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This article presents a case study on the Heritage Building Information Modeling (H-BIM) application in a historic village in Bursa, Turkey. The study addresses how tailor-made and highly structured H-BIM approaches can effectively be implemented in preservation applications for historic vernacular buildings in the rural architecture context.

Using inexpensive digital photogrammetry techniques tightly combined with an object-oriented BIM ontology, parametric meta-modeling and object/system propagation methods, the study employed a holistic H-BIM approach for capturing the materiality, building object behaviors and indigenous construction principles of a characteristic vernacular house that were synthesized in a parametric H-BIM model. The followed stages, steps and connected methods were systematized and articulated in a prototypical H-BIM implementation framework.

The study findings suggested that the developed parametric H-BIM approach can return effective results with the combined use of low-cost and practical digital photogrammetry with BIM methods. The flexibility and adaptability of the parametric H-BIM implementation framework facilitated the synthesis of a comprehensive H-BIM model and allowed an in-depth evaluation of local architectural heritage with its physical, spatial and environmental characteristics. The proposed H-BIM approach also provided significant documentation and system-specific assessment benefits for preserving the vernacular examples which are prone to extinction especially due to structural and systemic deterioration.

The study proposes a feasible, practical and replicable H-BIM implementation methodology for vernacular preservation applications. The knowledge-embedded H-BIM approach, flows and techniques presented in this study provide a holistic and systematic H-BIM framework – with the integrated use of digital photogrammetry and parametric meta-modeling methods – that has the potential for the democratization of H-BIM applications in education and practice.

This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for virtual fitting.

In this study, we briefly analyze the mainstream datasets of models of the human body used in the area to provide a foundation for parametric methods of such reconstruction. We then analyze and compare parametric methods of reconstruction based on their use of the following forms of input data: point cloud data, image contours, sizes of features and points representing the joints. Finally, we summarize the advantages and problems of each method as well as the current challenges to the use of parametric modeling in virtual fitting and the opportunities provided by it.

Considering the aspects of integrity and accurate of representations of the shape and posture of the body, and the efficiency of the calculation of the requisite parameters, the reconstruction method of human body by integrating orthogonal image contour morphological features, multifeature size constraints and joint point positioning can better represent human body shape, posture and personalized feature size and has higher research value.

This article obtains a research thinking for reconstructing a 3D model for virtual fitting that is based on three kinds of data, which is helpful for establishing personalized and high-precision human body models.

Algorithmic and computational thinking are necessary skills for designers in an increasingly digital world. Parametric design, a method to construct designs based on algorithmic logic and rules, has become widely used in architecture practice and incorporated in the curricula of architecture schools. However, there are few studies proposing strategies for teaching parametric design into architecture students, tackling software literacy while promoting the development of algorithmic thinking.

A descriptive study and a prescriptive study are conducted. The descriptive study reviews the literature on parametric design education. The prescriptive study is centered on proposing the incomplete recipe as instructional material and a new approach to teaching parametric design.

The literature on parametric design education has mostly focused on curricular discussions, descriptions of case studies or studio-long approaches; day-to-day instructional methods, however, are rarely discussed. A pedagogical strategy to teach parametric design is introduced: the incomplete recipe. The instructional method proposed provides students with incomplete recipes for parametric scripts that are increasingly pared down as the students become expert users.

The article contributes to the existing literature by proposing the incomplete recipe as a strategy for teaching parametric design. The recipe as a pedagogical tool provides a means for both software skill acquisition and the development of algorithmic thinking.

Public management researchers commonly model dichotomous dependent variables with parametric methods despite their relatively strong assumptions about the data generating process. Without testing for those assumptions and consideration of semiparametric alternatives, such as maximum score, estimates might be biased, or predictions might not be as accurate as possible.

To guide researchers, this paper provides an evaluative framework for comparing parametric estimators with semiparametric and nonparametric estimators for dichotomous dependent variables. To illustrate the framework, the article estimates the factors associated with the passage of school district bond referenda in all Texas school districts from 1998 to 2015.

Estimates show that the correct prediction of a bond passing increases from 77.2 to 78%, with maximum score estimation relative to a commonly used parametric alternative. While this is a small increase, it is meaningful in comparison to the random prediction base model.

Future research modeling any dichotomous dependent variable can use the framework to identify the most appropriate estimator and relevant statistical programs.

In this paper we develop a new semi-parametric model for conditional correlations, which combines parametric univariate Generalized Auto Regressive Conditional Heteroskedasticity specifications for the individual conditional volatilities with nonparametric kernel regression for the conditional correlations. This approach not only avoids the proliferation of parameters as the number of assets becomes large, which typically happens in conventional multivariate conditional volatility models, but also the rigid structure imposed by more parsimonious models, such as the dynamic conditional correlation model. An empirical application to the 30 Dow Jones stocks demonstrates that the model is able to capture interesting asymmetries in correlations and that it is competitive with standard parametric models in terms of constructing minimum variance portfolios and minimum tracking error portfolios.

Advances in digital design tools enable exploration and generation of dynamic building facades. However, some processes are formally prescribed and manually driven to only visualize the design concepts. The purpose of this paper is to present a proactive framework for integrating parametric design thinking, paying particular attention to building facade patterning.

