Wood-frame Buildings Research Articles

INVESTIGATING THE SEISMIC PERFORMANCE OF WOOD-FRAMED SHEAR WALL WITH ADVANCED CONNECTION SYSTEMS IN STRUCTURAL WOOD DESIGN AND ENGINEERING

Wood-framed buildings are popular for residential and commercial construction due to their sustainability, costeffectiveness, and aesthetic appeal. However, their seismic performance is a concern, particularly in earthquakeprone regions. This study investigates the seismic performance of wood-framed buildings with advanced connection systems. The research evaluates the structural integrity and resilience of wood-framed buildings subjected to seismic loads. Advanced connection systems, including innovative fastening techniques and reinforced connections, are analyzed to determine their effectiveness in enhancing the seismic performance of wood-framed buildings. The study aims to provide valuable insights for designers, engineers, and builders to improve the seismic resilience of wood-framed buildings. seismic performance of wood-framed buildings, advanced connection systems, and structural wood design. Determine areas requiring further investigation. The fundamentals of displacement-based seismic design are presented along with a description of the system parameters required for its application. A simple numerical model capable of predicting the cyclic response and energy dissipation characteristics of wood shear walls under general quasi-static cyclic loading is presented to evaluate these parameters for wood-framed buildings. The generalization of this model to three-dimensional wood-framed structures is also discussed. As an application example, the displacement-based seismic design of a simple one-story shear wall building is presented. In turn, this design approach is validated by nonlinear dynamic time-history analyses using earthquake records representative of the hazard levels associated with the design performance levels.

Comparative analysis of artificial intelligence models for real-time and future forecasting of environmental conditions: A wood-frame historic building case study

Precise environmental monitoring within historic buildings is crucial for ensuring optimal conditions that guarantee the proper preservation of these structures, thereby maintaining their integrity and cultural legacy. Moreover, outdoor environmental conditions can potentially impact the indoor environment, especially in historic structures with deficient insulation materials and damaged envelopes. As climate change points to more recurrent and severe extreme climatic events in the coming years, a current and future comprehensive evaluation of indoor microclimate in historic structures is essential. This study investigated the utilization of machine learning and deep learning algorithms for real-time and future forecasting of the indoor microclimate, including air temperature, relative humidity, and dew point, in a historic building located in San Antonio, Texas, USA. In situ monitored data from April 2022 to January 2023 were used to train different predictive algorithms. The results indicated that Multi-Layer Perceptrons and Support Vector Machine models yielded the most accurate values in terms of real-time forecasting of the indoor microclimate, while Extreme Gradient Boosting model excelled in convergence time. Additionally, Long Short-Term Memory models were the most accurate in predicting indoor microclimate using future weather data for the current century, specifically for 2050 and 2080. The methodology developed in this study can be applied to different construction types and locations globally. As it enables the prediction of environmental conditions crucial for historic preservation, the results have the potential to assist experts in making informed decisions about conserving historic structures, both now and in the future.

Mainshock-aftershock building fragility methodology for community resilience modeling

This study introduces a methodology for developing fragility functions that enable the assessment of seismic vulnerability and resilience at the community level for buildings subjected to mainshock-aftershock sequences. To date, this has been assessed at a single structural level or through statistical combinatorial approaches. This paper provides a solution for a suite of archetypes including ductile and non-ductile reinforced concrete frames as well as woodframe buildings. The findings highlight the central role of aftershocks in exacerbating damage states and increasing economic losses, emphasizing the importance of including these events in accurate assessments of community resilience and seismic risk. The suite of archetypes is applied at the community level using the IN-CORE platform to quantify the effect of incorporating aftershocks into community-level seismic vulnerability analyses. The ability to accurately include the effect of aftershocks within community-level risk and resilience analyses will be key to planning for earthquakes.

Auto-WoodSDA: A scalable end-to-end automation framework to perform probabilistic seismic risk and recovery assessment of new residential woodframe buildings

The seismic performance of residential woodframe buildings has a widespread and lasting impact on the socioeconomic vitality of a community. To enable efficient seismic risk and resilience assessment, a comprehensive framework that is rooted in performance-based earthquake engineering (PBEE) methodology is proposed. The framework is formulated as a computational workflow which is operationalized as an automation program dubbed “Auto-WoodSDA”. The end-to-end platform is developed to perform four major tasks: (1) generate code-compliant seismic design, (2) create numerical models, (3) perform nonlinear analyses, and (4) assess earthquake-induced financial losses and functional recovery time. Given the user inputs, Auto-WoodSDA sequentially executes the four tasks without intermediate human intervention to produce seismic performance metrics such as the expected annual loss. It is presented as a ready-to-implement platform that is computationally efficient and scalable in performing large-scale seismic risk and resilience assessment. An example building from the existing literature is used to demonstrate the key features of the automation framework and verify the results. The results underscore the ability of the AutoWoodSDA computational workflow to automate the generation of reliable new code-compliant woodframe building designs, perform nonlinear analysis, and assess the earthquake-induced impacts using PBEE principles.

