to simulations of DIHA at a community-scale domain. Second, it incorporates a novel "randomness" variable at debris collision. Especially, this variable account for inherent uncertainties in the debris motion tracking, such as angular momentums, and varied reflection angles, enhancing predictive reliability while maintaining computational efficiency. The model simplifies debris representation through disk-shaped elements, validated against scaled laboratory experiments, ensuring robust simulation of debris dynamics. By capturing the probabilistic nature of debris transport, the model aligns closely with observed phenomena and improves the assessment of complex, real-world scenarios. The integration of DIHA and the randomness-enhanced debris transport model represents a significant advancement in tsunami hazard modeling. The findings demonstrate the importance of coupling site-specific hazard metrics with adaptive modeling techniques, bridging gaps between theoretical research and practical disaster management applications. This dissertation contributes to the scientific understanding and mitigation of tsunami-driven debris hazards, enhancing coastal community resilience against future tsunami events.
Multi-hazard fire vulnerability assessment and resilience quantification
(University of Hawai'i at Manoa, 2025) Sherif, Mohamed Ayman; Moon, Dosoo; Civil Engineering
The increasing frequency and severity of multi-hazard events, particularly those involving fire and seismic loading, pose significant challenges to the resilience of structural systems. Fire following an earthquake, concurrent fire-seismic events, and fire following earthquakes with aftershocks introduce complex degradation mechanisms that compromise material properties, structural stability, and load-bearing capacity. Traditional design methodologies often treat these hazards in isolation, failing to capture their interdependent effects on structural behavior. This dissertation advances the field of multi-hazard vulnerability assessment by integrating fire-inclusive material modeling, probabilistic fragility analysis, and resilience quantification to improve performance-based design strategies. A central contribution of this research is the development of advanced nonlinear material models for steel and concrete under fire and cyclic loading conditions. These models capture critical thermal-mechanical interactions, including strain reversal effects, cyclic degradation, and temperature-dependent stress-strain behavior. The study introduces a bilinear-quadratic cyclic model for steel, incorporating plastic strain accumulation to enhance predictive accuracy under sequential and concurrent dynamic loading conditions. For concrete, a modified Mander’s model is extended to account for high-temperature degradation, including spalling, stiffness reduction, and progressive strength deterioration. These material models are validated through numerical simulations and experimental data to ensure their reliability in hazard assessments. Building upon these material formulations, a multi-hazard fragility assessment framework is developed to quantify the probability of structural failure under fire and seismic loading conditions. Probabilistic fragility curves are generated using finite element reliability using MATLAB method, incorporating uncertainty in fire intensity, seismic ground motion, and structural parameters. Case studies examine the fragility of reinforced concrete (RC) structures under various hazard sequences, including fire-following-earthquake, fire following earthquake with aftershock, and concurrent fire-seismic loading. Results highlight significant reductions in structural capacity due to fire-induced stiffness degradation, yield strength reduction, and progressive material failure mechanisms. To extend the utility of fragility analysis, this research introduces a resilience index as a computational metric for quantifying post-hazard structural performance. This index integrates fragility-based failure probabilities with structural damage states, providing an analytical tool for assessing recovery potential and structural adaptability under multi-hazard exposure. The framework demonstrates how elevated temperatures and cyclic loading interactions exacerbate structural vulnerabilities, reinforcing the need for multi-hazard-inclusive design approaches. The findings of this research contribute to the advancement of fire-aware fragility modeling and performance-based multi-hazard assessment, providing engineers, policymakers, and researchers with quantitative tools for designing resilient infrastructure in fire-prone and seismic regions. The proposed methodologies and models enhance the accuracy of multi-hazard structural performance predictions, bridging critical gaps in current hazard assessment frameworks.
Enhancing Wastewater Surveillance Through the Development of Novel Detection Assays for Variants of SARS-CoV-2 and Influenza Viruses
(University of Hawai'i at Manoa, 2024) Jeon, Min Ki; Yan, Tao; Civil Engineering
The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for the COVID-19 pandemic, has posed a significant threat to global public health. The transmission of this virus through respiratory droplets and aerosols has led to the rapid spread of infections. Since the COVID-19 pandemic outbreak started in late 2019, numerous studies have demonstrated the presence of SARS-CoV-2 viral particles or genomic RNA in bodily wastes, including feces, urine, and respiratory fluids, originating from both symptomatic and asymptomatic patients. Due to these results, wastewater surveillance has been growing as a supportive tool to monitor and determine the presence of respiratory viruses in communities. This approach can help identify the emergence of outbreaks before clinical cases are reported, allowing public health officials to take early measures to contain the spread of the virus. However, despite its potential benefits, wastewater surveillance also has some limitations that need to be addressed for accurate and effective surveillance. The overall objective of this dissertation was to enhance wastewater surveillance for enveloped respiratory viruses such as SARS-CoV-2 and influenza viruses through advancements in data adjustments and molecular analyses. First, we conducted cross-correlation analysis on time-series data of SARS-CoV-2 RNA abundance and clinical case data from two major wastewater treatment plants (WWTPs) in Honolulu, Hawaiʻi. The detection of time lags between the data was enhanced through prewhitening and population normalization strategies. Second, molecular detection inhibitors in wastewater, especially humic acid, were used to determine the inhibition effect on hydrolysis probe-based real-time polymerase chain reaction (qPCR). This indicates the significance of comprehending the inhibitory mechanism of reporter dye of hydrolysis probes in the presence of humic acid in wastewater to ensure accurate quantification of targets. Third, we developed a new nested RT-PCR-PCR method to amplify and sequence the spike (S) protein gene region of SARS-CoV-2 (532 bp), including the receptor binding domain (RBD) for mutation identification from monthly wastewater samples collected from a small residential sewershed in Honolulu, Hawai‘i since the beginning of the COVID-19 pandemic. The study aimed to determine the viability of detecting novel variants in wastewater and to evaluate the performance of removal of PCR inhibitors with the Inhibitor Removal Technology® (IRT) and internal amplification standard (IAS). Fourth, a new amplicon sequencing method was developed to simultaneously amplify 576 bp of the polymerase basic 1 (PB1) encoding gene from various influenza virus variants present in wastewater. To address amplification bias resulting from varying primer-template affinities among variants and the presence of PCR inhibitors, IASs with multiple genes and different primer-template affinities were used to evaluate the amplification bias. Collectively, the outcomes of this dissertation will illustrate the potential for enhancing wastewater surveillance of SARS-CoV-2 and influenza viruses, leading to more accurate detection of their abundance and variants in wastewater.
