Schematic Design Phase Research Articles

Geometry optimization in the schematic design phase of low-energy buildings for all European climates through genetic algorithms

The ongoing transition towards resilient and energy-efficient cities highlights the design of new buildings as a critical concern. With the increasing urbanization in Europe and the concurrent need for energy reduction and decarbonization, it is crucial to address energy efficiency in the construction sector, as by the recently adopted European Energy Performance of Building Directive. In this context, the article focuses on the role of geometry optimization in the schematic design phase of low-energy buildings, by considering it among different European climates. Indeed, this study aims to propose a multi-objective optimization approach (using a genetic algorithm) to optimize the “genes” of the building, e.g., shape, proportions, orientation and window-to-wall ratio of residential buildings in the early design phase, to cut off a significant portion of energy consumptions. The objective is thus to minimize heating and cooling energy needs based on the best combination of the above-mentioned genes. The research investigates optimal solutions across various European climates based on the Köppen-Geiger classification, comparing the results for 19 European cities with varying climate. The findings confirm that the energy needs of buildings are strongly influenced by the climate conditions of their location. The study, which comprehends almost 250.00 different configurations, assesses, as expected, the strong effect of climate conditions on the energy needs and highlights the cross-shaped buildings as the best performing in 17 over 19 sites investigated. The optimal solution for each site leads to total energy needs that are comprised between 4.58 kWh m-2 y-1 in Porto and 19.84 kWh m-2 y-1 in Goteborg, with an average across all cities of 12.45 kWh m-2 y-1. The research provides valuable insights for professional in the construction sector, aiding them in making informed decisions during the schematic design phase to achieve low-energy buildings that are adapted to specific climates.

Effective schematic design phase in design process

Design thinking is a way to create solid designs that responds to design problems and solve it in a creative and suitable way. However, it is not widely recognized in architectural education pedagogy in Egypt for undergraduate. Despite being very efficient in several business avenues but not in architectural pedagogy. So, this paper aims to spot the light on design thinking and the possibility of its usage in design process to help students have a successful architectural project that solves the design problems and face the site challenges through the use of visualization design thinking tool. Where students face a challenge in translating the verbal language of their collected data in the research phase to the architectural language in the schematic phase. There is a recognized gap between the research students perform in the beginning of design project and the schematic designs that students deliver. The study proposes the possibility of using visualization as a tool for design thinking to have a sufficient and successful schematic design phase. The study will explain how students could apply design thinking in architectural design to benefit from their research phase in their schematic design. Moreover, come up with solutions and variable ideas using the tools of deign thinking as a way for helping in delivering design problem solution and have a more effective schematic design. At the end of the research paper the study concludes how the students can use visualization tool to translate the verbal language to architectural language and the possibility for using design thinking. That to help students realize the importance of analysis phase in synthesis. The research follows descriptive method and quantitative analysis where first the descriptive method is used in illustrating design process and design thinking. Then the quantitative analysis in the experiment is done followed by a survey to prove research problem and help in proposing the solution.

Optimal use of renewable energy technologies during building schematic design phase

An increasing number of federal and state regulations and financial incentive programs have been enacted in recent years to promote renewable energy systems integration in new buildings. This requires designers to analyze the initial and lifecycle costs of feasible renewable energy systems in order to optimize their integration in buildings during all design phases. The goal of this study is to support designers in generating optimal building schematic designs to maximize the integration and generation of onsite renewable energy. To accomplish this goal, this paper presents the development of a novel multi-objective optimization model that can be used during the schematic design phase to identify optimal building design decisions including dimensions, orientation, location on site, solid-to-void ratio, and the type and size of onsite renewable energy systems. The optimization objectives of the developed model focus on maximizing the generation of onsite renewable energy, maximizing savings-to-investment ratio of all integrated renewable energy, and minimizing both construction and renewable energy costs. An application example of optimizing the schematic design of a 6500 m2 building was analyzed to highlight the model original contributions and its novel capabilities. The results of this analysis highlight the original contributions of the developed model and its novel capabilities that can be used to maximize the generation of onsite renewable energy and its savings-to-investment ratio while minimizing building cost by optimizing building schematic design and renewable energy (RE) technology decisions.

