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School of Architecture

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College of Design

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https://finding-aids.library.gatech.edu/agents/corporate_entities/1120

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Publication Search Results

Now showing 1 - 10 of 102

Structures and types of differentiated street grids: The generation, analysis, and sorting of universes of superblock designs

(Georgia Institute of Technology, 2019-05-22) Feng, Chen

The design of urban street networks is critical to how a city looks, feels, and functions. Moreover, the arrangement of streets inside the “superblocks”, which are the large urban areas divided up by the primary street network of the city, gives cities unique characters. This dissertation studies the street network designs at the scale of a square superblock that measures half a mile, or 800 m, on each side—a particularly common dimension for the spacing of arterial streets in the U.S., China, and many other countries. The contemporary urban landscape has been significantly shaped by two distinctive traditions for organizing streets at the scale of a superblock. At one extreme is the deployment of a uniform grid, differentiated only by street widths or intensity of development along the streets. At the other extreme is the “tree-like” pattern in which most separate branches or disjoined enclaves or loops are attached to the main streets, imposing a segregating hierarchy defined by mobility and access. This study explores street network designs that fall between these extremes; the designs in question can be described as differentiated grids. More specifically, we ask: (a) How to create differentiated grids by progressively deforming a square grid? (b) What different kinds of differentiated grids are there? (c) What is the relationship between the different rules that can be applied to creating differentiated grids and the emerging types of differentiation? To study those questions, eight different “syntactic operators” have been developed to progressively deform a street network. For each type of operation, a generative rule/algorithm was created to sequentially apply the operation on a uniform grid up to a specified number of times. An additional generative algorithm was also created to allow operations to be mixed in random sequences. Each generative algorithm was applied to generate a total of 600 differentiated street grids. This resulted in a “design universe” consisting of 5400 differentiated street grids that could be analyzed comparatively and queried for the presence of properties of interest. Such properties include graph connectivity, street density, block size and shape, intersection density, geometric regularity, directional reach, directional distance, and the diversity in syntactic conditions. In addition, the centrality structure of designs was studied. The aim was to formulate and test alternative definitions of “integration cores” and to develop relevant typologies. Consistent with space syntax literature, an integration core is defined as comprising the streets that are closer to all parts of the street network in terms of directional distance. Query algorithms were developed to select designs based on the definitions of alternative types of integration cores. Four main conclusions were reached. First, different types of operations have different capacities to influence the properties of a street network. Second, there are multiple dimensions of differentiation (e.g., differentiation in geometric alignment of streets, differentiation in configurational properties such as DDL, differentiation in block shapes, etc.). In many cases, measures along the different dimensions of differentiation are related. Their predictable relationship can be quantified. Third, while the relationship between different dimensions of differentiation usually has a consistent direction, its slope can vary, depending on the type of operation used to create the differentiation. The variation in slope suggests that properties that may be desirable (for example the creation of a diversified street grid) can be achieved with varying costs regarding properties that may be undesirable (for example the creation of less accessible streets). Fourth, the (local) generative rules used to generate designs do not necessarily lead to specific emergent global properties of the street network of the superblock. Although we cannot predict the specific syntactic type we get by applying a specific generative rule, we know that by applying certain generative rules, we are more likely to generate designs of a specific syntactic type. Thus, the thesis makes two significant contributions to the field of space syntax studies. First, it demonstrates how the systematic generation and querying of universes of designs can be used to rigorously define and enrich key syntactic ideas that have hitherto remained intuitive, such as the ideas of “deformed grid” and the “shape of the integration core”. Second, it demonstrates that in principle, the design of street networks at superblock scale can be studied according to the typologies of interface between local and global integration and according to the typologies of differentiation of the street grid.
A framework for coordinated models of architectural precast concrete facades