EVALUATION OF FOOD WASTE AND SEWAGE SLUDGE ANAEROBIC CO-DIGESTION: KINETIC MODELING, META-ANALYSIS, AND LONG-TERM OPERATION WITH MICROAERATION
(University of Hawai'i at Manoa, 2023) Chuenchart, Wachiranon; Khanal, Samir Kumar; Civil Engineering
Machine learning modeling has recently gained attention in bioprocess engineering research for its precision prediction, optimization, and failure detection. However, due to its “black box” nature, interpretability approaches are needed to integrate to improve their understandability. In our study, the conventional approach of bioprocess assessment (i.e., kinetic modeling, a systematic review with meta-analysis, and long-term continuous operation) assisted with statistical analysis, and machine learning modeling was employed. In the batch experiments, higher food waste content resulted in higher specific methane yield (SMY), indicating higher biodegradability during co-digestion. The superimposed model with the first-order kinetic and modified Gompertz structure exhibited better accuracy among others in co-digestion. Meta-analysis reveals synergistic interactions of lignocellulosic biomass with animal manures and food waste with animal manures and lignocellulosic biomass (relative synergistic index, RSI > 1.20). Based on correlation analysis, multilinear regression, and tree-based regression, temperature was identified as a key parameter to improve methane yield in co-digestion of lignocellulosic biomass and fats, oils, and grease. However, food waste content is more important in food waste co-digestion. Long-term anaerobic co-digestion reaffirms that higher food waste content resulted in higher methane yield due to its rapid biodegradability and reveals the interactions of microaeration on hydrogenotrophic methanogenesis. The time-series model, specifically the trained nonlinear autoregressive network with exogenous inputs (NARX), also showed promising application on continuous systems with R2 = 0.8–0.9.
ADAPTIVE CONTROL STRATEGY FOR TRAFFIC PLATOON COORDINATION EMPOWERED BY CONNECTED AND AUTOMATED VEHICLES
(University of Hawai'i at Manoa, 2023) Yuan, Runze; Zhang, Guohui; Civil Engineering
Traffic congestions caused by increasing population, car ownership, and corresponding traffic demands have been a serious issue that not only hazards the safety and comfort of the commuters, but also increases the economic losses and environmental damages. Platoon control enabled by connected and autonomous vehicles (CAV) is regarded as a powerful solution to alleviate the traffic pressure and congestions caused by road bottlenecks. However, it will take a long time before the CAV can share a high market penetration rate to achieve pure CAV platooning. Therefore, both CAVs and the human driven vehicles (HDV) without Vehicle-to-Vehicle (V2V) communication mechanism will coexist and form mixed platoons in the future for a long period of time. It places urgent demands on reliable and robust strategies for this kind of mixed platoons to achieve steady and smooth platoon control. In this study, a specific mixed platoon composition with a leading CAV, a following CAV, and several sandwiched HDVs between them is adopted to research the mixed platoon characteristics. A spring-mass-damper-clutch physical system inspired linear car following model with delay is used to account for the delayed reaction and the varying driving modes of human drivers. Since the HDVs are not equipped with V2V communication devices, the last following CAV is regarded as degraded CAV (DCAV). Therefore, an Adaptive Numerical algorithm for Subspace system Identification (AN4SID) method is proposed to identify the model of direct preceding HDV in front of the last following DCAV. The model could be used to predict the future states of the preceding HDV given the estimated delay through vector fitting and the planned future trajectory of the leading CAV. Then a hybrid control strategy combining the Model Predictive Control (MPC) and the optimal feedback control methods is applied to the following DCAV. The predicted HDV states will be used to calculate the reference trajectory of the following DCAV for the MPC process. Then the MPC control signal will be used as the feedforward input together with the feedback control input to eliminate the deviation caused by prediction errors.By conducting simulations based numerical experiments on MATLAB platform and the real vehicle trajectory data from the Next Generation Simulation (NGSIM) open dataset, the proposed AN4SID method shows reliable prediction performance compared with the Recursive Least Square (RLS) method and the Iterative Extended Kalman Filter (IEKF) method. Then, further experiments judged that our proposed hybrid control strategy overperformance both the Linear Quadratic Regulator (LQR) and the regular MPC algorithm, in terms of the safety, comfort of passengers, and fuel efficiency.
A Study Of Machine Learning Applications For Solving Problems In Structural Engineering
(University of Hawaii at Manoa, 2023) Song, Xi; Cho, Chunhee; Civil Engineering
Structural engineering, a sub-discipline of civil engineering, involves the design and analysis of structures. The goal of structural engineering is to ensure that these structures are safe, stable, and capable of performing their intended functions throughout their lifespan. Meanwhile, machine learning (ML), a subset of artificial intelligence, utilizes statistical methodologies to learn and generate predictions or decisions directly from data. This dissertation explores the integration of these two fields, offering innovative approaches to solve structural engineering problems through the application of ML.The work comprises three projects that showcase the application of ML in the domain of structural engineering. The first project focuses on the predicting structural strength of steel circular hollow section (CHS) X-joints. Using support vector machines and deep neural networks, this project demonstrates how machine learning can effectively manage structural strength prediction tasks, pointing towards a promising future for ML in this field. The second project ventures into seismic risk analysis, a crucial part of structural safety evaluations. The use of advanced ML algorithms, including the discussion of hyperparameter tuning and model optimization, allowed for a more efficient and accurate prediction of seismic impact on structures such as railway bridges. The last project adopts machine learning for structural damage detection, using pre-trained convolutional neural networks tailored for image-oriented input. Key structural dynamic properties are transcribed into scalograms via wavelet transform, serving as training samples for the machine learning model. The promising outcomes from this project endorse the potential of machine learning in augmenting the efficiency and accuracy of processes for detecting and evaluating structural damage. Throughout the dissertation, a progressive learning journey unfolds, detailing how the understanding and application of ML evolved from basic techniques to more advanced methodologies. Each project enhances the subsequent one, demonstrating a continuous improvement in the application and understanding of ML. This research demonstrates that machine learning can provides new perspectives and methods for tackling topics in structural engineering, greatly enhancing the efficiency and effectiveness of problem solving in the field. The integration of ML can circumvent the complex experiments, simulations, and calculations that are typically required in structural design and analysis. The work encourages future discussion in the field, refining ML applications, exploring more innovative techniques, and ultimately continuing to push the boundaries of what can be achieved in structural engineering.