Construction Cost Prediction Using Deep Learning with BIM Properties in the Schematic Design Phase

In the planning and design stage, it is difficult to accurately predict construction costs only by estimating approximate cost. It is also very difficult to predict the change in construction costs whenever the design changes. However, using the BIM model’s attribute information and machine learning techniques, accurate construction costs can be predicted faster than when using the existing approximate cost estimate. In this study, building information such as ‘total area’, ‘floor water’, ‘usage’, and BIM attribute information such as ‘wall area’, ‘wall water’, and ‘floor circumference’ were used together to predict construction costs in the schema design stage. As a result of applying the machine learning technique using both the building design information and the BIM model attribute information, it was found that the construction cost was improved compared to the result of individual predictions of the building information or BIM attribute information. While accurately predicting construction costs using BIM’s attribute information has its limits, it is expected to provide more accuracy compared to predicting costs solely based on construction cost influencing factors.

Integrating Urban Analytics into Postgraduate Urban Design Pedagogy: A Mixed-Methods Teaching Approach to Addressing Urban Liveability

As climate change, health, and social inequities call for more integrated planning approaches, data-driven urban analytics can support more socially sustainable urban design strategies. This article reports on an innovative pedagogical initiative, which introduced data-driven methods in academic teaching practices. Developed as a library of self-learning resources to complement existing study methods, the tools have been tested for their capacity to address social science issues, extracting insights from data on the underlying causes of urban problems. Our approach helped bridge the gap between research and schematic design phases and produced valuable learning outcomes related to liveability in disadvantaged urban neighborhoods.

Application and Design of Virtual Reality-Based Interactive Film System in Presentation of Architectural Design

Architects are unsatisfied with current ways of presenting their works in the schematic design phase to clients because the effects of the design presentation obtained nowadays are relatively weak and not self-explanatory. Based on this fact, we proposed a design solution using the concept of an innovative VR interactive film. This kind of VR film provides the clients with highly immersive and interactive VR experiences through virtual simulations in multiple human senses. In this essay, we explained the problem current architects encountered in the phase of architectural design presentation, evaluated the current state of VR in the field of film and architecture, and completed a system design designed with various technical details. Some of the technologies in this solution already exist, while others remain at the conceptual stage. It is possible to create an actual sample of such VR interactive films by prototyping all hardware.

Strategic schematic design process for realization of ultra-low-carbon buildings

The goal of the present research is to support decision-making in the schematic design phase for the realization of ultra-low-carbon buildings by improving the design procedures. Therefore, this research attempts to build an energy model that allows the designer to determine the equipment and specifications based on energy performance at the schematic design stage. Based on the schematic design outline, the present paper investigates whether the numerical targets that represent the energy performance of the building and the evaluation indexes that can be used at the schematic design stage are examined. In addition, recent system trends, decision specifications, and functions are investigated at the schematic design stage for each equipment item, thereby clarifying the decision level.

Knowledge-enhanced generative adversarial networks for schematic design of framed tube structures

In the schematic design phase of framed tube structures, component sizing is a vital task that requires expert experience and domain knowledge. Deep learning-based structural design methods enable machines to acquire expert experiences, but domain knowledge (e.g., empirical laws summarized by engineers from engineering practices) has not been embedded into such data-driven methods, resulting in common sense-conflicting designs. A knowledge-enhanced generative adversarial network is proposed by incorporating a novel differentiable evaluator for compliance checking of domain knowledge. A comparative study indicates that the proposed knowledge-enhanced method is 51% superior to the conventional data-driven method and 150 times faster than a competent engineer. The proposed method facilitates the schematic design of framed tube structures to be automatic and efficient, hence improving the productivity of structural engineers.

A study of optimal design process for complex-shaped skyscrapers’ structural systems in United Arab Emirates

Contemporary atypical skyscrapers in United Arab Emirates became the landmarks of the city and secured the urban competitiveness via innovative building design. These contemporary skyscrapers use non-linear geometry of structural frames, it is impossible to design these structures with conventional design methods. The objective of this paper is to examine the unit technologies for structural design of an atypical skyscraper and propose an optimal structural design process. As a methodology, the status of atypical skyscraper optimization technologies is analyzed, the status of data exchange among structural analysis programs, BIM software and FEM analysis programs are examined, and the case studies of some landmark buildings in United Arab Emirates designed by well known companies such as SOM, AECOM, and Salama Structural Engineers are explored. The result has shown that the unit technologies for optimizing atypical skyscrapers can follow four phases: Concept Design Phase, Schematic Design Phase, Design Development Phase and Construction Documentation Phase.

