Japan Architectural Review最新文献

In the 17th-century Louvre expansion project, many architects used free-standing columns, domes and large pediments for its east elevation. These elements helped give the elevation, over 150 m wide, the monumentality the court wanted, while also providing the appropriate articulation. Bernini was probably the only architect who did not use any of these elements. Instead, he relied heavily on engaged columns to articulate the elevation. However, his large order resulted in many unusual details: a broken entablature, a roughly twice as high plinth, a frieze not matching capitals, and strange molding under the architrave. Examinations of the documents and drawings show that these resulted from a conflict between “the columns that are enlarged while maintaining the same proportions” and “the functional dimensions and structural safety.” In other words, these were the drawbacks of combining monumentality and articulation in a palace of a size that the traditional Italian palace style would not have envisaged, while still adhering to the style. Bernini's Louvre did not receive the same criticism as the executed Colonnade, namely that it did not look like a residential building; however, we can see the limitations inherent in traditional Italian palace design there.

This paper aims to construct a Japanese localized Adaptive Model of thermal comfort and to examine the effect of humidity on the predicted comfort temperature. Also, the extent of adaptation, including the use of air conditioning, was investigated. Thermal comfort survey and measurements were conducted in a Japanese housing complex between 2020 and 2022, collecting 6607 responses. Window-opening behavior was investigated in 2018 and 2019 within the same housing complex to develop a probabilistic model of window opening. The slope of the derived adaptive model was steeper than in offices, indicating a greater extent of adaptation. Even when air conditioning is used, the range of adaptation was wider, with a slope of 0.26, whereas in offices, where more stringent climate control exists, the ASHRAE database suggests a slope of 0.13. The presented result showed the possibility of using a comfort model with the entire dataset, including when air conditioning is operated, provided that the way of adjusting the thermal environment in the room is mixed-mode. The model considering humidity showed that humidity affects it to a small extent, with a maximum effect of 0.13 K per 1 K outdoor temperature fluctuation, implying that a simple linear model is sufficient for comfort temperature prediction.

This study presents a practical framework for risk-informed seismic design that positions building functionality as a primary design objective and incorporates interdependencies among components into design decision-making. Existing approaches, such as FEMA P-58 and the REDi guidelines, acknowledge that functionality depends on multiple components and their interdependencies, but primarily address these relationships within evaluation models. In contrast, this paper elevates interdependencies to controllable design variables during the design phase, while maintaining consistency with Japanese design standards, thereby enabling designers to effectively improve building functionality. Furthermore, building upon the traditional concept of strength-based design, the proposed framework adopts vulnerability-based risk assessment by representing component design capacities as damage probabilities, advancing toward probabilistic performance evaluation. This approach links design choices to actual performance, allowing adjustments in redundancy and equipment layout. Functionality State (FS) curves are introduced to quantify the probability of achieving target functionality under seismic demands, supporting the setting and verification of design objectives. By directly integrating risk assessment into design decisions and embedding dependency structures within the design process, the framework enhances post-earthquake functionality and resilience, providing a transparent basis for decision-making and establishing a foundation for incorporating functionality into seismic design.

Curved steel members, widely utilized in modern architectural and structural applications, offer aesthetic, functional, and structural benefits. However, the plastic behavior of these members, particularly the yield, buckling, and ultimate strengths under various boundary conditions, remains insufficiently investigated. Unlike straight members, curved members lack well-established design equations and connection design guidelines, limiting their use for earthquake-resistant applications. This study investigated the plastic behavior of curved members through static analysis and extensive parametric studies, focusing on initial elastic stiffness, plastic strength, slenderness effects, and section compactness. Estimation equations for yield strength and buckling behavior with pinned- and fixed-boundary conditions were developed and validated using numerical simulations, demonstrating high accuracy. The findings further contributed to developing a connection design methodology that enhances material efficiency while preventing overly conservative designs. Moreover, a boundary constraint condition was identified to effectively control the yielding mechanism and achieve the desired plastic behavior. The proposed estimation equations and design recommendations provide a foundation for the practical implementation of curved members in seismic applications, improving structural efficiency, design flexibility, and functionality.

As the need to reduce use in the building sector increases, thermally activated building systems (TABS) have gained attention for providing both comfort and energy efficiency. Their large thermal mass enables peak load shifting, making them suitable for demand response (DR). Effective DR control requires methods that can flexibly handle dynamic building behavior, disturbances, and varying thermal characteristics. While model predictive control (MPC) is capable of predictive optimization, conventional MPC relies on fixed models and lacks adaptability to time-varying system conditions. This study introduces an adaptive MPC (AMPC) method, which incorporates online estimation and sequential model updating, to realize a DR-based control strategy for TABS. The method was evaluated through a co-simulation framework using Dymola and MATLAB/Simulink. Results show that AMPC can perform effective precooling and stably respond to DR requests. Through multiple case studies, the method was found to leverage the thermal storage capacity of TABS to flexibly shift cooling loads. Under the examined conditions, approximately 90%–100% of peak cooling energy was shifted to off-peak periods, while ceiling surface temperature errors were maintained within about 0.3°C. Furthermore, PMV remained within ±0.5 in all cases, demonstrating that thermal comfort can be preserved even under restricted cooling operation.