Integrated Approaches For Scalable Aquifer Numerical Modeling, Inversion, And Upscaling
(University of Hawaii at Manoa, 2023) Seo, Young-Ho; Lee, Jonghyun; Civil Engineering
In this dissertation, three interconnecting research themes in the domain of groundwater modeling and characterization are explored. The dissertation represents a significant integration of novel approaches and computational tools for groundwater modeling and characterization. It not only improves our current understanding but also presents considerable new directions for future study, making a significant contribution to groundwater modeling. Chapter 2 focuses on the development of a distinctive joint-inversion methodology, which utilizes hydrogeological, self-potential, and magnetotellurics data, to estimate hydraulic conductivity and electrical resistivity. The proposed technique doesn't necessitate any assumptions related to petrophysical relationships and demonstrates a 25\% improvement in the estimation of hydraulic conductivity in comparison to single data-type inversions, providing crucial insights into regions beyond immediate observation wells. In Chapter 3, a significant focus is placed on developing a reliable hydraulic conductivity upscaling tool for high-dimensional groundwater flow models. Recognizing the vital role of accurately representing hydraulic conductivity at an appropriate scale, the study strived to develop a computational tool that effectively balances computational efficiency while preserving key features of the detailed hydraulic conductivity field. The tool, based on Kitanidis' (1990) hydraulic conductivity upscaling approach, has the capability to calculate upscaled hydraulic conductivity values in the tensor form and account for anisotropy. Rigorous tests were carried out to assess the performance of the tool, and its resilience under various flow conditions, providing a reliable resource for high-dimensional groundwater modeling. Chapter 4 addresses the development of the PISALE software. This tool is specifically designed to manage the complexities of groundwater flow processes in Pacific islands that are marked by dynamic interactions between freshwater and seawater in highly heterogeneous volcanic rocks. The software integrates advanced mathematical techniques and parallel programming models to accelerate solutions and offer precision in reproducing freshwater-seawater interfaces in large-scale coastal aquifers.
Testing And Evaluation Of Self-consolidating Concrete (SCC) Using Volcanic Aggregates
(University of Hawaii at Manoa, 2023) Hosseinpanahi, Azadeh; Shen, Lin; Civil Engineering
Self-consolidating concrete (SCC) flows under its own weight, passes through intricate geometrical configurations, and fills the formwork without vibrating or consolidating. In comparison with conventional concrete mixes, SCC should be closely controlled in terms of its composition and rheological properties to meet the fresh property requirements simultaneously. However, large-scale applications and acceptance have not yet been well-established in Hawaii for SCC materials. The problem can be attributed to Hawaii's unique aggregate, which is locally mined and crushed with absorption capacities ranging from 1 to 5%. Because volcanic aggregate has different absorption capacities, gradations, and textures than mainland aggregate, conventional SCC mix designs will not work. As a result, this study examined how aggregate properties affect SCC rheology. It was found that higher aggregate volume, higher fine aggregate to coarse aggregate ratio, smaller aggregate size, and lower aggregate packing density may increase the yield stress of the SCC mixture. Aggregate size had an insignificant effect on plastic viscosity. SCC mixes were also studied for their mechanical and durability properties to ensure their sustainability. Furthermore, since the rheological properties of SCC have been proven in Chapter 2, machine learning models were conducted to predict plastic viscosity. During the last phase of this project, liquid carbon dioxide admixture was used to test concrete carbon neutrality in the field. According to the research, CO2 admixtures do not adversely affect the fresh, mechanical, or durability properties of concrete, and they may be useful for carbon sequestration in the construction industry.
Integrated Framework For Multi-hazard Resilience Assessment Of Infrastructures
(University of Hawaii at Manoa, 2023) Ghanem, Amr; Moon, DoSoo; Civil Engineering
Natural hazards such as earthquakes and tsunamis can have a severe impact on societies globally, causing significant economic losses and leading to casualties. In marine environments, earthquake-induced fault ruptures can trigger devastating tsunamis that amplify the scale of the disaster. Therefore, it is crucial to assess the structural fragility of infrastructure and buildings in regions that are prone to seismic and tsunami hazards. Previous research has shown that earthquakes and tsunamis have caused thousands of deaths and billions of dollars in losses. Thus, it is imperative to continue investing in research aimed at developing resilient infrastructure systems that can withstand multiple natural hazards, especially earthquakes, and tsunamis. By understanding the risks and implementing measures to enhance infrastructure resilience, communities can mitigate the impact of these hazards and reduce their devastating effects on their economies and societies.In the context of structure loss estimation and hazard risk assessment, fragility or vulnerability curves are commonly utilized. These curves represent the probability of failure for a specific hazard and are typically displayed using cumulative log-normal distribution functions that express the likelihood of achieving predetermined damage criteria. By utilizing fragility or vulnerability curves, decision-makers can better understand the potential for structural damage or failure during the hazard and develop strategies to mitigate risk and enhance infrastructure resilience. This dissertation developed a comprehensive analytical fragility framework for the assessment of structures subjected to multi-hazards. As well as to investigate the behavior of structures under these extreme loads using numerical simulation techniques and to provide valuable insights into the behavior of structures under seismic and tsunami loads. The developed simulation frameworkis applied to selected structures, analyzed, and compared the results of the research, and offers insights into the reliability and robustness of current assessment methodologies. The results of the research study are expected to contribute to the broader research goals of improving our understanding of structural fragility under extreme loads and developing more resilient structures in seismic and tsunami regions. This dissertation presents three studies that investigate the vulnerability of different types of infrastructures (buildings and bridges) when subjected to consecutive hazards (seismic and tsunami loads). The first research focuses on the seismic vulnerability analysis of skewed reinforced concrete bridges, which are commonly used in transportation networks due to their complex and non-orthogonal nature. Despite their geometric irregularities, such bridges are often necessary, and avoiding them is not a viable solution. To quantify the effects of skewness on bridge performance, fragility relationships for various bridge models are derived from nonlinear dynamic response history analysis using a new structural reliability method. The results show that the skew angle has a direct effect on the seismic vulnerability of reinforced concrete (RC) bridges, and this research can be useful for designing new skew RC bridges. The second research investigates the seismic fragility of reinforced concrete frames with mass irregularities resulting from possible changes in structure use. Such changes can significantly affect live load distributions, making the structure more vulnerable to earthquake damage. Comprehensive three-dimensional structural models are analyzed for accurate vulnerability evaluation, considering twenty-one frame models with varying vertical and in-plan irregularities under different live load distribution scenarios. The results highlight the effects of vertical and in-plan mass irregularities on the structural vulnerability and performance of reinforced concrete frames when subjected to earthquake loading. The third research addresses the vulnerability of structures under combined seismic and tsunami loads, which is a critical issue for enhancing resilience in coastal regions. Neglecting the interaction between joint intensity-measure fragilities can lead to significant inaccuracies when estimating damage or structural loss. Therefore, a numerical simulation framework is developed to assess the fragility of selected structures under various earthquake and tsunami scenarios using successive nonlinear dynamic time history analyses. The study emphasizes the importance of considering the complex interaction between various intensity measures to improve the accuracy of risk assessment and decision-making in disaster management. In conclusion, this research aims to enhance the resilience of structures under different loading conditions and to develop the knowledge and approaches to assess the vulnerability and performance of such infrastructures. The research emphasizes the need for an accurate evaluation of vulnerability under different loading conditions, including structural irregularities and complex loading scenarios, to improve the accuracy of risk assessment and decision-making in disaster management. The results of these studies provide valuable insights into the behavior of structures under different hazards loads and are expected to be useful for new designs of reinforced concrete bridges and frames subjected to seismic and tsunami loads and to assess the vulnerability of existing structures to hazard events., with the potential to reduce the economic consequences of damage to transportation systems and coastal regions.
