Civil & Environmental Engineering

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3D IMAGE ANALYSIS OF CT DATA OF CONCRETE CYLINDER SUNDERGOING DELAYED ETTRINGTIE FORMATION
(2019) Shi, Kuo; Amde, Amde M; Livingston, Richard A; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The strains in a concrete caused by delayed ettringite formation (DEF) are conventionally expressed in terms of the one-dimensional linear expansion. However, concrete is not a homogeneous material, and differences in the volume change between the inert aggregates and the reactive cement paste will produce variations in local displacements that cannot be detected by the linear expansion variable. With CT slices offered by Simultaneous neutron and X-ray computed tomography (SNXCT), this thesis applies image analysis algorithms to quantify the distortion of cylinder over time due to delayed ettringite formation. The research reported in this thesis concerned the development of several MATLAB programs to apply image analysis algorithms to quantify the distortion of cylinder over time in terms of summary variables. These included mean radial expansion, deviation from circularity, vertical tilt angle and rotation, void area fraction and the displacement of microbead internal reference points.
A Novel Framework for Sustainable Traffic Safety Programs Using the Public as Sensors of Hazardous Road Information
(MDPI, 2018-10-26) Chung, Younshik; Won, Minsu
Traditionally, traffic safety improvement programs (TSIPs) have been based on the number of crashes at a specific location or their severity. However, the crash datasets used for such programs are obtained from the police and include two limitations: not all crashes are collected by the police (most minor and near-miss crashes are not reported), and the traditional process uses crash data recorded for the past two or three years (meaning most data inevitably include a time lag). To overcome these limitations, this study proposes a new approach for a TSIP based on citizen participation through an online survey that is broadcasted through social media. The method uses the public as sensors of hazardous road information, which means that information can be collected on individual experiences of minor crashes and latent risk factors, such as near misses and traffic conflicts. To demonstrate this approach, a case study was carried out in a small district in the city of Goyang, Korea, which has one of the highest usage rates of social media technologies. The proposed method and a traditional method were both assessed.
ACCELERATING RESTORATION THROUGH INFORMATION-SHARING: UNDERSTANDING OPERATOR BEHAVIOR FOR IMPROVED MANAGEMENT OF INTERDEPENDENT INFRASTRUCTURE
(2024) Yazdisamadi, Mohammadreza; Reilly, Allison C.; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation examines the roles that organizations and individuals play in restoring interdependent infrastructure following disasters through three studies. In the first study, we focus on how operator heuristics affect the collective restoration speed of three interdependent infrastructure (electric power, chilled water, and IT networks). We do this by developing a novel framework that embeds an interdependent infrastructure network within an agent-based model that mimics the decisions and patterns observed of actual operators. The study sheds light on how coordination and information exchange by separate infrastructure parties affect decisions and thus restoration outcomes. In the second study, we examine recovery times and total unmet demand for the same three interconnected infrastructure systems assuming a variable fraction of node removals. The work is decomposed by the extent to which operators share information and coordinate strategies, enabling us to identify at what fraction of network failure does coordination and information sharing become beneficial. Our study indicates that prioritizing restoration based on node centrality produces the speediest recovery. We also show that communication among organizations may improve collective performance by as much as 50%. Our final research project uses a serious game, Breakdown, focused on restoration of interdependent infrastructure to assess whether engineering graduate students gain a deeper appreciation for the complexity of interdependent infrastructure and socio-technical systems more broadly. This is the first serious game designed to emphasize the value of cooperation, communication, and strategy in times of crisis in the field of interdependent infrastructure. As a result of playing Breakdown, graduate students demonstrated statistically significant improvements in engineering decision-making under uncertainty and sociotechnical systems concepts. As a result of this dissertation, the interdependent infrastructure community gains insight into (1) how individual operators' behavior influences the speed at which interdependent infrastructure systems recover; (2) how policies and procedures, like sharing information and cooperating, can help improve outcomes; and (3) the ways to teach graduate engineering students about socio-technical systems effectively. Using an agent-based model simulation, it quantifies the effects of human behavior, communication, and cooperation on recovery outcomes. By using a serious game, Breakdown, it proposes an innovative way to teach graduate engineering students about socio-technical systems.
