A Building Information Modeling (BIM)-centric Digital Ecosystem for Smart Airport Life Cycle Management

An increasing number of new airport infrastructure construction and improvement projects are being delivered in today\u27s modern world. However, value creation is a recurring issue due to inefficiencies in managing capital expenditures (CapEx) and operating expenses (OpEx), while trying to optimize project constraints of scope, time, cost, quality, and resources. In this new era of smart infrastructure, digitalization transforms the way projects are planned and delivered. Building Information Modeling (BIM) is a key digital process technique that has become an imperative for today\u27s Architecture, Engineering, Construction and Operations (AECO) sector. This research suggests a BIM-centric digital ecosystem by detailing technical and strategic aspects of Airport BIM implementation and digital technology integration from a life cycle perspective. This research provides a novel approach for consistent and continuous use of digital information between business and functional levels of an airport by developing a digital platform solution that will enable seamless flow of information across functions. Accordingly, this study targets to achieve three objectives: 1- To provide a scalable know-how of BIM-enabled digital transformation; 2- To guide airport owners and major stakeholders towards converging information siloes for airport life cycle data management by an Airport BIM Framework; 3- To develop a BIM-based digital platform architecture towards realization of an airport digital twin for airport infrastructure life cycle management. Airport infrastructures can be considered as a System of Systems (SoS). As such, Model Based Systems Engineering (MBSE) with Systems Modeling Language (SysML) is selected as the key methodology towards designing a digital ecosystem. Applying MBSE principles leads to forming an integrating framework for managing the digital ecosystem. Furthermore, this research adopts convergent parallel mixed methods to collect and analyze multiple forms of data. Data collection tools include extensive literature and industry review; an online questionnaire; semi-structured interviews with airport owner parties; focus group discussions; first-hand observations; and document reviews. Data analysis stage includes multiple explanatory case study analyses, thematic analysis, project mapping, percent coverage analysis for coded themes to achieve Objective 1; thematic analysis, cluster analysis, framework analysis, and non-parametric statistical analysis for Objective 2; and qualitative content analysis, non-parametric statistical analysis to accomplish Objective 3. This research presents a novel roadmap toward facilitation of smart airports with alignment and integration of disruptive technologies with business and operational aspects of airports. Multiple comprehensive case study analyses on international large-hub airports and triangulation of organization-level and project-level results systematically generate scalable technical and strategic guidelines for BIM implementation. The proposed platform architecture will incentivize major stakeholders for value-creation, data sharing, and control throughout a project life cycle. Introducing scalability and minimizing complexity for end-users through a digital platform approach will lead to a more connected environment. Consequently, a digital ecosystem enables sophisticated interaction between people, places, and assets. Model-driven approach provides an effective strategy for enhanced decision-making that helps optimization of project resources and allows fast adaptation to emerging business and operational demands. Accordingly, airport sustainability measures -economic vitality, operational efficiency, natural resources, and social responsibility- will improve due to higher levels of efficiency in CapEx and OpEx. Changes in business models for large capital investments and introducing sustainability to supply chains are among the anticipated broader impacts of this study

Complications Associated with Local Anesthesia in Oral and Maxillofacial Surgery

One of the important attempts in clinical oral surgery practice is to maintain safe and effective local anesthesia. Dental procedures are frequently performed under local anesthesia; thus, drug-related complications are often encountered. It is mandatory to have a preoperative evaluation of the patient and choosing the proper local anesthetic agent. Various complications including hypersensitivity, allergy, overdosage, toxicity, hematoma, trismus, paresthesia, or neuralgia can be observed during practice. Therefore, the practitioner should be aware of the possible complications and management methods. The aim of this chapter is to review the preoperative and postoperative complications associated with the local anesthetic in oral and maxillofacial surgery practice. The prevention of measures and treatment of the complications is also emphasized

Building Information Modeling (BIM) Implementation for Sustainability Analysis: A Mega Airport Project Case Study

It has been generally perceived that decision-making processes for implementing sustainable solutions to building elements should be in design and pre-construction phases. This perception hinders the transformation of current non-sustainable buildings into sustainable ones. It has been realized that retrofitting existing buildings can be more beneficial in terms of time and cost compared to new construction. This study aims to show that implementation of Building Information Modeling (BIM) for energy analysis improves the retrofit planning process. This study explains that in practice, BIM tools provide significant opportunities for creation of Building Energy Modeling (BEM); and the outputs of BEM analysis can be readily used in selection of energy efficiency measures. The case study approach is used in this study. Accordingly, 3D energy models of the Istanbul Grand Airport Project have been created. A heuristic optimization depicts a clear picture of why it is necessary to incentivize transforming BIM to BEM for decision-making processes of retrofitting. Correspondingly, the study findings show that BIM implementations can provide cost and time savings for energy analysis practices

Stepwise positional-orientational order and the multicritical-multistructural global phase diagram of the s=3/2 Ising model from renormalization-group theory