Applications Of Innovative Building Material And Computer Vision Methods In Geotechnical Engineering
(University of Hawaii at Manoa, 2022) Han, Xiaole; Jiang, Ningjun; Civil Engineering
The Hawaiian Islands have been a world-famous traveling spot for their unique tropical island view. But the particular geological formation of the islands and their unique locations have always proposed challenges for geotechnical engineers and geologists. For example, coral sand is widely encountered in coastal areas of tropical or subtropical regions. It can be found on most beaches in Hawaiian islands. Compared with silica sand, it usually exhibits weaker mechanical performance from the perspective of engineering geology. Thus, necessary soil improvements shall be applied to the coral. Considering the fragile and unique ecosystem, sustainable material with less carbon footprint and less environmental impact would be developed and selected priorly. Moreover, the infrastructures along the island have been facing coastal erosion issues from both physical erosion (waves) and chemical erosion (sea wind and seawater). The road embankment, the house embankment, the harbor, etc often require maintenance to sustain their service time. Due to the topography and climate, the windward side of the coastal area on Oahu is suffering from marine microplastics (MP) pollution issues. Furthermore, as an island state, hurricanes and tsunamis could also threaten the safety of islanders and infrastructures. Therefore, as a geotechnical major Ph.D. student, this dissertation would devote some potential solutions to the challenges. Firstly, a novel alkali-activation-based sustainable binder was developed for coral sand stabilization. The alkali-activated slag (AAS) binder material was composed of ground granulated blast furnace slag (GGBS) and hydrated lime with the amendment of biochar, an agricultural waste-derived material. The biochar-amended AAS stabilized coral sand was subjected to a series of laboratory tests to determine its mechanical, physicochemical, durability, and microstructural characteristics as well as durability. Results show that the addition of a moderate amount of biochar in AAS could improve soil strength, elastic modulus, and water holding capacity by up to 20%, 70%, and 30%, respectively. Moreover, the addition of biochar in AAS had a marginal effect on the sulfate resistance of the stabilized sand, especially at high biochar content. However, the resistance of the AAS-stabilized sand to wet-dry cycles slightly deteriorated with the addition of biochar. Based on these observations, a conceptual model showing biochar-AAS-sand interactions was proposed, in which biochar served as an internal curing agent, micro-reinforcer, and mechanically weak point. Secondly, a state-of-the-art deep-learning algorithm, Mask R-CNN, was utilized for the clayey soil crack detection, locating and segmentation. A comprehensive dataset including 1200 annotated crack images of 256×256 resolution was prepared for the algorithm training and validation. The proposed Mask R-CNN algorithm achieved precision, recall and F1 score of 73.29%, 82.76% and 77.74%, respectively. Besides, the algorithm gained a mean locating accuracy (APbb) of 64.14% and a mean segmentation accuracy (APm) of 47.59%. The detection performance of the Mask R-CNN was also compared with the U-Net in three different scenarios. The test results have demonstrated the superiority of the Mask R-CNN over the U-Net algorithm in crack detection, locating and segmentation and the algorithm could automatically process the crack characterization. Then, this dissertation proposed a state-of-the-art deep learning-based approach, Mask R-CNN, to locate, classify, and segment large marine microplastic particles (fiber, fragment, pellet, and rod). The fully trained Mask R-CNN algorithm was compared with U-Net in characterizing microplastics against various backgrounds. The results showed that the algorithm could achieve Precision=93.30%, Recall=95.40%, F1 score=94.34%, APbb=92.7%, and APm = 82.6% in a 250 images dataset with white background. The algorithm could also achieve a processing speed of 12.5 FPS. The results obtained in this study implied that the Mask R-CNN algorithm is a promising microplastics characterization method that can be potentially used in the future for large-scale surveys. Finally, a video instance segmentation algorithm was trained to locate, identify, and segment soil cracks in a real-time video stream. The algorithm could record the cracks' locations and numbers simultaneously. Besides, the crack ratio of clay could be calculated by crack pixels divided by total clay pixels among the entire soil cracking process. Furthermore, Structure from Motion (SfM) has been applied to reconstruct the 3D soil desiccation models. The soil crack can be detected in a 3D point cloud graph and highlighted. A series of 3D parameters like depth, volume, and cross-section profile can be obtained for future analysis. The proposed video instance segmentation method has demonstrated the potential application for real-time crack alerts and monitoring of geotechnical infrastructures via surveillance cameras.
Sandy Soil Stabilization by Microbial Induced Calcite Precipitation (MICP) using Bio-stimulation Method
(University of Hawaii at Manoa, 2022) Wang, Yijie; Jiang, Ningjun; Civil Engineering
Calcareous sands are often considered as very unstable and evolving materials with large particles allowing an abundance of air space. Their physical properties are usually defined as weak or no structure, free draining with high permeability, poor water retention, and high sensitivity to compaction. In tropic areas, the physical properties of sandy soils are more complicated. A more frequent cycling of wetting and drying can affect the physical properties significantly. These adverse engineering properties make it difficult to manage in the construction field. Chemical stabilization has been applied in the field for years. Frequently used stabilizers include Portland cement, lime and industrial waste lime, asphalt, and others. However, the major problem of these tradition materials is highly dependent on mass industrial production which requires substantial energy. Some potential environmental issues can be induced due to the high alkaline level of many of these chemical stabilizers. Considering the abovementioned limitations of those traditional additives, alternative technique is required to make the sandy soil stabilization more economic and environmental-friendly. Microbiologically Induced Calcite Precipitation (MICP) as a new interdisciplinary method combines the microbiological, geochemical, and geotechnical research to fulfill the increasing demands for the sandy soil improvement. The stabilization process can be achieved by inducing calcite precipitation within the sand matrix via microbial ureolysis procedure by ureolytic bacteria. The produced calcite precipitation preferentially accumulates at particle-particle contacts, which can provide extra connection and gain more strength. Because of the widely distribution of ureolytic microbes in the natural soil, the in-situ bio-stimulation of indigenous ureolytic bacteria becomes feasible. The study in this thesis firstly investigated the effect of enrichment media on the stimulation of native ureolytic bacteria in calcareous sand under solution condition. A series of batch tests were conducted, and the generic and three different selective enrichment media were compared from the biochemical aspects. The results show that the selective enrichment media rich in urea could successfully stimulate and enrich the native ureolytic bacteria by monitoring the ureolytic activity, pH, and electric conductivity. The nutrients with higher nitrogen sources show better efficiency in improving ureolytic activity. Secondly, the biochemical and direct shear behaviors of bio-cemented sand treated by bio-stimulated MICP were investigated under sand column condition. It was found that during the enrichment phase, the indigenous ureolytic bacteria can be enriched significantly within 48 hours, though the ureolysis rate was varying with the initial urea concentration. The microbial community changed significantly after enrichment stage. The ureolytic species could be found in the sand. Furthermore, the cementation content increased with the flushing number of cementation solution. The shear strength of bio-cemented sand could be significantly enhanced after MICP treatment. The cohesion and peak friction angle increased with elevated cementation level while declined with the increasing normal stress. Then, the compressive characteristics of bio-cemented sand was studied under one-dimensional compression tests. It was found that the compressibility of bio-cemented reduced with the increasing cementation content. The samples prepared under higher initial relative density showed less compression. Based on microscopic observations, a conceptual framework based on the interparticle contact modes and their corresponding damage modes during the compression tests was proposed. After that, to find out a way to preserve the enriched urease within soils as much as possible, and further increase the bio-cementation content, the biochar-amendment was incorporated into MICP. The shear behavior of biochar-amended bio-cemented calcareous sand treated via bio-stimulation was investigated through a series of direct shear test. The results showed that the addition of biochar powders could effectively increase the cementation content as the extra nucleation sites for native ureolytic bacteria. However, too much biochar within bio-cementation may become weak points and thus diminish the contribution of interparticle bonding to the shear strength. Finally, a preliminary exploration of bio-stimulated MICP in rainfall-induced erosion prevention was conducted by a series of laboratory model tests. The artificial sandy slope was made and subjected to the rainfall. Meanwhile, the photography-based SfM (Structure from Motion) as the new technique was firstly applied to evaluate the slope deformation under rainfall-induced erosion. The results showed that bio-stimulated MICP could significantly reduce the erosion on a sandy slope, especially in case treated by YE-based enrichment medium with 170 initial urea concentration. It is a good trial to explore a feasible monitoring way for the future full-scale application in field.
