Operation of environmentally responsive building components requires rapid prediction of the optimal adaptation of geometric shapes and positions, and such responsive configuration needs to be identified during the design process as early as possible. However, building simulation practices to characterize optimized shapes of various geometric design candidates are limited by complex simulation procedures, slow optimization, and lack of site information. This study suggests a practical approach to the design of responsive building façades by integrating on-site sensors, building performance simulation (BPS), machine-learning, and 3D geometry modeling on a unified design interface. To this end, a novel and efficient hybrid optimization algorithm, tabu-based adaptive pattern search simulated annealing (T-APSSA), was developed and integrated with wireless sensor data communication (using nRF24L01 and ESP8266 WiFi modules) on a parametric visual programming language (VPL) interface Rhino Grasshopper (0.9.0076, McNeel, Seattle, USA). The effectiveness of T-APSSA for early-stage BPS and optimal design is compared with other metaheuristic algorithms, and the proposed framework is validated by experimental optimal envelope (window shading) designs for single (daylight) and multiple (daylight and energy) objectives. Test results demonstrate the improved efficiency of T-APSSA in calculations (two to four times faster than other algorithms). This T-APSSA-integrated sensor-enabled design optimization practice supports rapid BPS and digital prototyping of responsive building façade design.

Human (occupant) behavior has been a topic of active research in the study of architecture and energy. To integrate the work of architectural design with techniques of building performance simulation in the presence of responsive human behavior, this study proposes a computational framework that can visualize and evaluate space occupancy, energy use, and generative envelope design given a space outline. A design simulation platform based on the visual programming language (VPL) of Rhino Grasshopper (GH) and Python is presented so that users (architects) can monitor real-time occupant response to space morphology, environmental building operation, and the formal optimization of three-dimensional (3D) building space. For dynamic co-simulation, the Building Controls Virtual Test Bed, Energy Plus, and Radiance were interfaced, and the agent-based model (ABM) approach and Gaussian process (GP) were applied to represent agents’ self-learning adaptation, feedback, and impact on room temperature and illuminance. Hypothetical behavior scenarios of virtual agents with experimental building geometry were produced to validate the framework and its effectiveness in supporting dynamic simulation. The study’s findings show that building energy and temperature largely depend on ABMs and geometry configuration, which demonstrates the importance of coupled simulation in design decision-making.

Respiratory aerosol particles carrying the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) are a primary cause of the long-distance infection, and insufficient ventilation systems make building occupants highly prone to the coronavirus disease-2019 (COVID-19). As a preventive measure of the aerosolized viable SARS-CoV-2 suspension in building space, we seek to propose an optimal design of the upper-room/drop-ceiling aeration grid system generating vertical laminar airflow (VLAF) as an aerosol barrier. On a test plan (6.1 × 4.7 m) representing the standard hospital patient room in South Korea (a 2.7 m-height room of 77.4 m³ in volume), we investigated the air-terminal size, spacing and air speed that shape uniform downflow of fresh air, minimizing horizontal spread. Our simulation results using the Taguchi method and computational fluid dynamics (CFD) in presence of indoor human expiration indicated that a steady vertical air supply of 0.3 m/s through 0.04m-diameter air diffusers deployed by 0.5 m spacing is the most effective to form VLAF. Physical particle detection tests at the height of 1.5 m in mockup setting of the optimal system design, revealed that expiratory aerosols produced by a single person were almost entirely removable in 20 s. Investigations also confirmed that the proposed design could minimize stagnant airflow regions and would potentially satisfy the indoor air-speed condition for occupant thermal comfort.

Purpose: This study aims to present an architectural application of 4D-printed climate-adaptive kinetic architecture and parametric façade design.Design/methodology/approach: This work investigates experimental prototyping of a reversibly self-shaping façade, by integrating the parametric design approach, smart material and 4D-printing techniques. Thermo-responsive building skin modules of two-way shape memory composite (TWSMC) was designed and fabricated, combining the shape memory alloy fibers (SMFs) and 3D-printed shape memory polymer matrices (SMPMs). For geometry design, deformation of the TWSMC was simulated with a dimension-reduced mathematical model, and an optimal arrangement of three different types of TWSMC modules were designed and fabricated into a physical scale model.Findings: Model-based experiments show robust workability and formal reversibility of the developed façade. Potential utility of this module for adaptive building design and construction is discussed based on the results. Findings help better understand the shape memory phenomena and presented design-inclusive technology will benefit architectural communities of smart climate-adaptive building.Originality/value: Two-way reversibility of 4D-printed composites is a topic of active research in material science but has not been clearly addressed in the practical context of architectural design, due to technical barriers. This research is the first architectural presentation of the whole design procedure, simulation and fabrication of the 4D-printed and parametrically movable façade.

Parametric complexity of the thermomechanical shape memory alloy (SMA) model is one of the major barriers to advanced application of the SMA actuation in adaptive architecture. This article seeks to provide architectural practitioners with decision-making information about SMA actuator design parameters. Simulation-based global sensitivity analysis of an SMA-bias spring actuation model reveals that the SMA spring index (a spring’s outer diameter divided by its wire diameter) and stiffness of the bias spring are significant factors in both displacement and force exertion. Among all parameters, maximum output stroke and force largely depend on the temperature range at which the SMA spring operates. These findings also indicate a trade-off between the spring diameter and wire thickness, demonstrating that the output stroke and force tend to counter one another. Appropriate preloading and choice of an optimal spring index should be considered for desirable SMA motion.

Microalgae-based photobioreactors (PBRs) have gained attention as a sustainable solution for indoor air quality (IAQ) control. This study investigates indoor CO₂ absorption performance of Spirulina maxima (S. maxima) in NaHCO₃-limited cultivation (standard: NaHCO₃-free medium = 1:1 v/v%) of a lab-scale PBR system. Cultivation performance of three medium amendments (standard, 50% NaHCO₃, and NaHCO₃-free) was compared by observing cell growth for 30 days in a controlled environment. Empirical examinations were conducted to evaluate the algal CO₂ uptake, and overall system performance in the culture volumes of 2, 4, and 7 L and natural indoor CO₂ concentration of ~1100 ppm. We found CO₂ was reduced by ~55%, in an air chamber of 0.064 m³, showing the greatest mitigation rate (~20%) on Day 4. Under a high concentration of CO₂ (10,000 ppm), the CO₂ levels were decreased up to ~90% before saturation. This research provides valuable insights into the development of S. maxima-activated IAQ control systems for airtight buildings.