This study investigates the characteristics of courtyards as communal spaces within the courtyard-style settlements of Patan City, Nepal, through an examination of ownership and usage. A block with three interconnected Buddhist monastery courtyards—Ilānanī, Sasunanī, and Kwābahā—was selected. Fieldwork included legal document analysis, stakeholder interviews, and full-day observations to identify usage and governance patterns. Ilānanī and Sasunanī are public land owned by the government, while Kwābahā is privately owned by its Saṃgha organization. The courtyards function differently: Ilānanī supports residential life, religious activity, tourism, commerce, and transit; Sasunanī is mainly residential and communal; Kwābahā serves as a religious and touristic centre, houses the priest's family, and provides a public resting space. These findings highlight the evolution of courtyard spaces in historic Patan into multifunctional communal areas. Despite differences in ownership, all three continue to serve as shared environments, balancing traditional religious and residential roles with new socio-cultural functions shaped by urban transformation.

This study numerically investigates the removal of indoor particulate pollutants of various diameters by ventilation, a portable air cleaner, and gravitational settling using a drift-flux model within a computational fluid dynamics framework. The drift-flux model is first validated against a benchmark particle dispersion experiment, showing good agreement with measured velocity and concentration. Simulations are then conducted for an L-shaped room equipped with ceiling ventilation and a portable air cleaner placed at four locations. Particles ranging from 1 to 50 μm (particle density: 1.6 × 10³ kg/m³) are considered uniformly generated. The relative contributions of ventilation (air change rates (ACH) of 0.5 and 2), air cleaner intake (ACH of 3.15), and gravitational settling are quantified. Results show that the air cleaner dominates removal for particles smaller than 10 μm, whereas gravitational settling governs particles larger than 10 μm. Considering no surface deposition or resuspension, the cleaner placement minorly influences overall removal efficiency. A one-node model based on an equivalent ACH framework is proposed to compare its predictions with CFD results. Although the one-node model cannot represent spatial variations, it captured overall trends in particle removal. This study provides insights for evaluating particle removal strategies and optimizing air cleaner use in indoor environments.

This study aims to assess the applicability of multi-agent simulation for crowd control after large-scale events. It focuses on pedestrian pathways around a stadium in an urban area. By utilizing real-world pedestrian flow data, we investigated the parameters essential for simulation and analyzed crowd control. Consequently, we identified critical simulation parameters, such as speed–density relationships and personal distance, which produced highly accurate results across different days. In terms of congestion control, we established an acceptable congestion range based on data and illustrated that averaging peak bottleneck flows effectively alleviates congestion using the simulation.

Optimizing HVAC operation in buildings while maintaining thermal comfort and indoor air quality (IAQ) is a major challenge. This study presents a framework that combines Gaussian Process Regression (GPR) models with an exhaustive search method to improve HVAC operation. The models were trained on Building Energy Management System (BEMS) data, with key features selected using the RReliefF algorithm. The GPR models achieved high prediction accuracy, with an RMSE of 0.22°C and R² of 0.813 for indoor temperature, and an RMSE of 34.45 ppm and R² of 0.919 for CO₂ concentration. For operational improvement, the supply air volume of the Dedicated Outdoor Air Handling Unit (DAHU) was adjusted to maintain CO₂ concentration near 700 ppm, while the supply air temperature of the Air Conditioning Unit (ACU) was controlled to keep indoor temperature between 26°C–27°C. These adjustments reduced fluctuations and lowered mean values, confirming improvements in both thermal comfort and IAQ. The proposed method requires no additional sensors or complex physical models, and its low computational cost ensures feasibility on standard PC environments. Overall, the results demonstrate that combining GPR-based prediction with exhaustive search enables simultaneous enhancement of thermal comfort and IAQ, with practical applicability verified using real BEMS data.

Work engagement has gained attention as an indicator of an environment where employees are productive and can work in a lively and active manner. A questionnaire survey of employees at a company was conducted as a baseline in October 2016 and a follow-up in October 2017. We analyzed 1072 responses. Following stratification of the psychological stress status, logistic regression analysis was performed by adopting the environment of a personal workspace at baseline as an independent variable and work engagement in the follow-up as a dependent variable. In the low psychological stress group, the respondents who assessed their workspace to be enclosed demonstrated a work engagement level 2.07 (95% confidence interval [CI]: 1.24–3.48) times higher than those who assessed their workspace as open. In the high psychological stress group, the odds ratio for the participants who had frequent work-related conversations in a personal workspace was significantly higher at 3.92 (95% CI: 1.23–12.51) than for those who had a low frequency of conversation. Workplaces should achieve a balance between promoting both concentration and communication. Thus, the appropriate design of a personal workspace environment should be considered to enhance work engagement.