Diversity Of Fecal Pathogens In Hawaii’s Coastal Waters And Detection With Improved Performance By Next Generation Sequencing
(University of Hawaii at Manoa, 2020) Saingam, Prakit; Yan, Tao; Civil Engineering
Among all pollutants in coastal waters, fecal pathogens have caused a lot of concerns due to their disease transmission risks. An investigation on the impact of pollution sources could provide guidelines for us to protect coastal water quality. However, the use of fecal indicator bacteria (FIB) in monitoring the presence of fecal pathogens can be misleading because of their prevalence in the environment. In the meantime, our understanding about the impact of storm water sources is still limited. While direct detection of pathogen has been an alternative monitoring system, the detection methods need to be improved. In order to address the above issues, I conducted four research projects, which will be shown and discussed in this dissertation. In Chapter Two, the use of FIB in monitoring the quality of tropical urban marine estuary waters was investigated. The investigation included distribution of three FIB and four fecal pathogens at Ala Wai Canal (Oahu, Hawaii). The results showed that there was no correlation detected among the three FIB. Also, most of the tested typical fecal pathogens were not found. However, a pathogen and a marine microbe Vibrio parahaemolyticus was found prevalent but not correlated with the FIB. These findings indicated inconsistency between the FIB and fecal pathogens at a tropical urban marine estuary. In Chapter Three, the immediate impact of major storms such as hurricanes on coastal waters was researched. The investigation included the prevalence and genotypes of FIB enterococci in coastal waters at Hilo bay immediately after the Hurricane Lane. Total enterococci across the investigated sites were detected with levels meeting the standard criteria and gradually decreased over time. However, the variation of enterococci concentrations and genotype distribution were more distinctive among sites. The findings uncover the immediate impact of a hurricane on temporal and spatial variation of coastal water quality. In Chapter Four, the impact of hurricane on occurrence of pathogenic enterococci in Hilo bay water was examined. In this study, 49 enterococci isolates from Hilo bay were scrutinized for their species identification, virulence genes and antibiotic resistance susceptibility. Among the isolates, prevalence of E. faecalis and E. faecium/E. durans and their resistance to eight antibiotics were observed and four virulence genes were detected. This suggests the hurricane impact on the occurrence of pathogens and identified potential pathogens in coastal waters. In Chapter Five, a novel PCR-NGS method of detecting pathogens in environmental samples was explored. This included tests on sensitivity and robustness against water samples. It will be shown that NGS can improve sensitivity of PCR and qPCR-based detection of Salmonella. Also, the PCR-NGS indicated that Salmonella can be successfully detected from coastal stream samples. These results demonstrated that PCR-NGS is a promising method of pathogen detection in environmental samples. Overall, this dissertation sheds light on how we can enhance coastal water quality monitoring. The following topics were investigated and discussed: (i) evidences of misleading use of FIB in monitoring tropical urban marine estuary waters, (ii) impact of storm water on coastal water quality and occurrence of pathogen, and (iii) a novel approach of pathogen detection essential for the development of the pathogen-based monitoring system.
Design of alkali-activated materials based on quantitative microanalysis of precursors and reaction kinetics
(University of Hawaii at Manoa, 2020) Mirmoghtadaei, Reza; Shen, Lin; Civil Engineering
Alkali-activated materials (AAMs) provide a new virtuous and green solution to the employment of waste materials, avoiding their harmful impacts on environment and ecology. Compared with conventional concrete mixes with cement, the composition and impurities of precursors, as well as the type and concentrations of alkalis should be carefully controlled in order to satisfy fresh properties, hardened properties, and durability simultaneously. Moreover, in order to optimize the mix design, it is essential to employ a reliable, accurate, and user-friendly approach to investigate precursors’ compositions as well as the reaction kinetics. Geopolymerization occurs through chemical reactions of powders containing aluminosilicate oxides with alkalis leading to the formation of Si-O-Al bonds. These three-dimensional networks have amorphous to semi-crystalline silicoaluminate structures. Material scientists classify any binder system obtained from the reaction of alkali sources with solid silicate powders as AAMs. The precursor can be calcium silicate as in the hydration of clinkers, or aluminosilicate-rich powders like blast furnace slag (BFS), fly ash, natural pozzolan, or bottom ash. Moreover, the alkali can be any soluble materials, which increase the pH in the mix and accelerate the dissolution process. To study the kinetic of alkali-activation and design of AAMs, which is robust regardless of type of precursors and alkalis, it is critical to be able to quantify different phases of precursors quickly, monitor the process of alkali-activation, and design AAMs with a reliable and easy method. In this study, a quantitative phase analysis by Raman Spectroscopy is introduced as a simple, fast, and reliable method for analyzing precursors and monitoring the kinetic of reactions. On the other hand, a new method based on the initial pH of concrete mixes was developed to design AAMs. It was found that Raman Spectroscopy is capable of successfully quantifying critical compositions and impurities of precursors. Different mixing procedures have been studied on precursors with high percentages of impurities in their compositions. Undesired elements in precursors could be sulfur, chloride, and unburnt carbon. It was found that applying alkali activators separately from silicate activators could significantly enhance the fresh and hardened properties of AAMs made from precursors with high impurities. Finally, the effects of different levels of initial pH on the mechanical properties and final products of AAMs were investigated. It was found that initial pH lower than 12 led to unstable soluble silica, a mixture of different crystals, and lower compressive strengths. It was also concluded that in the presence of optimal initial pH ranged between 12.2 and 12.4 the best selection for sodium silicate solution would be the products with a SiO2/Na2O ratio of 2.1.