Integrated Schematic Design Method for Shear Wall Structures: A Practical Application of Generative Adversarial Networks

The intelligent design method based on generative adversarial networks (GANs) represents an emerging structural design paradigm where design rules are not artificially defined but are directly learned from existing design data. GAN-based methods have exhibited promising potential compared to conventional methods in the schematic design phase of reinforced concrete (RC) shear wall structures. However, for the following reasons, it is challenging to apply GAN-based approaches in the industry and to integrate them into the structural design process. (1) The data form of GAN-based methods is heterogeneous from that of the widely used computer-aided design (CAD) methods, and (2) GAN-based methods have high requirements on the hardware and software environment of the user’s computer. As a result, this study proposes an integrated schematic design method for RC shear wall structures, providing a workable GAN application strategy. Specifically, (1) a preprocessing method of architectural CAD drawings is proposed to connect the GAN with the upstream architectural design; (2) a user-friendly cloud design platform is built to reduce the requirements of the user’s local computer environment; and (3) a heterogeneous data transformation method and a parametric modeling procedure are proposed to automatically establish a structural analysis model based on GAN’s design, facilitating downstream detailed design tasks. The proposed method makes it possible for the entire schematic design phase of RC shear wall structures to be intelligent and automated. A case study reveals that the proposed method has a heterogeneous data transformation accuracy of 97.3% and is capable of generating shear wall layout designs similar to the designs of a competent engineer, with 225 times higher efficiency.

Improving Design Quality by Contractor Involvement: An Empirical Study on Effects

It is generally acknowledged that good-quality design is a prerequisite for good quality and productive construction work. One proposed measure to improve the quality of construction has been contractors’ involvement in the design phase, and this phenomenon has been studied by several researchers. However, such approaches have not adequately addressed how this involvement affects the quality of the design. In this study, the aim was to study the effects of the early involvement of contactors on design quality based on evaluating the design quality factors. A case study was used to collect data and content analysis to analyze structural drawings and design meeting minutes of a large-scale infrastructure project. Particularly, the focus was on gathering information on the quality of the design and how it was addressed in the design coordination. We combined this quantitative data with qualitative open-ended thematic interviews, including respondents who led and coordinated the design on both the client and contractor sides. Our findings suggest that despite the vast amount of design changes, contractors’ involvement and development work in the detailed design phase improved design quality and constructability. Our findings also suggest that the contractor’s involvement during the schematic design phase had a design-enhancing effect in the detailed design phase. This study contributes to our understanding of contractors’ valuable role in design quality.

무리지능 기반 파라메트릭 파사드 패턴 디자인 방법 및 그래스호퍼 알고리즘 개발

In a trend of urbanization, population lives in cities. These citizens want to live in a good urban life. For their good lives, urban environment as their living areas is filled with buildings. so facade pattern designs as one of visual elements of architectural facade have been considered and demanded in an artistic perspective of architecture. In designing architectural facade, designers and architects need to have an inspiration or its various and creative idea provided in a short time in their schematic design phase. Therefore, this research aims to develop design methods and their Grasshopper algorithms for parametric facade pattern design based on Swarm Intelligence, which is used in the field of Biomimicry, which is one of elements and attributes of Biophilic Design and a field of making it possible for efficient and artistic results to be produced by structural orders and principles from nature. The detailed objectives of this research are first, theoretical review for facade parametric pattern design, and Biomimicry and Swarm Intelligence, second, building a logical structure to produce data corresponding to each flocking behavior’s rule, and third, developing design methods and Grasshopper algorithms for Swarm Intelligence-based parametric facade patterns, representing parametric facade pattern designs, and comparing and analyzing with previous research’s algorithm. The study is focused on only introduction of Swarm Intelligence-based parametric facade pattern design’s methods and Grasshopper algorithms, display of pattern design examples, which are previous steps of applied to architectural facades. This research means to define a basic Grasshopper algorithm based on Swarm Intelligence in order to develop detailed design methods of parametric facade pattern designs and help designers and architects to get inspired from and various and creative idea in a short time in earlier design stage. The research is expected to be able to play an expanded system for developing parametric facade pattern design in the field of not only architectural facade but also interior space design.