This work developed the PatternGen^© add-on in Autodesk® Revit which utilizes an analytical image data (AID) overlay approach as a data source to dynamically pattern the building facade. The add-on was used to manipulate the placement rules of curtain panels on facade surface geometry. As means of validating this research model, a real-life design project has been chosen to illustrate the practical application of this approach. Feedback and observations from a short end-user questionnaire assessed qualitatively the facade patterning and panelization approach.

The proposed merge (or overlay) of AID images can be used as a parametric thinking method rather than just theory to generate and articulate dynamic facade design. The facade panelization responds to an AID that resembles design-performance data (e.g. solar exposure, interior privacy importance and aesthetics).

This work identifies a form of parametric thinking defined as the expression of geometrical relationships and its configuration dependent on the AID pixel Red Green Blue color source values. In this type of thinking, it explores the impact of the digital process and parametric thinking utility when driven by an AID overlay. The framework highlighted the practical application of AID pixel approach within a digital process to benefit both designers and computational tools developer on emerging design innovations.

The purpose of this paper is to describe a novel design method to construct lattice structure computational models composed of a set of unit cells including simple cubic, body-centered cubic, face-centered cubic, diamond cubic and octet cubic unit cell.

In this paper, the authors introduce a new implicit design algorithm based on the computation of volumetric distance field (VDF). All the geometric components including lattice core structure and outer skin are represented with VDFs in a given design domain. This enables computationally efficient design of a computational model for an arbitrarily complex lattice structure. In addition, the authors propose a hybrid method based on the VDF and parametric solid models to construct a conformal lattice structure, which is oriented in accordance with the geometric form of the exterior surface. This method enables the authors to design highly complex lattice structure, computational models, in a consistent design framework irrespective of the complexity in geometric representations without sacrificing accuracy and efficiency.

Experimental results are shown for a variety of geometries to validate the proposed design method along with illustrative several lattice structure prototypes built by additive manufacturing techniques.

This method enables the authors to design highly complex lattice structure, computational models, in a consistent design framework irrespective of the complexity in geometric representations without sacrificing accuracy and efficiency.

The purpose of this paper is to focus on the advanced solution of the parametric non-linear model related to the Rayleigh-Benard laminar flow involved in the modeling of natural thermal convection. This flow is fully determined by the dimensionless Prandtl and Rayleigh numbers. Thus, if one could precompute (off-line) the model solution for any possible choice of these two parameters the analysis of many possible scenarios could be performed on-line and in real time.

In this paper both parameters are introduced as model extra-coordinates, and then the resulting multidimensional problem solved thanks to the space-parameters separated representation involved in the proper generalized decomposition (PGD) that allows circumventing the curse of dimensionality. Thus the parametric solution will be available fast and easily.

Such parametric solution could be viewed as a sort of abacus, but despite its inherent interest such calculation is at present unaffordable for nowadays computing availabilities because one must solve too many problems and of course store all the solutions related to each choice of both parameters.

Parametric solution of coupled models by using the PGD. Model reduction of complex coupled flow models. Analysis of Rayleigh-Bernard flows involving nanofluids.

The purpose of this paper is to propose an interactive 2D–3D garment parametric pattern-making and linkage editing scheme that integrates clothing design, simulation and interaction to design 3D garments and 2D patterns. The proposed scheme has the potential to satisfy the individual needs of fashion industry, such as precise fit evaluation of the garment, interactive style editing with ease allowance and constrained contour lines in fashion design.

The authors first construct a parametric pattern-making model for flat pattern design corresponding to the body dimensions. Then, the designing 2D patterns are stitched on a virtual 3D mannequin by performing a virtual try-on. If the customer is unsatisfied after the virtual try-on, the adjustable parameters (appearance parameters and fit parameters) can be adjusted using the 2D–3D linkage editing with hierarchical constrained contour lines, and the fit evaluation tool interactively provides the feedback.

The authors observed that the usability and efficiency of the existing garment pattern-making method simplifies the garment pattern-making process. The authors utilize an interactive garment parametric flat pattern-making model to generate an individualized garment flat pattern that effectively adjust and realize the local editing of the garment pattern-making. The 2D–3D linkage editing is then employed, which alters the size and shape of garment pattern for a precise human model fit of the 3D garment using hierarchical constrained contour lines. Various instances have validated the effectiveness of the proposed scheme, which can increase the reusability of the existing garment styles and improve the efficiency of fashion design.

First, the authors do not consider the garment pattern-making design of sophisticated styles. Second, the authors do not directly consider complex garment shapes such as wrinkles, folds, multi-layer models and fabric physical properties.

The authors propose a pattern adjustment scheme that uses the 3D virtual try-on technology to avoid repetitions of reality-based fit tests and garment sample making in the designing process of clothing products. The proposed scheme provides interactive selections of garment patterns and sizes and renders modification tools for 3D garment designing and 2D garment pattern-making. The authors present the 2D–3D interactive linkage editing scheme for a custom-fit garment pattern based on the hierarchical constraint contour lines. The spatial relationship among the human body, pattern pieces and 3D garment model is adequately expressed, and the final design result of the garment pattern is obtained by constraint solving. Meanwhile, the tightness tension of different parts of the 3D garment is analyzed, and the fit and comfort of the garment are quantitatively evaluated.