(Georgia Institute of Technology, 2019-02-28) Collins, Jeffrey

Architects are often unaware of details, constraints, and variables that define and deliver architectural components. Many factors such as constructability, budget, or scheduling commitments, force changes to design concepts – potentially resulting in time-consuming redesign or loss of design aspirations – because incorporation of fabrication and expert knowledge occurs too late in the process. At the same time, fabricators, obligated to re-model these components – typically via error-prone manual translation – may be unaware of critical architectural properties envisioned but difficult to represent in design intent documents. The focus of this dissertation is to establish a new framework for coordination among project actors, linking currently disparate global and local descriptions of architectural intent and corresponding components via parametric digital models, with the aim of improving representations, enabling more informed conversations, and streamlining exchanges during early stages of design. In order to show the potential of this framework, research is focused on architectural precast concrete façades. Building façades are especially relevant to both architectural theory and practice as they are critical to a buildings’ character but remarkably complex in assembly. The architectural precast façade offers, in particular, a system whose parts are discreet through surface panelization, customizable via extensive features, and fundamental to the overall buildings’ aesthetic. Protocols and techniques for generating and linking customizable digital models for coordination are documented for a variety of surface patterns and panel feature types found in precedent buildings with architectural precast concrete façades. These models are used to demonstrate the process of developing parametric maps, both as a means of engaging issues of fabrication in early stages of design as well as to demonstrate benefits of incorporating such maps in future state workflows. Knowledge gained from recording various processes undertaken, conversations held, and documents produced by precast fabricators during the shop drawing phase of their work informs the parametric maps from both global and local perspectives. The strategies from the precedent analysis are then implemented through the exploration of design and fabrication issues raised by novel student proposals. The research suggests that the current disconnect between architectural intent and fabrication knowledge contributes to limited design exploration, and ultimately, reduces use of architectural precast concrete façades and furthermore, that linked digital models can stimulate interaction between designers and fabricators – bridging currently disparate workflows and value systems – while simultaneously enabling design exploration, incorporating fabrication details, and allowing new opportunities for precast buildings to emerge.
A functional modeling framework for interdisciplinary building design

(Georgia Institute of Technology, 2018-08-01) Cavieres, Andres

The process of Building Design, as in many other forms of design, requires the effective integration of different types of knowledge. However, and in the specific context of Building Information Modeling, only structural knowledge is formally represented. Other types of necessary knowledge, such as those related to the functionality of design, and the set of causal behaviors from which such functionality is delivered, remain tacit or indirectly referenced by using structural properties as proxy representations (e.g. geometry). The lack of a more comprehensive and rigorous representational framework to formally describe various behavioral and functional aspects of buildings limits the scope of semantics required to support more effective interdisciplinary collaboration and design integration. In particular, there is a lack of computational support to describe cross-cutting behavioral interactions and side-effects that occur among different building sub-systems, which often play a role in the satisfaction of functional goals. To address this problem, the research proposes the development of a representational framework for the functional and behavioral characterization of building systems and components based on the Functional Representation (FR) schema developed by Chandrasekaran and Josephson (2000), and its recent formalization following the DOLCE foundation ontology, by Borgo et al. (2009). A subset of FR axioms has been translated into Description Logic using the Web Ontology Language (OWL-DL) to explore query capabilities of the proposed framework to support identification of behavioral interactions based on inference capabilities of available OWL-DL reasoners. The dissertation provides a theoretical basis for the formulation of functional modeling capabilities currently not available in Building Design. In particular, these capabilities are intended to support the incremental elucidation of behavioral interactions that emerge across different building sub-systems, based on the principle of co-participation of structural entities in a same behavioral phenomena (category of perdurants). The elucidation is expected to be supported by computational inference from structural relations asserted in BIM models by various stakeholders, and at different stages of the design process.
From physical layout to spatial experience: Understanding the impact of visual interfaces on teamwork in primary care clinics

(Georgia Institute of Technology, 2018-07-31) Lim, Lisa

Teamwork among healthcare providers is critical for the safety and quality of patient care. Multiple national strategies and programs have been developed and recommended for implementation of a team-based approach to primary care, and many healthcare organizations are adopting team-based primary care clinics. However, little is known about how clinic layouts can support the teamwork of staff members in team-based primary clinics. To date, there has been little agreement on how clinic layouts should be designed to support the teamwork experiences of staff members and patients. Thus, different healthcare organizations advocate for unique and significantly different types of team-based clinic layouts. This study looked at four team-based primary care clinics to empirically investigate the relationships between visibility metrics and both patients’ and staff members’ teamwork experience. The results of the study showed that the visual interfaces between staff members and patients, as well as between different groups of staff members, were found to have significant associations with awareness, communication, backstage communication, and overall perception of teamwork. While no specific differences in awareness perceptions were reported between clinics, some negative consequences resulting from the lack of staff’s ability to see the clinic area and other staff members were observed. Staff members had to spend additional time searching for each other and had their patient care process obstructed when they could not see the clinic area or other staff workstations. The visual interface between staff workstations also significantly predicted staff communication patterns. Clinics providing more visual connections between staff workstations reported stronger perceptions of timely and frequent communication, and staff members talked frequently to other staff members whose workstations were visually and physically connected with their own workstations. Furthermore, clinics providing more visual connections between staff workstations reported higher teamwork perception. Surprisingly, more visual connections between patients and staff workstations were associated with lower teamwork perceptions from the patients’ perspective. The visual connections between patients and staff workstations (visual exposure to patients) also negatively affected staff backstage communication patterns. Clinics with higher visual exposure levels reported higher levels of concern for privacy while communicating patient information, and the staff members across all four clinics preferred not to talk about patients at visually exposed areas, even if the locations were inside team areas. The findings of the study support designing team-based primary care clinics to enhance the teamwork experience of both staff members and patients. It is worth noting that this study investigates the teamwork experience of not only staff members but also patients, who are critical entities of teamwork for patient-centered care in primary care clinics. The design implications are expected to be applicable for the teamwork of other settings, especially for strong programs where both inhabitants and visitors exist as main user groups of the spaces.
On the role that specific domain knowledge and procedural strategies play in defining the episodic nature of architectural design formulation