Design of Navigation Satellite Systems in Effective Geomonitoring for Mining

Currently for a mining science it is actively developing branch of knowledge, called “satellite technology”, which has diverse practical applications for geodesy, mine surveying, control systems, mining logistic and transport complex, ensuring the safety and control of the risks there creation of tools and methods of the implementation of energy efficiency strategies. For specialists of mine surveying and geodesy introduction of practice, satellite-positioning methods has become almost revolutionary technological revolution that led to a radical revision of the structure of geodetic support of the country, fundamental changes in the methods field and laboratory work on the earth’s surface. There are examples of current uses of satellite technology over the last decade at the leading companies of the mining sector. The creation of new methods of technical and economic audit determines the need for generation and proof of the most common and objective criteria and evaluation indicators for the design phase and launch of the satellite equipment. To extend the lifetime of spacecraft is pro-posed in the schematic design phase to calculate the possible effects of electrostatic discharges and to give recommendations for reducing their negative influence. Developed a new method that allows for 2-3 orders of magnitude to reduce the complexity of calculation for the pattern of spreading of the currents on the surface of spacecraft from electrostatic discharge. The method is based by the idea of macromodeling. The accuracy of calculations is very high (the inaccuracy does not exceed 1%).

Sustainability evaluation for early design (SEED) framework for energy use, embodied carbon, cost, and daylighting assessment

ABSTRACT Given climate change and rapid global development, buildings must meet increasingly stringent environmental performance goals. Although numerous building simulation software assess energy performance, few inform the early stages of design when critical decisions impacting energy use and carbon footprint are made. Underrepresented early design simulation software could potentially significantly improve the environmental performance of buildings. This paper presents the SEED Framework for multi-objective early design decision-making that utilizes EnergyPlus-based building energy, structural finite element analysis, and Radiance-based daylighting simulations. When furnished with basic inputs, the SEED Framework generates numerous design options ranked by energy use, embodied carbon, construction cost, and daylighting metrics. A case study of a hypothetical mid-sized office building modelled in the Boston, Washington D.C., and Phoenix, USA climates demonstrates how the framework can guide decisions throughout pre- and schematic design phases. This framework aims to assist architects in designing high performance buildings within project and budgetary constraints.

Kinematic Chain Optimization Design Based on Deformation Sensitivity Analysis of a Five-Axis Machine Tool

This paper focuses on optimization of kinematic chain to reduce force-induced error in the scheme design phase of a five-axis machine tool. After conducting process planning on the machining target, local deformation of motion units in cutting positions is considered using a geometric way. A mathematical model is then established describing the influence of local deformation error on the general machining error through homogeneous transformation matrices. Conceptual model of the machine tool is constructed to obtain deformation distribution using static FEA. Error sensitivity coefficients are then calculated and compared among all alternative kinematic chains to select the optimized scheme. The proposed method is verified through a designing example of a five-axis vertical machining center. The optimized kinematic chain could lower the magnitude of deformation sensitivities by 9.69% and increase error equalization variance by 71.25% compared to the conventional method.

Fractal Patterns as Fitness Criteria in Genetic Algorithms Applied as a Design Tool in Architecture

This paper explores the generative use of a genetic algorithm incorporating a computer-based fractal dimension tool termed “DBVgen”. Fractals offer a quantitative and qualitative relation between nature, the built environment and computational mechanics and in this paper are explored as a bridge between these realms. The primary objective was to develop and employ a sophisticated analytic tool within a creative context using fractal dimension and the Vollendorf Method. This tool was then tested on a complex case study project and the results discussed. The design process developed for this research showed that the insertion of the DBVgen tool into a traditional schematic design phase was capable of creating unique and compelling compositions and aided in developing high level architectural solutions with respect to various parametric controls and designer feedback. A valuable aspect of this exploration was in positioning the DBVgen tool up front to aid in the creative process and better leverage downstream outcomes.

Designing for Patient Safety and Efficiency: Simulation-Based Hospital Design Testing.