Genomic Characterization of Salmonella In Municipal Wastewater For Community Enteric Disease Monitoring
(University of Hawaii at Manoa, 2020) Diemert, Sabrina; Yan, Tao; Civil Engineering
Municipal wastewater (MW) contains human enteric microorganisms: this includes normal gut flora and as pathogens from infected persons. These pathogens can include bacteria and viruses, as well as microorganisms from other domains. From a civil engineering perspective, these microorganisms normally present a public health threat which must be removed or inactivated during wastewater treatment. However, they can also represent a rich source of information about community health: this collective microbiome can be monitored for disease patterns, and used to inform public health interventions and policies. Traditional clinical surveillance methods underestimate community enteric disease burden; for salmonellosis, it is often assumed that the true number of infected persons is approximately 30 times the clinically reported rate. Municipal wastewater infectious disease surveillance may provide a less-biased option for public health monitoring. The overall objective of this dissertation was to use municipal water surveillance to elucidate community salmonellosis trends in Honolulu, Hawaii. Whole genome sequencing (WGS) was conducted on Salmonella isolates (n = 272) collected in weekly 24-hour composite samples from Sand Island Wastewater Treatment Plant in a yearlong monitoring campaign from 2010-2011. First, comparative genomics approaches were used to identify a salmonellosis outbreak which was previously missed by public health clinics in Honolulu: this demonstrates the sensitivity of MW surveillance for clinically relevant infections. Second, subclinical salmonellosis trends were examined, as an abundant strain of Salmonella in MW was found in low frequencies in health clinics (S. Derby). This strain was a previously under-reported sequence type of Derby, which exhibits low virulence potential but an increased ability to establish infections than most Derby strains, allowing it to maintain persistence in the community. Third, the antibiotic resistance gene (ARG) profiles of MW Salmonella was compared with clinical nontyphoidal salmonellosis ARG patterns: MW isolates reflect a subset of the clinical ARG diversity, with ARG rates appearing lower in MW than in clinical isolates. However, MW ARG patterns correspond with the prevalent serovars, and may be indicative of the Salmonella resistome for asymptomatic or minor infections. Taken together, the results of this dissertation demonstrate that MW surveillance can discern relevant public health trends which are inaccessible using traditional clinical monitoring approaches.
Effects Of Thermal Hydrolysis Temperature On Degradation Product Speciation, Methane Potential And Rheology
(University of Hawaii at Manoa, 2020) Hu, Bing; Babcock, Roger; Civil Engineering
The effects of low to medium temperature (44-121℃) thermal hydrolysis (THP) treatment of primary (PS) and secondary (WAS) municipal wastewater sludge on formation of carbohydrates, proteins, Melanoidins and methane generation potential were evaluated. Results show that between 1.5 and 12% of volatile solids (VS) was hydrolyzed into filtered dissolved solids (FDS), with 55-100% represented as carbohydrates and proteins depending on sludge type and THP temperature. Proteins are produced at 160 to 350% of the values for carbohydrates in terms of g gVS-1, and WAS values are 4 to 5 times as large as PS values. Much more low molecular weight (LMW) proteins are formed than high MW (HMW) proteins at all temperatures for both PS and WAS. The same is true for carbohydrates from PS, but the quantities of LWM and HWM produced are similar for WAS. Low-medium temperature THP increased biomethane potential (BMP) of WAS from 145 ml CH4 gVS-1 in untreated WAS to up to 230 ml CH4 gVS-1 (44 to 57% increase depending on temperature), and only nominally increased BMP of PS (by 0 to 7.5%). THP caused the formation of much more Melanoidins in WAS than PS and showed little dependence on temperature in the range evaluated herein. There was a nearly 20-fold increase in supernatant color for both PS and WAS that was well correlated with increases in THP temperature. Overall, the effects of low-medium temperature THP are significant for WAS and limited for PS. Product speciation of soluble components in secondary sewage sludge during THP is investigated in this research. The dissolved components concentrations increased with increasing THP temperatures (between 80 and 220℃) and reaction time (between 0 and 60 min), including dissolved solids, COD, TOC, carbohydrates, VFA, TN, protein, amino acids, and ammonium. At low temperature THP as 80℃, the carbohydrate and protein portion to sCOD is higher than the high temperature THP (110-200℃) due to THP releases nutrients from intercellular to free water but temperature not high enough to break down these structures. Proteins are highly denatured at 200℃ that ammonium concentration goes much higher than other conditions. The liquid brown color which is mainly from melanoidins generated during THP goes darker with temperature up and reaction duration. Melanoidins concentrations are also calculated from high molecular weight material, protein and carbohydrate, whereas the results fail to follow with the color results because of inaccurate conducted in measurements. The effects of THP pre-treatment of PS and WAS on particle size distribution (PSD), apparent viscosity and dewaterability prior to and following anaerobic digestion (AD) were studied. Results showed that when THP there was a shift in particle size distribution during THP of WAS, with particles in the range of 10 to 40 μm decreasing and 2-3 μm particles increasing. The apparent viscosity of WAS at a shear rate of 5 s-1 and 15-min reaction time increased relative to a control (4071 cP) at lower temperatures (80-110℃) due to gelation (up to 5880 cP) and then decreased dramatically in proportion to temperature increases to 140, 170 and 200℃ (2261, 1131 and 678 cP, respectively). Anaerobic digestion of the THP-treated mixed PS+WAS sludge further decreased the viscosity. The dewaterability of digestate from lab-scale ADs fed THP-treated mixed sludge improved compared to a control. The total solids (TS) of centrifuged sludge cake increased from 19.8 to 30.4% for pre-treated at 170℃ THP treated sludge compared to non-THP-treated. This result suggests a lower energy usage in the downstream sludge drying process. THP has been used prior to AD in sewage sludge treatment to increase digestion reaction rate, methane generation, and digested sludge dewaterability. All of these benefits point toward energy savings and the potential for net zero energy. Energy simulations were performed for a medium-sized municipal wastewater treatment plant (WWTP) that is in the process of adding THP, co-digestion of high energy wastes, thermal sludge drying, and combined heat and power (CHP). Laboratory experiments were conducted to determine site-specific efficiencies for THP, AD and BMP as inputs to the model. Historic and future projected facility energy use was also incorporated. The electricity energy input for sludge treatment decreased when applying THP to secondary sludge at 140°C (421 kW input when flow rate is 509 kg hr-1) and 170°C (258 kW input) compared to no THP treatment (463 kW). THP has little effect on the energy balance for PS because the methane yield improvement is minimal compared to WAS. Energy input for PS without THP is 537 kW when the flow rate is 927 kg hr-1, which decreased to 327 kW with THP at 170°C. Net zero energy can be achieved only by conducting co-digestion with a high-energy substrate such as 20% of VS loading added as fats oils and grease (FOG).