WITHDRAWAL – Administrative Duplicate Publication: Statistical Analysis of Japan Wood Frame Building Earthquake Debris Extent and Its Use in Road Networks in Japan

WITHDRAWAL – Administrative Duplicate Publication: Statistical Analysis of Japan Wood Frame Building Earthquake Debris Extent and Its Use in Road Networks in Japan

Implementation of Wood-Framed Buildings in the Nordic Region: A MADAMOS (an Integrated Multi-Criteria Decision-Making Approach for Profitable Realization Alternatives) Method

This study optimizes the sustainable implementation of light wood-framed buildings in the Nordic region using multi-criteria decision-making. Integrating prefabrication, transportation logistics, and multi-criteria decision-making (MCDM) methods enhances cost efficiency, time savings, and quality assurance. Significant international and local impact promotes sustainable construction practices. Strong promotion fosters industry-wide adoption. The presented framework enables stakeholders to make informed decisions, enhancing the efficiency and effectiveness of building implementation processes and fostering sustainable development in the construction industry.

Regional climate change adaptation planning: a case study on single-story wooden-frame residential buildings vulnerable to hurricane winds in selected US coastal locations

The projected increase in sea surface temperature due to climate change is expected to substantially intensify future hurricanes. Wooden light-frame residential buildings are particularly vulnerable to hurricane damage, and their risk is expected to increase due to heightened exposure and intensifying hurricanes. Therefore, adaptation strategies need to be planned to reduce damage to such buildings while considering the impact of climate change on hurricanes. This study investigates the effectiveness of various climate change adaptation strategies for coastal wood-frame single-story residential buildings and demonstrates how these strategies can be planned. The study considers the four Representative Concentration Pathways (RCPs) proposed by the IPCC to investigate the impact of climate change on wind hazard and losses. Additionally, three locations in the coastal United States of varying sizes, exposure, and hurricane hazard levels are considered: Harris County, Texas; Mobile County, Alabama; and Miami-Dade County, Florida. The results show that the increase in wind speeds and losses will be non-linear with time. All considered adaptation strategies decreased losses, with some able to completely counter the increasing losses even under high emission scenarios. Investigating the effectiveness of adaptive measures can guide stakeholders in allocating funds and efforts for hurricane risk management and enhancing community resilience.

Attractiveness of wood-frame multi-storey buildings in seven European countries: consumer segmentation and the effect of fire safety information

Wooden construction has the potential to contribute to climate change mitigation, and it is being promoted by the EU and national governments. However, several market barriers to wood-frame multi-storey building (WMSB), have been recognized, including obstacles in national building codes, lack of expertise in wood construction, and material durability concerns among end-users as well as other technical aspects. Given that increased wood construction is a target, understanding consumer perceptions of WMSB is crucial. In this study, consumer attitudes on WMSB were studied through consumer segmentation relying on demographic attributes. Further, the effect of providing fire safety information was explored. To this end, an online survey was deployed in seven European countries, with 7007 responses. The results show that in general, the awareness and attractiveness of WMSB is low amongst European consumers. Out of all respondents, 46% had not heard of WMSB before and only 12% stated that they are interested in the subject and know something about it, showing a clear lack of information and awareness within the general public. Significant differences in the perceived attractiveness of wooden multi-storey construction between consumer segments exist, with younger consumers and urban consumers being more attracted to living in WMSB than older or rural consumers. Fire safety was an important attribute affecting overall attractiveness, yet updated information regarding fire safety and control in WMSBs had a small but statistically significant negative effect on the perceived attractiveness. The results indicate that targeted marketing efforts are needed to inform potential consumers of WMSB and aspects related to fire safety effectively.