(Georgia Institute of Technology, 2018-07-24) Soza Ruiz, Pedro Alejandro

This dissertation presents a study of design activity based on the analyses of fifty-six design processes taken from fourteen designers which were give four related architectural problems. The motivating interest was to investigate what is specifically distinctive about the architectural design process, with a focus on how the activity is organized or planned, and on how knowledge of different kind and external visual representations—sketches—are brought into play. These considerations and interests are derived from the assumption that the cognitive processes underlying the design activity are embodied and distributed throughout the materials and techniques used for the purpose. Findings reveal that the design activity is structured episodically, a feature that is not yet discussed adequately within extant literature on the topic. Episodes are described as forms of continuous activity grounded in specific forms of external representations and addressing a cluster of related sub-problems. Results also showed that unfamiliar tasks and settings generated larger number of episodes, which is conformity with the thesis that architects address novel design challenges by breaking up the overall design task into a number of smaller and more familiar sub-tasks, but that this restructuring emerges during the context of the design. Further findings concern the nature of these episodes. Episodes were found to fall into three main types, those concerned with issues of program and spatial organization, those concerned with site and physical context, and those with formulating broad goals. The quality of the designs depended not so much on the number of such episodes, or their order, but on their richness measured in terms of the number of design issues addressed within them and their variety.
Integrated assessment of buildings and distributed energy resources (DER) at the neighborhood scale

(Georgia Institute of Technology, 2017-11-13) Carneiro, Gustavo Antonio

In urban regions, traditionally a main electric grid fed by centralized power plants serves the growing energy demand of residential and commercial buildings. However, the advent of new technologies, such as distributed renewable energy generation, local energy storage, and smart controls, is transforming the way buildings interact and transact with the electric grid. When operating in coordination, several buildings or households can leverage their aggregate potential and use their energy flexibility and distributed resources to improve the operation of both the main grid and the pool of integrated and intelligent buildings. Much attention has been drawn to the potential benefits of these types of integration, especially the capabilities they can provide in terms of aggregate demand management and local power resilience. Nevertheless, building energy modeling at the urban level has not yet reached the necessary computational manageability and simulation robustness to assess these novel scenarios. To address this hiatus, the current thesis presents a computer-aided energy simulation method to model the integration of multiple buildings and distributed energy resources (DER) at the neighborhood scale. The proposed methodology uses a reduced order simulation approach to achieve a reliable and tractable dynamic modeling framework that can manage multiple transacting building energy models and DER models in a single platform. To test the modeling approach, this study first carries out a virtual experiment of a small community in Miami, FL, where it is possible to compare the outcomes of community energy consumption from our reduced order model to the outcomes from a higher order simulation approach. When using the community energy model to evaluate the performance of different DER options for community peak load shaving, we can observe that the influence of the model order reduction reveals to be very minor when compared to other uncertainties related to scenario variability and, especially, systems’ efficiencies. Secondly, we apply the reduced order modeling approach to an existing residential community in Rancho Cordova (Sacramento County), CA, with solar energy generation and battery energy storage. With this case study, we demonstrate the viability of our approach to construct and calibrate a reduced order model of fifteen households based only on limited and general data related to energy performance of the entire neighborhood. The developed reduced order model is used to evaluate the performance of different energy storage arrangements for reducing the occurrence of community super peak loads. In this virtual experiment, we can demonstrate how the model allows for uncertainty analyses over the influence of input parameters, as well as for more sophisticated optimization studies, including stochastic optimization, in a timely and transparent fashion. Finally, the proposed reduced order simulation approach is used to construct and test relevant energy performance measures at the neighborhood scale. Using the model unique features of manageability, reliability and flexibility, we propose the foundations for quantifying and measuring “community energy resilience” for outage situations, based on concepts of number of sustained hours and respective energy end-use convenience levels. We also measure and monetize DER options for providing “community energy flexibility”, aimed at shaping the load profile of a residential community to match the electric grid needs.
Addressing data informativeness in risk-conscious building performance simulation applications