ACCESSIBILITY BASED EVALUATION OF COASTAL RURAL COMMUNITIES’ VULNERABILITY TO COASTAL FLOODING AND THEIR ADAPTATION OPTIONS
(2022) Yahyazadeh Jasour, Zeinab; Reilly, Allison C; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Global climate change and sea-level rise will cause significant risks to coastal communities. To make inclusive and cost-effective adaptation planning decisions, we need to understand who may be impacted and when. Currently, planning literature generally focuses on housing impacts; when will a house be inundated, and what adaptation strategies are useful to keep a house habitable? Housing, though, is only one of many types of infrastructures people need to reside in an area. Reliable roads are another. This dissertation conducts an analysis of parcel-level impacts of SLR on local residents’ ability to reach key amenities such as emergency services, grocery stores, and schools. Furthermore, it strategically evaluates where road protection should be implemented so that access is maintained in an equitable manner. Next, I use the accessibility analysis to identify the important roads for gathering high-resolution flood data to improve the accuracy of the analysis. I use Dorchester County, Maryland, U.S., as a case study. It is an extremely low-lying rural county and is expected to shrink in half by the end of the century due to SLR. The results from the case study indicate that some parcels are not expected to be inundated by SLR but are expected to experience accessibility impacts. Road protection appears to be a temporary strategy that can buy time for long-term adaptation strategies such as relocation. However, the protection strategies should be cautiously selected based on decision-makers priorities. The insight obtained by this dissertation highlights that when policy and decision-makers are deciding among adaptation strategies, they need to reach some level of consensus about assumptions for which a possible future is planned, and also the trade-off between increasing accessibility levels and balancing the distribution of accessibility among different demographic groups.
ACTIVE RELOCATION AND DISPATCHING OF HETEROGENEOUS EMERGENCY VEHICLES
(2014) Sharifi, Elham; Haghani, Ali; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
An emergency is a situation that causes an immediate risk to the property, health, or lives of civilians and can assume a variety of forms such as traffic accidents, fires, personal medical emergencies, terrorist attacks, robberies, natural disasters, etc. Emergency response services (ERSs) such as police, fire, and medical services play crucial roles in all communities and can minimize the adverse effects of emergency incidents by decreasing the response time. Response time is not only related to the dispatching system, but also has a very close relationship to the coverage of the whole network by emergency vehicles. The goal of this dissertation is to develop a model for an Emergency Management System. This model will dynamically relocate the emergency vehicles to provide better coverage for the whole system. Also, when an emergency happens in the system the model will consider dispatching and relocation problem simultaneously. In addition, it will provide real-time route guidance for emergency vehicles. In summary, this model will consider three problems simultaneously: area coverage, vehicle deployment, and vehicle routing. This model is event-based and will be solved whenever there is an event in the system. These events can be: occurrence of an emergency, change in the status of vehicles, change in the traffic data, and change in the likelihood of an emergency happening in the demand nodes. Three categories of emergency vehicle types are considered in the system: police cars, ambulances, and fire vehicles. The police department is assumed to have a homogeneous fleet, but ambulances and fire vehicles are heterogeneous. Advanced Life Support (ALS) and Basic Life Support (BLS) ambulances are considered, along with Fire Engines, Fire Trucks, and Fire Quints in the fire vehicle category. This research attempts to provide double coverage for demand nodes by non-homogenous fleet while increasing the equity of coverage of different demand nodes. Also, the model is capable of considering the partial coverage in the heterogeneous vehicle categories. Two kinds of demand nodes are considered, ordinary nodes and critical nodes. Node demands may vary over time, so the model is capable of relocating the emergency fleet to cover the points with highest demand. In addition, an attempt is made to maintain work load balance between different vehicles in the system. Real-world issues, such as the fact that vehicles prefer to stay at their home stations instead of being relocated to other stations and should be back at their home depots at the end of the work shift, are taken into account. This is a unique and complex model; so far, no study in the literature has addressed these problems sufficiently. A mathematical formulation is developed for the proposed model, and numerical examples are designed to demonstrate its capabilities. Xpress 7.1 is used to run this model on the numerical examples. Commercial software like Xpress can be used to solve the proposed model on small-size problems, but for large-size and real-world problems, an appropriate heuristic is needed. A heuristic method that can find good solutions in reasonable time for this problem is developed and tested on several cases. Also, the model is applied to a real-world case study to test its performance. To investigate the model's behavior on a real-world problem, a very sophisticated simulation model that can see most of the details in the system has been developed and the real case study data has been used to calibrate the model. The results show that the proposed model is performing very well and efficient and it can greatly improve the performance of emergency management centers.