Machine Learning-Based Seismic Damage Assessment of Residential Buildings Considering Multiple Earthquake and Structure Uncertainties

Wood-frame structures are used in almost 90% of residential buildings in the United States. It is thus imperative to rapidly and accurately assess the damage of wood-frame structures in the wake of an earthquake event. This study aims to develop a machine-learning-based seismic classifier for a portfolio of 6,113 wood-frame structures near the New Madrid Seismic Zone (NMSZ) in which synthesized ground motions are adopted to characterize potential earthquakes. This seismic classifier, based on a multilayer perceptron (MLP), is compared with existing fragility curves developed for the same wood-frame buildings near the NMSZ. This comparative study indicates that the MLP seismic classifier and fragility curves perform equally well when predicting minor damage. However, the MLP classifier is more accurate than the fragility curves in prediction of moderate and severe damage. Compared with the existing fragility curves with earthquake intensity measures as inputs, machine-learning-based seismic classifiers can incorporate multiple parameters of earthquakes and structures as input features, thus providing a promising tool for accurate seismic damage assessment in a portfolio scale. Once trained, the MLP classifier can predict damage classes of the 6,113 structures within 0.07 s on a general-purpose computer.

Comparative assessment of alternative methods for evaluating the optimality of ground motion intensity measures using woodframe buildings

Selection of an optimal ground motion intensity measure (IM) is one of the preliminary yet integral steps in minimizing uncertainty propagation through the probabilistic performance-based earthquake engineering framework. The optimal IM is evaluated and selected based on two widely known evaluation metrics: efficiency and sufficiency. In this study, the univariate regression- and entropy-based methods that are currently available to compute efficiency and sufficiency are presented. More importantly, the existing methods are expanded to account for multivariate relationships between various engineering demand parameters (EDPs), the IM, and the causal parameters. Finally, a comparative assessment of alternative methods is performed based on 10 different IMs and 10 woodframe archetype buildings. The univariate and multivariate methods produce comparable results for the efficiency-based assessment with SaT1 and ASI performing comparably well. Also, for all IMs, both the dispersion and joint entropy are found to be lower in the single-family dwellings (SFDs) compared to the multi-family dwellings (MFDs). This observation can be explained by the higher ductility demands in the latter of the two building types. Similar results are also obtained between the univariate and multivariate entropy-based sufficiency evaluations. In both cases (univariate and multivariate), SaT1 and PGA are the most sufficient IMs for SFDs and MFDs with Saavg also performing well for the MFDs.

Physics-based probabilistic capacity models and fragility estimates for light wood frame shear walls

Light wood frame buildings are common in the United States, and due to their prevalence, there has been significant damage to this type of building in previous earthquakes. For this building type, shear walls (typically sheathed with oriented strand board) are the main lateral force-resisting element. Probabilistic models and fragility estimates incorporating the prevailing uncertainties for shear walls are needed to make accurate predictions of the effects of future earthquakes on buildings of this type. This paper uses experimental data to develop probabilistic capacity models for the shear force and drift of light wood frame shear walls at the yield, peak, and ultimate performance levels. The proposed models are applicable to shear walls in low-rise buildings where the shear deformation is dominant. Moreover, the proposed models are applicable to walls that are similar to walls in the dataset. The probabilistic models are constructed starting from deterministic models. For the shear force, a new deterministic model is proposed. This model predicts the shear force capacity of the wall based on the capacity of individual nails. For drift, existing deterministic drift limits are used. The deterministic models are then improved by incorporating the effect of additional physical characteristics through explanatory basis functions that are shown to be significant in a probabilistic model selection procedure. Finally, fragility estimates are constructed for an example shear wall using the proposed capacity models and conditioning on the shear force and drift demands.

Review of wind loading on roof to wall connections in low-rise light wood-frame residential buildings

Several post-hurricane studies have indicated the prevalence of roof damage in low-rise wood-frame buildings. One of the major reasons for this includes failure of roof-to-wall connections (RTWCs). This has led to a lot of research on RTWCs in a bid to understand the reasons for the failures, the capacities of the RTWCs and development of better RTWCs especially in hurricane prone regions. This study reviews the research works to date on factors affecting wind loads on RTWCs. It explores the experimental tests on RTWCs in roofing structures and component tests of single RTWCs. Numerical and analytical modeling of RTWCs as part of a roof system or as single connections are all reviewed. Finally, recommendations for future research works to bridge current knowledge gaps are made.

Costs of Implementing Design for Adaptability Strategies in Wood-Framed Multifamily Housing

Owners, occupants, and society are constantly changing the demands and expectations placed on buildings. Design for adaptability (DfA) provides one approach for delivering buildings that serve current needs and that can be readily adapted to meet future demands. The benefits and strategies of DfA have been widely reported; however, there is a dearth of information on the costs of implementing DfA. This paper presents a case study evaluating the economic costs of applying select DfA strategies to a wood-framed multifamily residential building in Atlanta. Comparisons are made between the construction costs of a baseline non-DfA building and a series of adaptable buildings. DfA strategies in the adaptable buildings include increased floor live load, increased floor-to-floor height, and the use of post-and-beam framing instead of interior structural walls. When all three of these strategies were implemented in the same design, the estimated building construction cost increased by 14%. The cost increase ranged from 1% to 7% when only one of the DfA strategies was implemented in a design. These comparisons are intended to facilitate cost–benefit analyses by designers, owners, and contractors interested in intentionally designed adaptable buildings.