In the schematic design phase of a new freestanding children's hospital, Simulation-based Hospital Design Testing (SbHDT) was used to evaluate the proposed design of 11 clinical areas. The purpose of this article is to describe the SbHDT process and how it can help identify and mitigate safety concerns during the facility design process. In the design of new healthcare facilities, the ability to mitigate risk in the preconstruction period is imperative. SbHDT in a full-scale cardboard mock-up can be used to proactively test the complex interface between people and the built environment. This study was a prospective investigation of SbHDT in the schematic design planning phase for a 400-bed freestanding children's hospital where frontline staff simulated episodes of care. Latent conditions related to design were identified through structured debriefing. Failure mode and effect analysis was used to categorize and prioritize simulation findings and was used by the architect team to inform design solutions. A second round of testing was conducted in order to validate design changes. A statistically significant reduction in criticality scores between Round 1 (n = 201, median = 16.14, SD = 5.8) and Round 2 (n = 201, median score of 7.68, SD = 5.26, p < .001) was identified. Bivariate analysis also demonstrated a statistically significant reduction in very high/high criticality scores between Round 1 and Round 2. SbHDT in the schematic phase of design planning was effective in mitigating risk related to design prototypes through effective identification of latent conditions and validation of design changes.

Advancing building engineering through structural and topology optimization

Traditional building design is often done in a (pseudo-) sequential manner: the architect defines the form, the structural engineer defines the material and member dimensions, and the mechanical engineer defines the openings, clearances, and additional spaces that ensure proper operation of the building. The design process should ideally be linear, where each discipline receives a complete design from the previous. In reality, however, upstream revisions are usually substantive: significant work in the schematic design and design development phases are due to resolving upstream issues. That said, within the conceptual design and initial phase, the process is mostly linear. This work presents a set of tools that move towards an integrated design optimization, where the building’s form and structure are optimized together and not as separate stages in the design. This approach often results in a higher impact/gain in efficiency, safety, cost-savings, and ultimately results in innovative designs. This industrial application manuscript provides specific details on the implementation and experience gained from the development of various topology optimization tools for use in building engineering. These are all accompanied by examples of their use in applied building projects or more general structural engineering problems. Part of the success of this effort is attributed to the environment in which these tools are implemented, which is friendly to architects. In contrast, commercial tools for this purpose tend to cater to engineers instead.

Economy-energy trade off automation – A decision support system for building design development

Building energy simulation is traditionally applied at late phases of the design, when most decisions on specifications of building systems are made. There has been a growing attempt in the literature to enable such simulations at earlier phases of design, when decisions’ impact on the lifecycle behavior is the strongest. While researchers have developed tools/models to support planning and conceptualization phases from this aspect; there have been not much developments for early design development stage (which is usually the scope of semi-detailed cost estimates). This paper introduces a software tool for generating multiple design scenarios and evaluating them, by combining energy simulation and economic analyses, at schematic design and early design development phases of building projects. In this regard, we used state-of-the art of open source technologies, as well as cloud computing, to integrate energy simulation into the alternative selection procedure. The developed system focuses on architectural parameters; lighting power density; and heating, ventilation and air conditioning (HVAC). Analysis of sensitivity of lifecycle energy to such parameters, in a group of representative real-world projects, helped us to limit variations of such parameters, and subsequently their combinations. Using OpenStudio measures and the computational power offered by the cloud, our system generates/simulates all possible design scenarios (combinations of alternative variations for design parameters); and compares them based on building economics performance measures. The workflow is showcased in a case study project, by automatically creating and evaluating 97 design scenarios, based on economic efficiency and liquidity.

Prediction of embodied carbon emissions from residential buildings with different structural forms

Quantifying and predicting embodied carbon emissions (ECEs) accurately in the scheme design phase is an effective way to reduce ECEs from the source. While previous studies focused on the assessment of carbon emissions (CEs) after construction, this research proposes quick prediction calculation models of ECEs based on CEs of main building materials during scheme design phase by conducting case studies on 129 residential buildings (RBs) of different structures in Jiangsu, China, the accuracy of which is verified by comparing the predicted results with CEs obtained by actual bill of quantities. It is proved that the proposed models simplify ECEs calculation, guide low-carbon building design and facilitate policy making on sustainable development of buildings and cities.