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Reducing energy consumption while providing a high-quality environment for building occupants has become an important target worthy of consideration in the pre-design stage. A reasonable design can achieve both better performance and energy conservation. Parametric design tools show potential to integrate performance simulation and control elements into the early design stage. The large number of design scheme iterations, however, increases the computational load and simulation time, hampering the search for optimized solutions. This paper proposes an integration of parametric design and optimization methods with performance simulation, machine learning, and algorithmic generation. Architectural schemes were modeled parametrically, and numerous iterations were generated systematically and imported into neural networks. Generative Adversarial Networks (GANs) were used to predict environmental performance based on the simulation results. Then, multi-object optimization can be achieved through the fast evolution of the genetic algorithm binding with the database. The test case used in this paper demonstrates that this approach can solve the optimization problem with less time and computational cost, and it provides architects with a fast and easily implemented tool to optimize design strategies based on specific environmental objectives.

The use of parametric and multi-objective optimization (MOO) as a new way of approaching architectural design has been growing in line with current breakthroughs in computational architecture. Wood, on the other hand, is a living and unique building material that provides durability, manufacturing flexibility, and local availability. One of the structure types that provides high structural stability is the hyperboloid. However, the exploration of hyperboloid structures in building design, together with the building daylight objective, is still limitedly reported. This paper presents the application of the parametric approach and multi-objective optimization in optimizing the structure and daylight objectives of a hyperboloid two-story wooden house in Japan, made of 105 mm × 105 mm × 4000 mm Japanese timber. The method involves iterating dynamic parameters such as radius bottom, offset distance, timber members, twisting level, building height, radius-top, and roof slope to optimize the structural objective of minimizing normal force average, displacement, and cost while simultaneously maximizing building volume. Regarding daylight objectives, unit movement and glazing ratio that control the glazing strategies were explored to optimize useful daylight illumination (UDI) in summer and winter. The optimization and exploration yielded 10,098 solutions in structural analysis and 406 solutions in daylight exploration. Based on the data analysis, the proposed methodology has successfully produced the best design solution, discovering the balance between the objective trade-offs. In addition, the most influential parameter that shapes the value of design objectives has been identified. The findings of this research were expected to contribute to and enhance the performance-based design optimization, and support design decision-making process in the early design stage of a wooden house with a hyperboloid structure.

With the emergence of novel targeted anticancer agents, drug combinations have been recognized as cutting edge development in oncology. However, limited attention has been paid to overdose control in the existing drug combination dose finding methods which simultaneously find a set of maximum tolerated dose (MTD) combinations. To enhance patient safety, we develop the multiple-agent non-parametric overdose control (MANOC) design for identifying the MTD combination in phase I drug combination trials. By minimizing an asymmetric loss function, we control the probability of overdosing in a local region of the current dose combination. We further extend the MANOC design to identify the MTD contour by conducting a sequence of single-agent subtrials with the dose level of one agent fixed. Simulation studies are conducted to investigate the performance of the designs proposed. Although the MANOC design can prevent patients from being allocated to overtoxic dose levels, its accuracy and efficiency in dose finding remain competitive with existing methods. As an illustration, the MANOC design is applied to a phase I clinical trial for identifying the MTD combinations of buparlisib and trametinib.

This research adopted literature analysis methods to explain the principles and types of line illusion and, secondly, using Grasshopper software generated some fashion design samples with visual illusion element application. Then semantic analysis was applied to investigate audiences’ cognition, with the aim to improve the design. Lastly, Grasshopper software was used to generate new design patterns by changing the set of generated points through algorithm operation and dotted line interference to change the presented linear illusion forms and patterns. The results of this research show that with the support of parametric technology, the opportunities and space for creating line elements in clothing will be further expanded, enabling that real-time pattern or apparel design changes, and adjustments can be realized by parameter variable controlling. The research comprised a new attempt at combining linear visual illusion, fashion design and parametric design, showing the content and design case studies for relevant research in this area.

Nowadays, digital technology has been applied in various fields. As far as the architectural design industry is concerned, computer-aided design and artificial intelligence simulation design have greatly improved the design technology of the architectural industry. This paper mainly elaborates the new possibilities brought by the parameterized software GC to the construction industry.