Seismic performance of high-capacity light wood frame shear walls with three rows of nails

With the increase of building height for light wood-frame construction and seismic loads in National Building Code of Canada 2015, stronger shear wall systems have been facing higher demands, especially for mid-rise wood-frame buildings located in high seismic zones. In collaboration with FPInnovations, a new high-capacity shear wall system with two or three rows of nails was developed. This paper presents the test results of shear walls with three rows of nails. A total of 12 specimens (with two standard shear wall specimens as a reference) were tested under reversed cyclic loading. Test results show that shear walls with three rows of nails have approximately-three times the lateral load resistance of a standard shear wall with the same sheathing thickness, nail diameter and nail spacing. The initial stiffness and ultimate displacement of the high-capacity shear wall are also greater than the comparable standard shear wall. Seismic equivalency to standard shear walls in accordance with ASTM D7989 was also conducted. Although shear walls with three rows of nails have three times of lateral load capacities of a standard shear wall, their design values are less than twice the design values of the standard shear walls. This is mainly due to the fact that a higher over-strength factor has to be used to meet the ductility criteria in ASTM D7989.

Motivators and impediments to seismic retrofit implementation for wood-frame soft-story buildings: A case study in California.

Motivating property owners to mitigate seismic risks for existing buildings is a major challenge for many earthquake-prone regions. This article identifies primary factors that may affect the adoption of seismic retrofit by owners of commercial and residential buildings, assesses the influence of economic, social, regulatory, and individual factors on retrofit implementation in three California cities, and discusses potential approaches to promoting seismic retrofits. Data for three retrofit programs are utilized to create predictive models for retrofit probability. The results suggest that retrofit probability for multifamily residential buildings may increase with building height, median housing value, educational attainment, and population density in the neighborhood, but may decrease with building age, building size, land value, and housing vacancy rate in the neighborhood. The retrofit decision for commercial buildings is strongly correlated with the number of stories and rooms, land value, vacancy rate, and population density, while the retrofit decision for residential buildings is highly associated with building age, number of rooms, land value, median housing value, median contract rent, and educational attainment. Overall, promoting seismic retrofits requires careful consideration of different motivators and impediments to owner's retrofit actions for commercial and residential buildings, and for older, taller, larger buildings, which tend to be more vulnerable but are associated with higher retrofit costs. In addition, neighborhood characteristics including median housing value and vacancy rate may be strong indicators of the retrofit probability among building clusters.

Substitution impacts of Nordic wood-based multi-story building types: influence of the decarbonization of the energy sector and increased recycling of construction materials

BackgroundThe building and construction sectors represent a major source of greenhouse gas (GHG) emissions. Replacing concrete and steel with wood is one potential strategy to decrease emissions. On product level, the difference in fossil emissions per functional unit can be quantified with displacement factors (DFs), i.e., the amount of fossil emission reduction achieved per unit of wood use when replacing a functionally equivalent product. We developed DFs for substitution cases representative of typical wood-frame and non-wood frame multi-story buildings in the Nordic countries, considering the expected decarbonization of the energy sector and increased recycling of construction products.ResultsMost of the DFs were positive, implying lower fossil emissions, if wood construction is favored. However, variation in the DFs was substantial and negative DFs implying higher emissions were also detected. All DFs showed a decreasing trend, i.e., the GHG mitigation potential of wood construction significantly decreases under future decarbonization and increased recycling assumptions. If only the decarbonization of the energy sector was considered, the decrease was less dramatic compared to the isolated impact of the recycling of construction materials. The mitigation potential of wood construction appears to be the most sensitive to the GHG emissions of concrete, whereas the emissions of steel seem less influential, and the emissions of wood have only minor influence.ConclusionsThe emission reduction due to the decarbonization of the energy sector and the recycling of construction materials is a favorable outcome but one that reduces the relative environmental benefit of wood construction, which ought to be considered in forest-based mitigation strategies. Broadening the system boundary is required to assess the overall substitution impacts of increased use of wood in construction, including biogenic carbon stock changes in forest ecosystems and in wood products over time, as well as price-mediated market responses.