The spin-3/2 Ising model, with nearest-neighbor interactions only, is the prototypical system with two different ordering species, with concentrations regulated by a chemical potential. Its global phase diagram, obtained in d=3 by renormalization-group theory in the Migdal-Kadanoff approximation or equivalently as an exact solution of a d=3 hierarchical lattice, with flows subtended by 40 different fixed points, presents a very rich structure containing eight different ordered and disordered phases, with more than 14 different types of phase diagrams in temperature and chemical potential. It exhibits phases with orientational and/or positional order. It also exhibits quintuple phase transition reentrances. Universality of critical exponents is conserved across different renormalization-group flow basins via redundant fixed points. One of the phase diagrams contains a plastic crystal sequence, with positional and orientational ordering encountered consecutively as temperature is lowered. The global phase diagram also contains double critical points, first-order and critical lines between two ordered phases, critical end points, usual and unusual (inverted) bicritical points, tricritical points, multiple tetracritical points, and zero-temperature criticality and bicriticality. The four-state Potts permutation-symmetric subspace is contained in this model

Renal complications of lipodystrophy: A closer look at the natural history of kidney disease

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/144612/1/cen13732_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/144612/2/cen13732.pd

A Building Information Modeling (bim)-centric Digital Ecosystem For Smart Airport Life Cycle Management

An increasing number of new airport infrastructure construction and improvement projects are being delivered in today’s modern world. However, value creation is a recurring issue due to inefficiencies in managing capital expenditures (CapEx) and operating expenses (OpEx), while trying to optimize project constraints of scope, time, cost, quality, and resources. In this new era of smart infrastructure, digitalization transforms the way projects are planned and delivered. Building Information Modeling (BIM) is a key digital process technique that has become an imperative for today’s Architecture, Engineering, Construction and Operations (AECO) sector. This research suggests a BIM-centric digital ecosystem by detailing technical and strategic aspects of Airport BIM implementation and digital technology integration from a life cycle perspective. This research provides a novel approach for consistent and continuous use of digital information between business and functional levels of an airport by developing a digital platform solution that will enable seamless flow of information across functions. Accordingly, this study targets to achieve three objectives: 1- To provide a scalable know-how of BIM-enabled digital transformation; 2- To guide airport owners and major stakeholders towards converging information siloes for airport life cycle data management by an Airport BIM Framework; 3- To develop a BIM-based digital platform architecture towards realization of an airport digital twin for airport infrastructure life cycle management. Airport infrastructures can be considered as a System of Systems (SoS). As such, Model Based Systems Engineering (MBSE) with Systems Modeling Language (SysML) is selected as the key methodology towards designing a digital ecosystem. Applying MBSE principles leads to forming an integrating framework for managing the digital ecosystem. Furthermore, this research adopts convergent parallel mixed methods to collect and analyze multiple forms of data. Data collection tools include extensive literature and industry review; an online questionnaire; semi-structured interviews with airport owner parties; focus group discussions; first-hand observations; and document reviews. Data analysis stage includes multiple explanatory case study analyses, thematic analysis, project mapping, percent coverage analysis for coded themes to achieve Objective 1; thematic analysis, cluster analysis, framework analysis, and non-parametric statistical analysis for Objective 2; and qualitative content analysis, non-parametric statistical analysis to accomplish Objective 3. This research presents a novel roadmap toward facilitation of smart airports with alignment and integration of disruptive technologies with business and operational aspects of airports. Multiple comprehensive case study analyses on international large-hub airports and triangulation of organization-level and project-level results systematically generate scalable technical and strategic guidelines for BIM implementation. The proposed platform architecture will incentivize major stakeholders for value-creation, data sharing, and control throughout a project life cycle. Introducing scalability and minimizing complexity for end-users through a digital platform approach will lead to a more connected environment. Consequently, a digital ecosystem enables sophisticated interaction between people, places, and assets. Model-driven approach provides an effective strategy for enhanced decision-making that helps optimization of project resources and allows fast adaptation to emerging business and operational demands. Accordingly, airport sustainability measures -economic vitality, operational efficiency, natural resources, and social responsibility- will improve due to higher levels of efficiency in CapEx and OpEx. Changes in business models for large capital investments and introducing sustainability to supply chains are among the anticipated broader impacts of this study

Challenges and Enablers in BIM-Enabled Digital Transformation in Mega Projects: The Istanbul New Airport Project Case Study

The Architecture Engineering and Construction (AEC) sector has been working on an increasing number of mega projects having large scale investments worldwide. The majority of these mega projects are infrastructure projects that are comparatively more difficult to manage in terms of yielding an expected return of investments while increasing quality and productivity. Today’s construction technology landscape offers a wide variety of innovative digital solutions for optimizing the project constraints of scope, time, cost, quality, and resources. Despite being one of the least digitized sectors, the AEC sector is currently ripe for adopting innovative digital solutions. It is observed that Building Information Modeling (BIM) has been rapidly adopted to tackle the ever-evolving challenges of mega infrastructure projects. This study investigates the challenges and enablers of utilizing an end-to-end BIM strategy for digital transformation of mega project delivery processes through a mega airport project case study, in order to contribute a solid strategic understanding in BIM implementation for mega infrastructure projects. The case study is followed with two-phased semi-structured interviews. Based on the findings, major challenges are sustaining continuous monitoring and controlling in the project execution, engineering complexity and aligning stakeholders’ BIM learning curves whereas strategic control mechanisms, incentivizing the virtual collaborative environment, and continuous digital delivery are major enablers

Treatment For The Large Aggressive Benign Lesions Of The Jaws.

Our aim was to evaluate the clinical outcome of the conservative management of the significantly large benign aggressive lesions of the jaws