Molecular And Metagenomic Characterization Of Bacterial Pathogens And Antibiotic Resistance Genes In Complex Environments
(University of Hawaii at Manoa, 2020) Li, Bo; Yan, Tao; Civil Engineering
Bacterial pathogens and antibiotic resistant genes (ARGs) in the environment have become important clinical issues. Characterization of pathogens and ARGs in the environment is essential for health risk assessment. The high diversity and usually low concentrations of bacterial pathogens and their ARGs in environmental samples pose challenges to current detection methods. Current molecular methods, including polymerase chain reaction (PCR) and next generation sequencing (NGS), suffer different limitations in specificity, sensitivity, throughput, and/or quantitative capacity. The overall objective of this dissertation is to develop new molecular and metagenomic approaches to characterize bacterial pathogens and ARGs in complex environments, with particular aims in improving specificity, sensitivity and throughput of current molecular methods. Four specific objectives are covered in this dissertation. First, this dissertation examined the overestimation potential of dye-based qPCR method for ARG detection by comparing with specific probe-based qPCR, which was subsequently confirmed through NGS amplicon sequencing. Overestimation of ARGs was observed in dye-based qPCR reaction, which is mainly caused by non-specific amplification. Second, a novel method that combines multiplex PCR with NGS (mPCR-NGS) was developed for simultaneous detection of multiple waterborne pathogens. The multiplex level of mPCR was significantly increased by using NGS to display amplicons of 14 target genes simultaneously. Third, metagenomic sequencing and bioinformatic analyses were used to detect ARGs in pristine soil samples, and a total of 48 ARGs were detected. Fourth, a quantitative metagenomic sequencing methods was developed by spiking non-natural internal DNA standards into DNA samples. Comparison between the quantitative metagenomic sequencing approach and qPCR quantification demonstrated comparable levels of accuracy. The findings in this study help to better understand and improve current molecular methods for the characterization (detection or quantification) of pathogens and ARGs in the environment. The overestimation of ARGs by dye-based qPCR suggests its inappropriateness for ARG detection in environmental sample. The novel mPCR-NGS and quantitative metagenomic sequencing show promises in high throughput detection and quantification of target genes for environmental monitoring.
On The Large And Small Strain Cyclic Behavior Of Sands
(University of Hawaii at Manoa, 2019) Doygun, Ogul; Brandes, Horst; Civil Engineering
Monotonic, cyclic and shear wave response of five different quartz and silica sands was investigated from a varied and extensive data base consisting of drained monotonic direct simple shear tests, undrained cyclic direct simple shear tests, undrained cyclic triaxial tests and shear wave velocity tests. Test data sets were obtained from the experimental studies conducted by previous researchers. Approximately 500 tests in all were analyzed to examine cyclic sand behavior at large strains (0.1% to 4%) and small strains (less than 0.1%) under a range of constituent and initial conditions. The findings are presented in three chapters. The overall objective of this research is to obtain a better understanding of the strength and degradation characteristics of sands over a wide range of strains for various constituent and initial parameters. Extensive studies in the past showed that sand behavior becomes significantly nonlinear at large strains. The application of linear equivalent methods for shear strains larger than 0.1% can lead to erroneous results in the calculation of degradation parameters of sands. Numerical analyses and constitutive models are helpful to consider the nonlinear behavior of soil at these large strains. However, numerical models are required to be calibrated based on experimental data. The question is how to perform a reliable calibration with experimental results for high strains where the standard linear equivalent methods applied to laboratory experimental data becomes erroneous. This question was the main motivation of this study. The overall contribution here can be summarized as the development of a new calculation method to evaluate soil damping ratio more realistically at large strains (i.e., 0.1% to 4% shear strain, or the onset of liquefaction), and investigating the effect of various parameters on the soil behavior at these large strains with this new method. In order to make a better assessment on the plausibility of the new method, sand behavior was investigated both in the small and large strain range by means of laboratory experimental data on the monotonic and cyclic strength of a series of sands, as well as on the shear wave velocity response of some of these sands. In Chapter 1, the behavior of sands was examined under drained monotonic and undrained cyclic loading at moderately small to large strains. A previous data set developed at the University of Hawaii was used for this. This allowed consideration of the combined effects of gradation and fines content on sand behavior. The data analysis was extended to the range of very small strains by means of pre-shear and post-liquefaction shear wave velocity measurements. The combined effect of gradation and fines content represents a unique investigation, as previous studies have focused either solely on the fines content, or solely on gradation characteristics. Earlier studies on the effects of fines content typically involved combination of a clean sand base with various amounts of non-plastic silt and clay fractions, which can lead to unnatural gradations, especially at the transition from fine sand to silt and clay. A more careful approach, as followed in this study, is based on experimental data from assembled gradations that cover a range of smooth grain size distributions spanning from coarse sand to silt and clay sizes. Both poorly graded and well-graded distributions were considered. The key parameters in this study were the amount of fines (fines content FC), texture (mean grain size D50) and gradation (uniformity coefficient Cu). Monotonic and cyclic response was investigated with regard to these parameters. The main findings of Chapter 1 show that the overall monotonic, cyclic and shear wave behavior of sands is primarily a function of the amount of non-plastic fines and gradation plays a secondary but still important role. Whereas static shear strength of clean sands decreases slightly with a decreasing mean grain size, cyclic shear strength and shear wave velocity appear to be relatively independent of D50. An increase in Cu leads to a decrease both in the static and cyclic strength of sands. Shear wave transmission becomes slower with an increase in Cu, which indicates less stiffness of the sand, as can be assessed by the initial shear modulus from shear wave velocity measurements. Addition of small amount of fines causes an initial strength increase in both static and cyclic tests, which is followed by a continuous decrease after a threshold value of fines (in static tests less than 5%, in cyclic tests around 15%). The drop in the cyclic strength by addition of fines was more pronounced when Cu increased, indicating the important role of the gradation parameter Cu on silty sands, although the major effect is still the amount of fines. Trends in post-liquefaction shear wave measurements over different gradations and fines contents also indicate that fines content has a more significant effect on the overall sand behavior than the gradation does. Chapter 2 describes a new method developed in this study to calculate damping ratio of sands from undrained, load-controlled cyclic tests. Different calculation approaches available in the literature were first examined in terms of their plausibility in the high strain range. The data analysis on five widely ranging sands covering a significant set of initial conditions shows that the available linear equivalent methods of damping calculation lead to erroneous results, starting from shear strains around 0.1%, due to the observed highly nonlinear behavior of sands at large strains. The new numerical method calculates a more realistic damping value, and this follows from consideration of the pore water pressure accumulation during undrained testing. The new computational method follows the natural form of every hysteresis loop instead of relying on approximations inherent in linear equivalent methods. The main findings of the Chapter can be summarized as follows: 1) A new method is developed, validated and implemented numerically to estimate damping more accurately in laboratory cyclic direct simple shear and triaxial tests, which is also deemed to yield more plausible results at high and very high strains (larger than 1% shear), for which there is very little published experimental data in the literature. 