Matching Items (21)
Filtering by
- All Subjects: engineering
- Creators: Liu, Yongming
Description
The construction industry in India suffers from major time and cost overruns. Data from government and industry reports suggest that projects suffer from 20 to 25 percent time and cost overruns. Waste of resources has been identified as a major source of inefficiency. Despite a substantial increase in the past few years, demand for professionals and contractors still exceeds supply by a large margin. The traditional methods adopted in the Indian construction industry may not suffice the needs of this dynamic environment, as they have produced large inefficiencies. Innovative ways of procurement and project management can satisfy the needs aspired to as well as bring added value. The problems faced by the Indian construction industry are very similar to those faced by other developing countries. The objective of this paper is to discuss and analyze the economic concerns, inefficiencies and investigate a model that both explains the Indian construction industry structure and provides a framework to improve efficiencies. The Best Value (BV) model is examined as an approach to be adopted in lieu of the traditional approach. This could result in efficient construction projects by minimizing cost overruns and delays, which until now have been a rarity.
ContributorsNihas, Syed (Author) / Kashiwagi, Dean (Thesis advisor) / Sullivan, Kenneth (Committee member) / Kashiwagi, Jacob (Committee member) / Arizona State University (Publisher)
Created2013
Description
This research examines the current challenges of using Lamb wave interrogation methods to localize fatigue crack damage in a complex metallic structural component subjected to unknown temperatures. The goal of this work is to improve damage localization results for a structural component interrogated at an unknown temperature, by developing a probabilistic and reference-free framework for estimating Lamb wave velocities and the damage location. The methodology for damage localization at unknown temperatures includes the following key elements: i) a model that can describe the change in Lamb wave velocities with temperature; ii) the extension of an advanced time-frequency based signal processing technique for enhanced time-of-flight feature extraction from a dispersive signal; iii) the development of a Bayesian damage localization framework incorporating data association and sensor fusion. The technique requires no additional transducers to be installed on a structure, and allows for the estimation of both the temperature and the wave velocity in the component. Additionally, the framework of the algorithm allows it to function completely in an unsupervised manner by probabilistically accounting for all measurement origin uncertainty. The novel algorithm was experimentally validated using an aluminum lug joint with a growing fatigue crack. The lug joint was interrogated using piezoelectric transducers at multiple fatigue crack lengths, and at temperatures between 20°C and 80°C. The results showed that the algorithm could accurately predict the temperature and wave speed of the lug joint. The localization results for the fatigue damage were found to correlate well with the true locations at long crack lengths, but loss of accuracy was observed in localizing small cracks due to time-of-flight measurement errors. To validate the algorithm across a wider range of temperatures the electromechanically coupled LISA/SIM model was used to simulate the effects of temperatures. The numerical results showed that this approach would be capable of experimentally estimating the temperature and velocity in the lug joint for temperatures from -60°C to 150°C. The velocity estimation algorithm was found to significantly increase the accuracy of localization at temperatures above 120°C when error due to incorrect velocity selection begins to outweigh the error due to time-of-flight measurements.
ContributorsHensberry, Kevin (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Arizona State University (Publisher)
Created2013
Description
Structural/system health monitoring (SHM) and prognostic health management (PHM) are vital techniques to ensure engineering system reliability and safety during the service. As multi-functionality and enhanced performance are in demand, modern engineering systems including aerospace, mechanical, and civil applications have become more complex. The constituent and architectural complexity, and multisource sensing sources in modern engineering systems may limit the monitoring capabilities of conventional approaches and require more advanced SHM/PHM techniques. Therefore, a hybrid methodology that incorporates information fusion, nondestructive evaluation (NDE), machine learning (ML), and statistical analysis is needed for more effective damage diagnosis/prognosis and system safety management.This dissertation presents an automated aviation health management technique to enable proactive safety management for both aircraft and national airspace system (NAS). A real-time, data-driven aircraft safety monitoring technique using ML models and statistical models is developed to enable an early-stage upset detection capability, which can improve pilot’s situational awareness and provide a sufficient safety margin. The detection accuracy and computational efficiency of the developed monitoring techniques is validated using commercial unlabeled flight data recorder (FDR) and reported accident FDR dataset. A stochastic post-upset prediction framework is developed using a high-fidelity flight dynamics model to predict the post-impacts in both aircraft and air traffic system. Stall upset scenarios that are most likely occurred during loss of control in-flight (LOC-I) operation are investigated, and stochastic flight envelopes and risk region are predicted to quantify their severities.