Adjustment Factors and Applications for Analytic Approximations of Tour Lengths
(2021) Choi, Youngmin; Schonfeld, Paul M.; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The shortest tour distance for visiting all points exactly once and returning to the origin is computed by solving the well-known Traveling Salesman Problem (TSP). Due to the large computational effort needed for optimizing TSP tours, researchers have developed approximations that relate the average length of TSP tours to the number of points n visited per tour. The most widely used approximation formula has a square root form: √n multiplied by a coefficient β. Although the existing models can effectively approximate the distance for conventional vehicles with large capacities (e.g., delivery trucks) where n is large, approximations that seek to cover large ranges of n, possibly to infinity, tend to yield poorer results for the small n values. Thus, this dissertation focuses on approximation models for the small n values, which are needed for many practical applications, such as for some recent delivery alternatives (e.g., drones). The proposed models show promise in analyzing the real-world problems in which actual tours serve few customers due to limited vehicle capacity and incorporate realistic constraints, such as the effects of a starting point location, geographical restrictions on movements, demand patterns, and service area shapes. The dissertation may open new research avenues for analyzing the new transportation alternatives and provide guidelines to planners for choosing appropriate models in designing or evaluating transportation problems. Approximation models are estimated from the following experiments: 1) a total of 60 cases are developed by considering various factors, such as point distributions and shapes of service areas. 2) Solution methods for TSP instances are compared and chosen. 3) After the TSPs are optimized for each n, the TSP tour lengths are averaged. 4) Lastly, models for the averaged TSP tour lengths are fitted with ordinary least squares (OLS) regression. After the approximations are developed, some possible extensions are explored. First, adjustment factors are designed to integrate the 60 cases within one equation. With those factors, it can be understood how approximation varies with each classification. Next, the approximations considering stochastic customer presence (i.e., probabilistic TSP) are proposed. Third, the approximated tour lengths are compared with the optimal solutions of vehicle routing problem (VRP) in actual rural and urban delivery networks. Here, some additional factors, such as a circuity factor and service zone shape, are discussed. Lastly, the proposed methodology is applied to formulate and explore various types of existing and hypothetical delivery alternatives.
ADVANCED DATA ANALYTICS AND MESOSCOPIC DYNAMIC TRAFFIC ASSIGNMENT SIMULATION FOR TRAFFIC IMPACT ANALYSIS OF MARYLAND CASINOS
(2019) Donaldson, David; Zhang, Lei; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Three full-service casinos recently opened in Maryland: Live! Casino at the Arundel Mills Mall (June 2012), Horseshoe in Downtown Baltimore (August 2014), and MGM at the National Harbor (December 2016). The increased travel demand associated with such large entertainment complexes prompted an effort to quantify each facility’s impact on regional and local traffic patterns; therefore, a three-pronged analysis was conducted. First, historic vehicle probe data were analyzed to quantify and visualize the observed, local traffic impact for selected months before and after each casino became operational. Subsequently, an open-source mesoscopic DTA simulator named DTALite modeled the regional impact of the before/after scenarios as well as a special event scenario (e.g. Baltimore Ravens’ football game). The paper’s final component explored two innovative trip generation estimation methods to supplement the ITE Manual’s data limitation for casinos by utilizing aggregated mobile device trip data and an origin-demand adjustment system imbedded within DTALite. Ultimately, the data analytics and simulation-based modeling revealed no major traffic impact was generated by any casino. Moreover, upon comparison with ground truth count data, the origin-demand estimation technique out-performed both the ITE-based and location-based trip estimation methods.