2) Previous small-strain studies are based largely on strain-controlled cyclic tests, whereas the new method is developed for undrained load-controlled cyclic triaxial or direct simple shear tests, which are the most common types of laboratory cyclic tests. 3) A new guideline for damping ratio of clean sands covering a very wide range of shear strains (0.1 to 4%) is proposed as an alternative to the classic bounds by Seed and Idriss (1971). Almost all previous laboratory studies document the damping ratio behavior of sands only up to a shear strain level of about 1%. This new chart extends the bounds to 4% strain and is more helpful for the estimation of pre-liquefaction damping behavior of sands, given that failure state during an earthquake is very likely to occur at shear strains well in excess of 1%. These relatively large strains can become quite important in many practical projects, such as in the design of offshore platforms, soil embankments, excavations, slopes, levees, earth dams, dikes, etc. Chapter 2 finds a clear relationship between cyclic shear data and pore water pressure accumulation in undrained tests. While previous studies have suggested that there is a correlation between dissipated energy during cyclic shear and accumulated excess pore water pressure in undrained tests, a re-interpretation of previous test results on five different sands with various initial material properties and test conditions indicates that there is a distinct correlation between stored strain energy and accumulated pore water pressure, which was used to validate the new calculation method to compute damping from undrained cyclic triaxial and direct simple shear tests. The newly developed method leads to a new interpretation of damping behavior at large strains, which is distinctly different from trends noted by earlier studies that are based on variations of the linear equivalent method. In Chapter 3, the new method to compute damping is applied to a range of data sets from various sources in order to understand the effects of constitutive and initial state parameters on the damping behavior of sands at high strains. The controlling parameters of interest include shear strain, number of cycles, cyclic stress ratio, void ratio, cyclic strength, gradation, confining stress, non-plastic fines content and over-consolidation ratio. Other parameters affecting the damping behavior are also considered, such as initial shear stress, drainage, degree of saturation, frequency of loading, and plastic fines content. The newly calculated damping ratios at high strains are consistent with those based on linear equivalent methods at small strains. A significant correlation between cyclic strength and damping ratio further verifies the plausibility of the proposed calculation method. At constant cyclic stress ratio, confining stress and void ratio, a decrease in cyclic strength (e.g., due to increasing non-plastic fines content) leads to a faster material degradation (smaller number of cycles to liquefaction) and larger energy dissipation, resulting in a larger damping ratio. On the other hand, a soil specimen with higher cyclic strength requires more loading cycles to liquefy due to a slower material degradation and smaller energy dissipation (smaller damping ratio) at similar high strains. The proposed damping ratio bounds for a wide range of clean sands in Chapter 2 are also in a good agreement with test results for sands with non-plastic fines content up to 25%. The results from Chapter 2 and 3 also suggest that energy-based liquefaction assessment is inherently superior to stress- or strain-based liquefaction methods. Due to the strong correlation between cyclic strength and damping ratio, general cyclic strength evaluations (e.g. increase or decrease in cyclic strength) can substitute for assessments based on damping ratio, and this may be more convenient in many cases. Chapter 4 provides the major conclusions of this study. In addition, recommendations are made for further improvements to the new damping calculation method so that it can be extended to other testing conditions. Additional recommendations are made for the development of a nonlinear equivalent calculation method for evaluating shear modulus from cyclic experimental data. Other recommendations are presented on the damping behavior of soils during the liquefaction and post-liquefaction phase. The Appendix includes Matlab scripts, which were developed to analyze existing laboratory data sets. Scripts were developed to calculate damping based on four different linear approaches, and also for the newly devised method. Additional scripts were developed for evaluating linear equivalent shear modulus based on different approaches. Other scripts are presented to analyze the net energy gain portions of pore water pressure data with regard to dissipated and stored energy.
Estimation Of Turbulent Heat Fluxes Via The Synergistic Assimilation Of Land Surface Temperature, Air Temperature And Specific Humidity Into A Variational Data Assimilation Model
(University of Hawaii at Manoa, 2019) Tajfar, Elahe; Bateni, Sayed M.; Civil Engineering
The balance of energy at the Earth's surface is linked to the overlying atmospheric boundary layer (ABL). The sensible (H) and latent (LE) heat fluxes are important components of Earth’s radiation budget and its climate system, which directly influence the properties of the boundary layer and characterize exchange of heat and moisture between the land surface and its overlying atmosphere. Therefore, their accurate estimation is of crucial importance for a better understanding of land surface-atmosphere exchange processes and obtaining the heat and moisture budgets. Different approaches have been developed to estimate turbulent heat fluxes (i.e., H and LE). A number of studies used time-series of air temperature and specific humidity observations to estimate turbulent heat fluxes. These works require the specification of surface roughness lengths for heat and momentum and/or ground heat flux, which are often unavailable. This study estimates turbulent heat fluxes and the atmospheric boundary layer (ABL) height, potential temperature, and humidity by assimilating sequences of air temperature and specific humidity into an atmospheric boundary layer model within a new variational data assimilation (VDA) framework. The unknown parameters of the VDA system are neutral bulk heat transfer coefficient (CHN) and evaporative fraction (EF). It needs neither the surface roughness parameterization nor ground heat flux measurements. The performance of the developed VDA approach is tested over the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) site for the summer of 1987 and 1988. The results show that the developed VDA framework is capable of estimating the unknown parameters (i.e., EF and CHN) reasonably well. The developed VDA model can predict the turbulent heat fluxes fairly accurately at the FIFE site. In addition, the ABL height, specific humidity, and potential temperature estimates from the VDA system are reasonably close to those inferred from the radiosondes both in terms of magnitude and diurnal trend. The introduced VDA framework is advanced by the synergistic assimilation of LST, air temperature and specific humidity into a coupled land surface-ABL model. The augmented VDA system is also validated at the FIFE sites. It outperforms the previous study in which air temperature and specific humidity were assimilated. Finally, both developed VDA approaches are tested at five sites (namely, Desert, Audubon, Bondville, Brookings, and Willow Creek) with contrasting climatic and vegetative conditions. The results show that the first VDA system (that assimilates reference-level air temperature and specific humidity) performs well at wet/densely vegetated sites (e.g., Willow Creek), but its performance degrades at dry/slightly vegetated sites (e.g., Desert). These outcomes show that the sequences of reference-level air temperature and specific humidity have more information on the partitioning of available energy between the sensible and latent heat fluxes in wet and/or densely vegetated sites than the dry and/or slightly vegetated sites. The second VDA approach (that assimilates LST, reference-level air temperature and specific humidity) outperforms the first approach that assimilated only the state variables of atmosphere (i.e., reference-level air temperature and humidity), and can accurately estimate turbulent heat fluxes over a wide variety of environmental conditions.

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