In addition, a robust, automatic damage diagnosis technique using ultrasonic Lamb waves and ML models is developed to effectively detect and classify fatigue damage modes in composite structures. The dispersion and propagation characteristics of the Lamb waves in a composite plate are investigated. A deep autoencoder-based diagnosis technique is proposed to detect fatigue damage using anomaly detection approach and automatically extract damage sensitive features from the waves. The patterns in the features are then further analyzed using outlier detection approach to classify the fatigue damage modes. The developed diagnosis technique is validated through an in-situ fatigue tests with periodic active sensing.
The developed techniques in this research are expected to be integrated with the existing safety strategies to enhance decision making process for improving engineering system safety without affecting the system’s functions.
ContributorsLee, Hyunseong (Author) / Chattopadhyay, Aditi (Thesis advisor) / Liu, Yongming (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Fard, Masoud Yekani (Committee member) / Tang, Pingbo (Committee member) / Campbell, Angela (Committee member) / Arizona State University (Publisher)
Created2021
Description
National Airspace Systems (NAS) are complex cyber-physical systems that require swift air traffic management (ATM) to ensure flight safety and efficiency. With the surging demand for air travel and the increasing intricacy of aviation systems, the need for advanced technologies to support air traffic management and air traffic control (ATC) service has become more crucial than ever. Data-driven models or artificial intelligence (AI) have been conceptually investigated by various parties and shown immense potential, especially when provided with a vast volume of real-world data. These data include traffic information, weather contours, operational reports, terrain information, flight procedures, and aviation regulations. Data-driven models learn from historical experiences and observations and provide expeditious recommendations and decision support for various operation tasks, directly contributing to the digital transformation in aviation. This dissertation reports several research studies covering different aspects of air traffic management and ATC service utilizing data-driven modeling, which are validated using real-world big data (flight tracks, flight events, convective weather, workload probes). These studies encompass a range of topics, including trajectory recommendations, weather studies, landing operations, and aviation human factors. Specifically, the topics explored are (i) trajectory recommendations under weather conditions, which examine the impact of convective weather on last on-file flight plans and provide calibrated trajectories based on convective weather; (ii) multi-aircraft trajectory predictions, which study the intention of multiple mid-air aircraft in the near-terminal airspace and provide trajectory predictions; (iii) flight scheduling operations, which involve probabilistic machine learning-enhanced optimization algorithms for robust and efficient aircraft landing sequencing; (iv) aviation human factors, which predict air traffic controller workload level from flight traffic data with conformalized graph neural network. The uncertainties associated with these studies are given special attention and addressed through Bayesian/probabilistic machine learning. Finally, discussions on high-level AI-enabled ATM research directions are provided, hoping to extend the proposed studies in the future. This dissertation demonstrates that data-driven modeling has great potential for aviation digital twins, revolutionizing the aviation decision-making process and enhancing the safety and efficiency of ATM. Moreover, these research directions are not merely add-ons to existing aviation practices but also contribute to the future of transportation, particularly in the development of autonomous systems.