Advanced Denitrification in Bioretention Systems Usinging Woodchips as a Primary Organic Carbon Source
(2013) Peterson, Ian James; Davis, Allen P; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Bioretention systems still lack the ability to effectively mitigate nitrogen concentrations from urban stormwater. Column tests were conducted to evaluate the effect of nitrate concentration, stormwater retention time, limestone addition, and woodchip species, size, and mass percentage on the bioretention denitrification process. Denitrification of artificial stormwater appeared to follow pseudo-first-order kinetics. A 0.8 day average retention time showed the highest nitrate removal percentage of 82.4 + 0.4%. Longer retention times correspond to greater removal efficiency. Willow Oak and Red Maple woodchips resulted in the highest total nitrogen removal efficiencies at 61.9 + 0.8% and 61.8%, respectively. Smaller woodchips and higher woodchip mass percentage corresponded to greater nitrate removal efficiencies, but also higher organic nitrogen leaching. Media containing 4.5% 5 mm Willow Oak woodchips by mass represented optimum conditions with a pseudo-first-order denitrification rate of 4.1 + 4.6 day-1 with nitrate concentrations of 1.5 to 4.5 mg/L N.
Advancing Scientific Knowledge: Ethical Issues in the Journal Publication Process
(MDPI, 2017-12-31) McCuen, Richard H.
The goal of this paper is to assess the journal publication process from value and ethical perspectives. The specific objectives are: (1) To define fundamental values relevant to scientific journal publication; (2) To identify stakeholders involved in professional journals and their value rights and responsibilities; (3) To discuss the steps of the journal publication process where ethical dilemmas arise and the potential influences of such dilemmas on the advancement of knowledge; and (4) To summarize actions that can minimize unethical practices throughout the steps of the publication process. Values such as honesty, efficiency, accountability, and fairness will be discussed. Issues related to the various stakeholders such as self-citation, plagiarism, dual publication, a lack of timeliness, and issues related to authorship will be a primary focus.
An Agent-Based Model To Examine Housing Price, Household Location Choice, And Commuting Times In Knox County, Tennessee
(2007-08-22) Mulbrandon, Matthew; Clifton, Kelly; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The research conducted for this thesis uses an agent-based model (ABM) to simulate housing price, location, and journey to work (JTW) times for households in Knox County, Tennessee. The model is a unique hybrid, combining analytic functions and agents that typically have been used separately for theoretical urban research in very simplified urban landscapes. At the same time it uses data from a real urban area to run and calibrate the model, which is common for statistically-based or gravity models. There are two goals for this simulation; first to examine the feasibility of this approach in urban modeling, second to test the effect of altering transportation times and preferences on agent behavior. Results show this approach can fit real data and represent urban processes reasonably well. In addition several interesting and surprising results are reported from model runs.
Agent-Based Models of Highway Investment Processes: Forecasting Future Networks under Public and Private Ownership Regimes
(2012) Yusufzyanova, Dilya; Zhang, Lei; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The present highway funding system, especially fuel taxes, may become a less reliable revenue source in the future, while the transportation public agencies do not have sufficient financial resources needed to meet the increasing traffic demand. In the last two decades there has been increasing interest in utilizing private sector to develop, finance and operate new and existing roadways in the United States. While transportation privatization projects have shown signs of success, it is not always clear how to measure the true benefits associated with these projects for all stakeholders, including the public sector, the private sector and the public. "Win-win" privatization agreements are tricky to make due to conflicting nature of the various stakeholders involved. Therefore, there is a huge need to study the welfare impacts of various road privatization arrangements for the society as a whole, and the financial implications for private investors and public road authorities. In order to address these needs, first, an empirical analysis is performed to study the investment decision processes of public transportation agencies. Second, the agent-based decision-making model is developed to consider transportation investment processes at different levels of government which forecasts future transportation networks and their performance under both existing and alternative transportation planning processes. Third, various highway privatization schemes currently practiced in the U.S. are identified and an agent-based model for analyzing regulatory policies on private-sector transportation investments is developed. Fourth, the above mentioned models are demonstrated on the networks with grid and beltway topologies to study the impacts of topology configuration on the privatization arrangements. Based on the simulation results of developed models, a number of insights are provided about impacts of ownership structures on the socio-economic performance in transportation systems and transportation network changes over time. The proposed models and the approach can be used in long-run prediction of economic performance intended for describing a general methodology for transportation planning on large networks. Therefore, this research is expected to contribute significantly to the understanding and selecting proper road privatization programs on public networks.