(Georgia Institute of Technology, 2017-08-02) Li, Qi

Building performance management remains an important aspect in reducing building energy consumption and enhancing occupants’ thermal comfort and work productivity. Recent decades witnessed the maturity and proliferation of numerous methods, software and tools that span the whole spectrum of common building performance management practice. Among those related research and applications, the use of information and data in calibration and validation of building performance simulation (BPS) models constitutes an important subject of study especially in fault detection, operations management, and retrofit analysis. An extensive review of BPS model calibration and validation studies reveals two major research gaps. First, contemporary model calibration practice calls for an effective and robust method that can systematically incorporate a variety of information and data, handle modelling and prediction uncertainties, and maintain consistent model performance. Second, current approaches to collecting information and data in real practice largely depend on individual experience or common practice; further study is needed to understand the value of information and data, i.e. assess data informativeness, such as to support specific decision-making processes in choosing data monitoring strategies and to avoid missed opportunities or wasted resources. To this end, this dissertation develops a new framework to address data informativeness in model calibration and validation to answer two major research questions: 1) how to make optimal use of available information and data to calibrate a building simulation model under uncertainty, and 2) how to quantify the informativeness of information and data for risk-conscious building performance simulation applications. This framework builds upon uncertainty propagation using detailed measurements, and inverse modelling using Bayesian inference. It introduces probabilistic performance metrics to assess model prediction consistency and quantify data informativeness. Following an explanation of the framework’s theoretical soundness, this dissertation provides two case studies to demonstrate its practical effectiveness. The first is a controlled experiment in the Flexlab test facility at Lawrence Berkeley lab. A new validation methodology is proposed to validate a simulation model under uncertainty, in which the validation criteria build upon the introduced probabilistic performance metrics. Given the experiment setup, uncertainty propagation based on synthetic measurements is applied, which effectively improves prediction agreement and reduces the risk of accepting invalid simulation outcomes. The second is to determine the appropriate model form and metering data for a hypothetical intervention analysis of an existing building with hydronic heating on the Cambridge, UK campus. A three-level modelling method is proposed to enable modelling all thermal processes occurring in individual rooms while efficiently modelling the whole building to estimate heating system performance. Different sets of metering data are then used to calibrate the physical model, and the result indicates the superiority of Bayesian inference in exploiting the value of data, the necessity of room temperature and electricity monitoring under uncontrolled conditions, and the potential of daily metering data for calibration in real building performance management practice.
BIM synapse: A framework for BIM interoperability in the cloud

(Georgia Institute of Technology, 2017-07-11) Afsari, Kereshmeh

In the Architecture, Engineering, and Construction (AEC) industry, collaboration within Building Information Modeling (BIM) process is mainly based on transferring files. BIM data is being exchanged in either vendor specific file formats or neutral format using Industry Foundation Classes (IFC) as open BIM standard. However, since the web enables cloud-based BIM services, it provides an opportunity to exchange non-file based data via the web and over the networks. Alternative BIM data sharing solutions have been developed based on the federation of BIM models with BIM server technologies or using an interchange hub for data exchange in real-time. These solutions face several challenges, are vendor locked, and integrate two or multiple applications to a third new system which is tightly coupled. In addition to scalability issues, these data sharing technologies make the collaborating applications dependent upon each other which end up with high complexity. In fact, current cloud-based interoperability solutions do not provide a loosely coupled system with the flexibility to reduce dependencies among collaborating applications. Therefore, the main objective of this research is to propose an interoperability framework that supports a network-based BIM data exchange for loosely coupled collaboration in the cloud. This research emphasizes that there is a need to reshape BIM collaboration in the cloud by using web technologies. This study indicates that Cloud-based Building Information Modeling needs to deploy major components of the cloud interoperability including the APIs, data transfer protocols, data formats, and standardization to redefine BIM dataflow in Cloud-BIM applications. BIM Synapse framework proposed in this research utilizes web technologies- as the enabler for a cloud-based collaborative process- to restructure current BIM dataflow. BIM Synapse deploys cloud interoperability features and IFC data model to address current challenges of BIM data exchange in the cloud and provides a loosely-coupled network-based data interoperability solution for Cloud-BIM. The study also applies the proposed framework on BIM collaboration in the conceptual design process of precast concrete buildings and evaluates the correctness, accuracy, completeness, and consistency of the BIM Synapse framework. BIM Synapse framework has a major contribution to standardization of Cloud-based BIM data exchange and can enable the integration of the Internet of Things (IoT) - that requires network connectivity and provision of resources through the Web of Things (WoT)- with the BIM process. The study also recommends required revisions to the IFC specification so that the IFC schema can perform as the basis for Cloud-BIM interoperability.
Spatiotemporal occupancy in building settings