ContributorsPang, Yutian (Author) / Liu, Yongming (Thesis advisor) / Yan, Hao (Committee member) / Zhuang, Houlong (Committee member) / Marvi, Hamid (Committee member) / Ren, Yi (Committee member) / Arizona State University (Publisher)
Created2023
Description
The design of energy absorbing structures is driven by application specific requirements like the amount of energy to be absorbed, maximum transmitted stress that is permissible, stroke length, and available enclosing space. Cellular structures like foams are commonly leveraged in nature for energy absorption and have also found use in engineering applications. With the possibility of manufacturing complex cellular shapes using additive manufacturing technologies, there is an opportunity to explore new topologies that improve energy absorption performance. This thesis aims to systematically understand the relationships between four key elements: (i) unit cell topology, (ii) material composition, (iii) relative density, and (iv) fields; and energy absorption behavior, and then leverage this understanding to develop, implement and validate a methodology to design the ideal cellular structure energy absorber. After a review of the literature in the domain of additively manufactured cellular materials for energy absorption, results from quasi-static compression of six cellular structures (hexagonal honeycomb, auxetic and Voronoi lattice, and diamond, Gyroid, and Schwarz-P) manufactured out of AlSi10Mg and Nylon-12. These cellular structures were compared to each other in the context of four design-relevant metrics to understand the influence of cell design on the deformation and failure behavior. Three new and revised metrics for energy absorption were proposed to enable more meaningful comparisons and subsequent design selection. Triply Periodic Minimal Surface (TPMS) structures were found to have the most promising overall performance and formed the basis for the numerical investigation of the effect of fields on the energy absorption performance of TPMS structures. A continuum shell-based methodology was developed to analyze the large deformation behavior of field-driven variable thickness TPMS structures and validated against experimental data. A range of analytical and stochastic fields were then evaluated that modified the TPMS structure, some of which were found to be effective in enhancing energy absorption behavior in the structures while retaining the same relative density. Combining findings from studies on the role of cell geometry, composition, relative density, and fields, this thesis concludes with the development of a design framework that can enable the formulation of cellular material energy absorbers with idealized behavior.
ContributorsShinde, Mandar (Author) / Bhate, Dhruv (Thesis advisor) / Peralta, Pedro (Committee member) / Liu, Yongming (Committee member) / Jiao, Yang (Committee member) / Kwon, Beomjin (Committee member) / Arizona State University (Publisher)
Created2023
Description
Phase change materials (PCMs) are combined sensible-and-latent thermal energy storage materials that can be used to store and dissipate energy in the form of heat. PCMs incorporated into wall-element systems have been well-studied with respect to energy efficiency of building envelopes. New applications of PCMs in infrastructural concrete, e.g., for mitigating early-age cracking and freeze-and-thaw induced damage, have also been proposed. Hence, the focus of this dissertation is to develop a detailed understanding of the physic-chemical and thermo-mechanical characteristics of cementitious systems and novel coating systems for wall-elements containing PCM. The initial phase of this work assesses the influence of interface properties and inter-inclusion interactions between microencapsulated PCM, macroencapsulated PCM, and the cementitious matrix. The fact that these inclusions within the composites are by themselves heterogeneous, and contain multiple components necessitate careful application of models to predict the thermal properties. The next phase observes the influence of PCM inclusions on the fracture and fatigue behavior of PCM-cementitious composites. The compliant nature of the inclusion creates less variability in the fatigue life for these composites subjected to cyclic loading. The incorporation of small amounts of PCM is found to slightly improve the fracture properties compared to PCM free cementitious composites. Inelastic deformations at the crack-tip in the direction of crack opening are influenced by the microscale PCM inclusions. After initial laboratory characterization of the microstructure and evaluation of the thermo-mechanical performance of these systems, field scale applicability and performance were evaluated. Wireless temperature and strain sensors for smart monitoring were embedded within a conventional portland cement concrete pavement (PCCP) and a thermal control smart concrete pavement (TCSCP) containing PCM. The TCSCP exhibited enhanced thermal performance over multiple heating and cooling cycles. PCCP showed significant shrinkage behavior as a result of compressive strains in the reinforcement that were twice that of the TCSCP. For building applications, novel PCM-composites coatings were developed to improve and extend the thermal efficiency. These coatings demonstrated a delay in temperature by up to four hours and were found to be more cost-effective than traditional building insulating materials.
The results of this work prove the feasibility of PCMs as a temperature-regulating technology. Not only do PCMs reduce and control the temperature within cementitious systems without affecting the rate of early property development but they can also be used as an auto-adaptive technology capable of improving the thermal performance of building envelopes.
The results of this work prove the feasibility of PCMs as a temperature-regulating technology. Not only do PCMs reduce and control the temperature within cementitious systems without affecting the rate of early property development but they can also be used as an auto-adaptive technology capable of improving the thermal performance of building envelopes.