Agricultural practices influence foliar endophytic communities in coffee plants of different varieties
(Wiley, 2023-02-16) Castillo-Gonzalez, Humberto; Bloomberg, Joshua; Alvarado-Picado, Eduardo; Yarwood, Stephanie; Chaverri, Priscila
Fungal endophytes are pivotal components of a plant's microbiome, profoundly impacting its health and fitness. Yet, myriad questions remain concerning the intricate interactions between these microorganisms and their hosts, particularly in the context of agriculturally important plants such as Coffea arabica. To bridge this knowledge gap and provide a comprehensive framework, this study investigated how farming practices shape the taxonomic and functional diversity of phylloplane endophytes in coffee. Coffee plant leaves from two distinct producing regions in Costa Rica were sampled, ensuring the representation of various coffee varieties (Obatá, Catuaí, and Caturra), agricultural management methods (organic vs. conventional), sun exposure regimes (full sunlight/monoculture vs. natural shade/agroforestry), and leaf developmental stages (newly emerged asymptomatic vs. mature leaves). Fungal communities were characterized by employing both culture-dependent and independent techniques (internal transcribed spacer 2 nuclear ribosomal DNA metabarcoding). The results showed a greater diversity of endophytes in mature leaves and conventionally managed plants, with coffee variety exerting an unclear influence. The effect of sun exposure was surprisingly negligible. However, data emphasize the benefits of agroforestry and organic farming, which are linked to reduced putative pathogens and heightened levels of potentially mutualistic fungi, fostering functionally diverse communities. Despite the role that plant microbiomes might play in agricultural production, the knowledge to shape endophytic communities through breeding or management is lacking. The results from this study provide a framework to understand how both plant and agricultural practices influence endophyte diversity within coffee crops. These insights hold promise for guiding future efforts to manipulate coffee microbial communities effectively.
Air Express Network Design with Hub Sorting
(2007-11-05) Ngamchai, Somnuk; Schonfeld, Paul M.; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This dissertation examines an innovative strategic operation for next day air package delivery. The proposed system, in which some packages are sorted twice at two distinct hubs before arriving at their destinations, is investigated for its potential savings. A two-stage sorting operation is proposed and compared to the currently operated single-stage sorting operation. By considering the endogenous optimization of hub sorting and storage capacities, cost minimization models are developed for both operations and used for performance comparison. Two solution approaches are presented in this study, namely the Column Generation (CG) approach and the Genetic Algorithm (GA) approach. The first method is implemented to optimize the problem by means of linear programming (LP) relaxation, in which the resulting model is then embedded into a branch-and-bound approach to generate an integer solution. However, for solving realistic problem sizes, the model is intractable with the conventional time-space formulation. Therefore, a Genetic Algorithm is developed for solving a large-scale problem. The GA solution representation is classified into two parts, a grouping representation for hub assignment and an aircraft route representation for aircraft route cycles. Several genetic operators are specifically developed based on the problem characteristics to facilitate the search. After optimizing the solution, we compare not only the potential cost saving from the proposed system, but also the system's reliability based on its slack. To provide some insights on the effects of two-stage operation, several factors are explored such as the location of regional hubs, single and multiple two-stage routings and aircraft mix. Sensitivity analyses are conducted under different inputs, including different demand levels, aircraft operating costs and hub operating costs. Additional statistics on aircraft utilization, hub capacity utilization, circuity factor, average transfers per package, and system slack gain/loss by commodity, are analyzed to elucidate the changes in system characteristics.