Purpose Life cycle assessment (LCA) has not been widely applied in the building design process because it is perceived to be complex and time-consuming. There is a high demand for simplified approaches that architects can use without detailed knowledge of LCA. This paper presents a parametric LCA approach, which allows architects to efficiently reduce the environmental impact of building designs. Methods First, the requirements for design-integrated LCA are analyzed. Then, assumptions to simplify the required data input are made and a parametric model is established. The model parametrizes all input, including building geometry, materials, and boundary conditions, and calculates the LCA in real time. The parametric approach possesses the advantage that input parameters can be adjusted easily and quickly. The architect has two options to improve the design: either through manually changing geometry, building materials, and building services, or through the use of an optimization solver. The parametric model was implemented in a parametric design software and applied using two cases: (a) the design of a new multi-residential building, and (b) retrofitting of a single-family house. Results and discussion We have successfully demonstrated the capability of the approach to find a solution with minimum environmental impact for both examples. In the first example, the parametric method is used to manually compare geometric design variants. The LCA is calculated based on assumptions for materials and building services. In the second example, evolutionary algorithms are employed to find the optimum combination of insulation material, heating system, and windows for retrofitting. We find that there is not one optimum insulation thickness, but many optima, depending on the individual boundary conditions and the chosen environmental indicator. Conclusions By incorporating a simplified LCA into the design process, the additional effort of performing LCA is minimized. The parametric approach allows the architect to focus on his main task of designing the building and finally makes LCA practically useful for design optimization. In the future, further performance analysis capabilities such as life cycle costing can also be integrated.

Parametric design of mechanical products should meet the requirements of standardization, generalization and serialization. For existing design examples, computer aided design and parametric design technology are used without destroying design principles and basic structural characteristics. Electronic device products have the characteristics of relatively simple structure and easy serialization. Under the condition of market economy, if the structural design of products can be quickly completed and serialized products can be derived quickly, enterprises will be in a more active position in the fierce market competition. Parametric design technology has a long theoretical precipitation period and application demonstration period. The blank in theory and instability in the application process of new ideas and methods can not be compared with parametric design technology. Aiming at the problems existing in the parametric design of electronic equipment, this paper explores the system opening strategy of parametric design of electronic equipment based on the design requirements of mechanical products and equipment.

Steel cladding profiles are widely used in modern construction, yet the combined effects of the cladding geometry, self-shading, and surface absorptivity remain underexplored, as most studies focus on coatings or thermal bridging of steel cladding. This study addresses that gap by using simulations calibrated to measured data from small-scale experiments to evaluate three steel cladding profiles across diverse climates and orientations: Standing Seam, Corrugated, and Interlocking. Results show that the profile geometry influences cavity and internal temperatures, with deeper protrusions or wider rib spacing reducing shading effectiveness. Self-shading improves comfort hours in hot, cooling-dominated climates (e.g., Singapore, Abu Dhabi, Brisbane) but offers limited benefit in cooler regions. Building-scale simulations predict reduced peak cooling loads (∼28%) and modest annual HVAC energy savings, highlighting the potential for smaller, more efficient systems. These findings indicate the significant role of cladding geometry, beyond coatings, in passive thermal regulation and climate-responsive façade design.

The traditional landscape garden planning and design mechanism has the defects of singularity of subject, unidirectionality of process, and contingency of method. Parametric landscape planning and design can quantitatively characterize the elements and optimize the design process. In this paper, we design a landscape garden routing design model based on ant colony Dijkstra’s combinatorial algorithm. Firstly, we analyze the role of parametric landscape planning and design mechanism, and carry out the specific application of parametric method in the whole process of landscape garden investigation and analysis, scheme conception, evaluation and construction management stage. Then the Dijkstra algorithm is optimized using the ant colony algorithm to realize the landscape environment road routing. The TSPLIB95 dataset is selected to carry out simulation experiments in Matlab2023 software environment and analyze the landscape quality of a mountain park. It is found that the shortest path planned by the algorithm in this paper is 304.78m, which is more than 200m less than the classical ant colony algorithm, and the fitness curve tends to be stabilized in only 69 iterations. Among the indicators in the factor layer of the mountain park, the highest score is C16 Scenic landscape accessibility, which is 8.65 points. The next highest scores were 8.65 for C16 Landscape Accessibility, followed by 8.35 and 8.34 for C8 Diversity of Ornamental Characteristics and C14 Enrichment and Harmonization of Landscape Elements, respectively. The final total score is 7.36 points, which is at a relatively satisfactory level.