ContributorsAguayo, Matthew Joseph (Author) / Neithalath, Narayanan (Thesis advisor) / Rajan, Subramaniam D. (Committee member) / Mobasher, Barzin (Committee member) / Underwood, Benjamin (Committee member) / Liu, Yongming (Committee member) / Arizona State University (Publisher)
Created2018
Description
ABSTRACT
The problem of litigation and disputes in the construction sector is a major impediment to countries’ development goals. The purpose of this paper is to investigate the problem of high legal costs and long delays that arise due to litigation involving project owners, designers, contractors and other construction parties worldwide and in Saudi Arabia, as well as to give recommendation according to the outcomes of this research. The causes of litigious behavior in Saudi Arabia and other countries around the world were identified and documented, also the differences in litigation of the Saudi Arabian construction industry as compared to other countries were identified. Preliminary investigations revealed that there are some level of similarity in the nature of the causes. Thus, these causes were grouped into three main categories which are expectation factors, communications factors and documentation factors. Further research based on existing literature showed that the practices used to minimize litigation in the construction industry were investigated. The following delivery process were researched: design-build (DB) delivery method, Alliance Contracting, Construction Manager at Risk (CMAR), Best Value Approach, Integrated Project Delivery (IPD), and Public-Private Partnerships (PPPs), and the PIPS/PIRMS approach. These delivery methods were found to have issues, which means the methods by observation do not seem to be the ideal solution to minimize litigation in the construction industry. The only delivery method found to have no litigation issues was the PIPS/PIRMS approach.
The problem of litigation and disputes in the construction sector is a major impediment to countries’ development goals. The purpose of this paper is to investigate the problem of high legal costs and long delays that arise due to litigation involving project owners, designers, contractors and other construction parties worldwide and in Saudi Arabia, as well as to give recommendation according to the outcomes of this research. The causes of litigious behavior in Saudi Arabia and other countries around the world were identified and documented, also the differences in litigation of the Saudi Arabian construction industry as compared to other countries were identified. Preliminary investigations revealed that there are some level of similarity in the nature of the causes. Thus, these causes were grouped into three main categories which are expectation factors, communications factors and documentation factors. Further research based on existing literature showed that the practices used to minimize litigation in the construction industry were investigated. The following delivery process were researched: design-build (DB) delivery method, Alliance Contracting, Construction Manager at Risk (CMAR), Best Value Approach, Integrated Project Delivery (IPD), and Public-Private Partnerships (PPPs), and the PIPS/PIRMS approach. These delivery methods were found to have issues, which means the methods by observation do not seem to be the ideal solution to minimize litigation in the construction industry. The only delivery method found to have no litigation issues was the PIPS/PIRMS approach.
ContributorsAlmutairi, Saud (Author) / Kashiwagi, Dean (Thesis advisor) / Sullivan, Kenneth (Committee member) / Kashiwagi, Jacob (Committee member) / Arizona State University (Publisher)
Created2015
Description
Delays are a major cause for concern in the construction industry both globally and locally in Saudi Arabia. This paper identifies the main causes of delay in infrastructure projects in the holy city of Makkah (Saudi Arabia) and compares these with projects around the rest of the country and other Gulf countries as well. Data were obtained from 49 infrastructure projects that were undertaken by the owner and were analyzed quantitatively to understand the severity and causes of delay. 10 risk factors were identified in this study and these factors were grouped into four categories. The average delay in infrastructure projects in the city of Makkah was found to be 39%. The most severe cause of delay was found to be the land acquisition factor. This highlights the critical land ownership and acquisition issues that is prevailing in Makkah. In addition to this, other factors include contractors’ lack of expertise, haphazard underground utilities (line services), and re-designing. It is concluded that majority of delays were caused from the owner’s side as compared to contractors, consultants, and other project’s stakeholders. This finding was in line with the research findings of the Gulf Countries Construction (GCC) Industry’s literature as well. This study will fill an important practice and research gap for improving the efficiency in project delivery for infrastructure projects in the holy city of Makkah and the Gulf countries at large.