An Algorithm for Crew Scheduling Problem with Bin Packing Features
(2008-11-14) Qiao, Wenxin; Haghani, Ali; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This thesis proposes a new approach for solving the traditional crew scheduling problem. The crew scheduling problem is solved with a bin packing approach in polynomial time. Based on the extensive research on the bin packing problem during the past 40 years, an algorithm that is proved to be the most efficient for solving most bin packing problems is selected and modified for application in the crew scheduling problem. A Modified Best-Fit-Decreasing Algorithm is proposed and discussed in this study. A case study is conducted using the proposed algorithm and the results are discussed.
An Alignment Optimization Model for a Simple Highway Network
(2008-04-07) KANG, MIN WOOK; SCHONFELD, PAUL; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
A new highway addition to an existing road network is typically considered for improving traffic performance in that road network. However, finding the new highway that best improves the existing network is a very complex problem since many factors affect the road construction. Besides changes in traffic flow patterns due to the new highway, various costs associated with highway construction as well as design specifications, safety, environmental, and political issues affect such a project. Until recently, many studies have dealt separately with the problems of highway alignment optimization and network design. However, no models have been found that integrate these problems comprehensively and effectively. This dissertation seeks to find a realistic three-dimensional highway alignment that best improves an existing network, while considering its costs, geometric design, and environmental impacts on the study area. To fulfill this objective, an effective network model is developed that can simultaneously optimize (i) highway alignments and (ii) junction points with existing roads. In addition, the model's optimization process considers traffic impacts due to the highway addition as well as factors associated with its construction. This dissertation starts by investigating the major cost components and important constraints in the highway design processes. Next, existing models for optimizing highway alignments are reviewed by assessing their advantages and disadvantages. Effective solution search methods are then developed to help solve the complex optimization problem. Development of the search methods is essential since an equilibrium traffic assignment as well as alignment optimization is undertaken in the proposed network model. Precise formulations of various highway costs and constraints are also developed for evaluating the various candidate alternatives. Cost functions for system improvements that can be obtained from the new highway addition are proposed. These are calculated based on the equilibrium traffic flows found from the assignment process. Complex geographical constraints including user preferences and environmentally sensitive areas are realistically represented, along with design standards required for highways. To represent highway alignments, sets of tangents, circular curves and transition spirals are used; in addition, three-leg structure models are also developed for representing the highway endpoints. Finally, several case studies are conducted to test the performance of the proposed models.
ALL ABOUT CONGESTION: MODELING DEPARTURE TIME DYNAMICS AND ITS INTEGRATION WITH TRAFFIC MODELS
(2011) Xiong, Chenfeng; Zhang, Lei; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
This thesis comprehensively studies departure time choice models, and analyzes the consequent system-level peak spreading effects. In modeling, the school of discrete choice models successfully reveals the user heterogeneity. A mixture logit model and a latent class model based on the notion of carpooling preference have been estimated. Then a novel positive approach has been developed, which avoids the assumptions of rationality and focuses on how individuals actually make departure time decisions. Following this positive theory, we specify Bayesian learning, empirically estimate search start and stopping conditions that vary among users, and empirically derive search and decision rules from a joint reveal/stated-preference survey dataset. This innovative behavioral model is integrated with a traffic simulation model for a real-world study. Findings from this application reveal the potential of the proposed model to capture network dynamics and behavioral reactions. This integrated framework also provides a valuable tool for the evaluation of new transportation infrastructures, policies, and operation strategies.