(Georgia Institute of Technology, 2017-05-30) Gomez Zamora, Paula Andrea

This thesis presents an investigation of methods to capture and analyze spatiotemporal occupancy patterns of high resolution, demonstrating their value by measuring behavioral outcomes over time. Obtaining fine-grain occupancy patterns is particularly useful since it gives researchers an ability to study such patterns not just with respect to the geometry of the space in which they occur, but also to study how they change dynamically in time, in response to the behavior itself. This research has three parts: The first is a review of the traditional methods of behavioral mapping utilized in architecture research, as well as the existing indoor positioning systems, offering an assessment of their comparative potential, and a selection for the current scenario. The second is an implementation of scene analysis analyses using computer vision to capture occupancy patterns on one week of surveillance videos over twelve corridors in a hospital in Chile. The data outcome is occupancy in a set of hospital corridors at a resolution of one square foot per second. Due to the practical detection errors, a two-part statistical model was developed to compute the accuracy on recognition and precision of location, given certain scenario conditions. These error rates models can be then used to predict estimates of patterns of occupancy in an actual scenario. The third is a proof-of-concept study of the usefulness of a new spatiotemporal metric called the Isovist-minute, which describes the actual occupancy of an Isovist, over a specified period of time. Occupancy data obtained using scene-analyses, updated with error-rate models of the previous study, are used to compute Isovist-minute values per square feet. The Isovist-minute is shown to capture significant differences in the patient surveillance outcome in the same spatial layout, but different organizational schedule and program.
Optimal strategies for demand charge reduction by commercial building owners

(Georgia Institute of Technology, 2017-05-23) Zhang, Yuna

A substantial part of electricity bills in various types of commercial buildings, such as office buildings, hospitals and retails can consist of demand charges. Demand charges represent the penalty for an electricity consumer levied by the utility provider. They are typically a direct result of the shape of the power duration curve, in particular, the hours that a certain power level is exceeded in a given billing period (normally a month). Lowering the peak and/or reducing the hours that a power threshold is exceeded can drastically reduce demand charges. The ability to do so by dynamic, operational adjustments reflects the “energy flexibility” of the building. This term is now widely used in Europe and is the subject of a new international effort (IEA Annex 67) in this area. This thesis targets the optimal choice among design and operational measures in a retrofit or new design project that delivers the most effective way of reducing demand charges and increasing energy flexibility of commercial buildings. This goal will be achieved through an analysis of all feasible energy and peak reduction measures in different building types and in different use contexts. A search algorithm that compares all possible interventions will deliver the optimum, first with a deterministic analysis then with the recognition of the effects of all possible sources of uncertainty. This thesis evaluates the measures that are commonly adopted to decrease energy consumption and increase energy flexibility and thus reduce demand charges, including (1) upgrading building components and installing energy efficient equipment; (2) applying dynamic building load control strategies such as demand-side management; (3) installing a rooftop photovoltaic (PV) panel array. Operational interventions include the manipulation of thermostat settings and possibly the voltage reduction of lighting and appliances (in some cases including HVAC components) in the building, which may reduce thermal and visual comfort for certain periods. In order to support retrofit and design improvement decisions, an approach is developed that finds the optimal mix of measures that maximize the net present value of the investment in energy flexibility measures over twenty years for the owner. This study will analyze optimal solutions for three commercial building types. Differences between them in terms of energy use and peak demand will be investigated and a generically applicable measure of energy flexibility will be developed. These three buildings are chosen (by scaling their total floor area) such that their demand charges are in the same range. The monetary benefit of energy flexibility will be studied under different demand charge rate structures and under variable building consumption scenarios. This research will result in a new optimization framework for choosing the optimum among multiple options. Based on the proposed framework, this research will determine optimal ways to increase energy flexibility, leading to the best investment decisions for different commercial building types in different locations and under different rate structures.