ContributorsElawi, Ghazi Saad A (Author) / Kashiwagi, Dean (Thesis advisor) / Sullivan, Kenneth (Committee member) / Kashiwagi, Jacob (Committee member) / Arizona State University (Publisher)
Created2015
Description
Fracture phenomena have been extensively studied in the last several decades. Continuum mechanics-based approaches, such as finite element methods and extended finite element methods, are widely used for fracture simulation. One well-known issue of these approaches is the stress singularity resulted from the spatial discontinuity at the crack tip/front. The requirement of guiding criteria for various cracking behaviors, such as initiation, propagation, and branching, also poses some challenges. Comparing to the continuum based formulation, the discrete approaches, such as lattice spring method, discrete element method, and peridynamics, have certain advantages when modeling various fracture problems due to their intrinsic characteristics in modeling discontinuities.
A novel, alternative, and systematic framework based on a nonlocal lattice particle model is proposed in this study. The uniqueness of the proposed model is the inclusion of both pair-wise local and multi-body nonlocal potentials in the formulation. First, the basic ideas of the proposed framework for 2D isotropic solid are presented. Derivations for triangular and square lattice structure are discussed in detail. Both mechanical deformation and fracture process are simulated and model verification and validation are performed with existing analytical solutions and experimental observations. Following this, the extension to general 3D isotropic solids based on the proposed local and nonlocal potentials is given. Three cubic lattice structures are discussed in detail. Failure predictions using the 3D simulation are compared with experimental testing results and very good agreement is observed. Next, a lattice rotation scheme is proposed to account for the material orientation in modeling anisotropic solids. The consistency and difference compared to the classical material tangent stiffness transformation method are discussed in detail. The implicit and explicit solution methods for the proposed lattice particle model are also discussed. Finally, some conclusions and discussions based on the current study are drawn at the end.
A novel, alternative, and systematic framework based on a nonlocal lattice particle model is proposed in this study. The uniqueness of the proposed model is the inclusion of both pair-wise local and multi-body nonlocal potentials in the formulation. First, the basic ideas of the proposed framework for 2D isotropic solid are presented. Derivations for triangular and square lattice structure are discussed in detail. Both mechanical deformation and fracture process are simulated and model verification and validation are performed with existing analytical solutions and experimental observations. Following this, the extension to general 3D isotropic solids based on the proposed local and nonlocal potentials is given. Three cubic lattice structures are discussed in detail. Failure predictions using the 3D simulation are compared with experimental testing results and very good agreement is observed. Next, a lattice rotation scheme is proposed to account for the material orientation in modeling anisotropic solids. The consistency and difference compared to the classical material tangent stiffness transformation method are discussed in detail. The implicit and explicit solution methods for the proposed lattice particle model are also discussed. Finally, some conclusions and discussions based on the current study are drawn at the end.
ContributorsChen, Hailong (Author) / Liu, Yongming (Thesis advisor) / Jiao, Yang (Committee member) / Mignolet, Marc (Committee member) / Oswald, Jay (Committee member) / Solanki, Kiran (Committee member) / Arizona State University (Publisher)
Created2015
Description
A roofing manufacturer wants to differentiate themselves from other roofing manufacturers based on performance information. However, construction industry has revealed poor performance documentation in the last couple of decades. With no current developed performance measurement model in the industry, two roofing manufacturers approached the research group to implement a warranty program that measures the performance information of their systems and applicators. Moreover, the success of any project in the construction industry heavily relies upon the capability of the contractor(s) executing the project. Low-performing contractors are correlated with increased cost and delayed schedules, resulting in end-user dissatisfaction with the final product. Hence, the identification and differentiation of the high performing contractors from their competitors is also crucial. The purpose of this study is to identify and describe a new model for measuring manufacturer performance and differentiating contractor performance and capability for two roofing manufacturers (Manufacturer 1 and Manufacturer 2) in the roofing industry. The research uses multiple years of project data and customer satisfaction data collected for two roofing manufacturers for over 1,000 roofing contractors. The performance and end-user satisfaction was obtained for over 7,000 manufacturers' projects and each contractor associated with that project for cost, schedule, and quality metrics. The measurement process was successfully able to provide a performance measurement for the manufacturer based on the customer satisfaction and able to identify low performing contractors. This study presents the research method, the developed measurement model, and proposes a new performance measurement process that entities in the construction industry can use to measure performance.
ContributorsGajjar, Dhaval (Author) / Kashiwagi, Dean (Thesis advisor) / Sullivan, Kenneth (Thesis advisor) / Kashiwagi, Jacob (Committee member) / Arizona State University (Publisher)
Created2016