Alternative Dynamic Testing by Active Control
(2012) Wagman, Nicholas Alexander; Chang, Peter C; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
As the general public becomes increasingly aware of the seismic risk to structures, Americans expect assurance from structural engineering professionals that building designs are safe and reliable. Increasing public scrutiny places even greater emphasis on the need for research and validation of performance-based earthquake engineering designs. Current methods for experimental validation of designs with full-scale tests (e.g. shake table and pseudo dynamic testing) can be extremely expensive and the facilities necessary are not available at many universities. This thesis proposes an Alternative Dynamic Test which uses a properly scaled model test specimen and a desktop shake table to perform accurate experimental validation of structural designs. The methodology and laboratory setup of this testing method are discussed including the motor characterization and power requirements. Error approximation and practical implementation of the Alternative Dynamic Test are also addressed.
ANALYSES OF INFLUENTIAL FACTORS FOR ACCURATE DETERMINATION OF PEAK RATE FACTORS AND TIMES TO PEAK OF UNIT HYDROGRAPHS
(2017) Zhao, Tianming; McCuen, Richard H.; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Despite the availability of a number of sophisticated hydrologic models, the unit hydrograph (UH) is still one of the most widely used models for computing runoff hydrographs. The two-parameter gamma UH can be fully characterized by two parameters: the peak rate factor (PRF) and the time to peak (tpUH). Currently, obtaining accurate estimates of UH parameters is still a problem, especially for ungauged watersheds. The goal of this research was to analyze factors that influence estimates of UH parameters and to develop general guidelines that can assist in estimating UH parameters more accurately. A calibration model was developed for evaluating PRFs and tpUHs simultaneously from rainfall-runoff data. The effects of various influential factors were identified and investigated based on analyses of both synthetic and measured rainfall-runoff data. Results showed that the accuracy of calibrated UH parameters is affected by the rainfall characteristics, the time offset, the nonuniformity of rainfall, the extent of nonlinear watershed processes, and the flexibility of the gamma probability distribution function. Guidelines were developed to assist UH users in interpreting the calibration results and calibrating UH parameters more accurately.
Analysis and behavior investigations of box girder bridges
(2010) Begum, Zakia; Fu, Chung C; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
Due to efficient dissemination of congested traffic, economic considerations, and aesthetic desirability horizontally curved steel box girder bridges have become increasingly popular nowadays in modern highway systems, including urban interchanges. Although significant research has been underway on advanced analysis for many years to better understand the behavior of all types of box-girder bridges, however, the results of these various research works are scattered and unevaluated. Hence, a clear understanding of more recent work on straight and curved box-girder bridges is highly desired. The non-composite steel section must support both the fresh concrete and the entire construction loads hence steel box girders are at their critical stage during construction. In the current study, non composite straight and curved steel boxes are analyzed with beam and shell elements using the three dimensional finite element analysis and their behavior is investigated. The present research addresses comparison using beam and shell element models of the straight and curved box girder bridge. This task involves examining the stress patterns obtained using static three-dimensional finite element modeling. Comparisons are made between stresses obtained for the straight and curved box girder bridges, from the beam element model and shell element model for each. Further, the finite element results are compared to the BEST center program DESCUS-II results. Finally, the parametric investigations are performed on the curved steel box model to evaluate the effects of several important parameters on the behavior of the girder.
ANALYSIS AND SIMULATION OF ENERGY USE AND COST AT A MUNICIPAL WASTEWATER TREATMENT PLANT
(2011) Feng, Yilu; Brubaker, Kaye L; Civil Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
The cost of electricity, a major operating cost of municipal wastewater treatment plants, is related to influent flow rate, power price, and power load. With knowledge of inflow and price patterns, plant operators can manage processes to reduce electricity costs. Records of influent flow, power price, and load are evaluated for Blue Plains Advanced Wastewater Treatment Plant. Diurnal and seasonal trends are analyzed. Power usage is broken down among treatment processes. A simulation model of influent pumping, a large power user, is developed. It predicts pump discharge and power usage based on wet-well level. Individual pump characteristics are tested in the plant. The model accurately simulates plant inflow and power use for two pumping stations [R2 = 0.68, 0.93 (inflow), R2 =0.94, 0.91(power)]. Wet-well stage-storage relationship is estimated from data. Time-varying wet-well level is added to the model. A synthetic example demonstrates application in managing pumps to reduce electricity cost.