Determination of Individual Building Performance Targets to Achieve Community-Level Social and Economic Resilience Metrics

The retrofit of wood-frame residential buildings is a relatively effective strategy to mitigate damage caused by windstorms. However, little is known about the effect of modifying building performance for intense events such as a tornado and the subsequent social and economic impacts that result at the community level following an event. This paper presents a method that enables a community to select residential building performance levels representative of either retrofitting or adopting a new design code that computes target community metrics for the effects on the economy and population. Although not a full risk analysis, a series of generic tornado scenarios for different Enhanced Fujita (EF) ratings are simulated, and five resilience metrics are assigned to represent community goals based on economic and population stability. To accomplish this, the functionality of the buildings following the simulated tornado is used as input to a computable general equilibrium (CGE) economics model that predicts household income, employment, and domestic supply at the community level. Population dislocation as a function of building damage and detailed sociodemographic US census-based data is also predicted and serves as a core community resilience metric. Finally, this proposed methodology demonstrates how the metrics can help meet community-level resilience objectives for decision support based on a level of design code improvement or retrofit level. The method is demonstrated for Joplin, Missouri. All analyses and data have been developed and made available on the open-source IN-CORE modeling environment. The proposed multidisciplinary methodology requires continued research to characterize the uncertainty in the decision support results.

A simplified approach to assess the technical prefeasibility of multistory wood-frame buildings in high seismic zones

Timber structures present a promising solution to reduce the current environmental footprint of the construction industry. For timber buildings designed in seismic zones, wood-frame shear walls are a common lateral resistant system for low- and mid-rise structures. However, for practitioners and engineers unfamiliar with seismic analysis methods for wood-frame structures, estimation of the systems viability can be complex and time-consuming, hindering an extended adoption of timber structures. Therefore, this paper presents a novel methodology to determine at early design phases the technical feasibility of wood-frame structures in highly seismic zones, so-called Simplified Tool for Technical Pre-feasibility or STTP framework. The methodology was developed by analyzing a comprehensive database of 201 wood-frame buildings designed with different seismic performance factors, architectural configurations, number of stories, soil conditions, and anchorage system. By employing input data readily available at the initial stages of structural projects, the proposed methodology verifies the viability of employing wood-frame shear walls as the lateral resistant system of the structure, and provides additional valuable information such as fundamental periods and wall predesigns. Besides, global stiffness and inter-story deformations can be estimated with an error less than 11%. In this way, accurate feedback can be promptly obtained by employing a minimum amount of resources. The results from the methodology can be employed along with cost calculation methods so as to estimate the economic impact of the project and different solutions.

Quantifying the effect of probability model misspecification in seismic collapse risk assessment

One of the main steps in probabilistic seismic collapse risk assessment is estimating the fragility function parameters. The maximum likelihood estimation (MLE) approach, which is widely used for this purpose, contains the underlying assumption that the likelihood function is known to follow a specified parametric probability distribution. However, this assumed distribution may not always be consistent with the “true” probability distribution of the collapse data. This paper implements the Information matrix equivalence theorem to identify the presence of model misspecification i.e., if the assumed collapse probability distribution is, in fact, the “true” one. In the presence of model misspecification, the fragility parameter estimates continue to be asymptotically normally distributed but the variance–covariance matrix is no longer equal to the inverse of the Fisher’s Information matrix. To increase the robustness of the variance–covariance matrix, the Huber–White sandwich estimator is implemented. Using collapse data from eight woodframe buildings, the effect of model misspecification on fragility parameter estimates and collapse rate is quantified. For the considered building cases, the parameter estimation uncertainty in the collapse risk did not increase when the “sandwich” estimator was used compared to when probability model misspecification was not considered (i.e., using MLE). The proposed framework should be used to further investigate the issue of probability model misspecification as it relates to fragility parameter estimation since only a single construction type (woodframe buildings) and limit state (collapse) was considered in the current study.

Infrared thermography for quantitative thermal performance assessment of wood-framed building envelopes in Canada

Since many buildings in Canada were built prior to the advent of national and provincial energy codes and standards, quantifying building envelope thermal performance is an important step in identifying retrofit opportunities in existing buildings. This study aimed to use external quantitative infrared thermography (IRT) to estimate effective U-value of opaque building envelopes (considering the effect of thermal bridging sources) of a conditioned at-scale structure comprised of four wood-framed wall assemblies commonly used in Canada. Furthermore, the effect of vignetting artefacts on effective U-value measurements was assessed, followed by a practical approach to correcting for it to improve accuracy of U-value estimation and calibration of energy models. Additionally, a comprehensive uncertainty analysis was performed to evaluate the impact of input variables on the accuracy and uncertainty of results. Finally, apart from qualitative and quantitative thermal assessment of the building envelope, a novel relative quantitative infrared index (IRI) methodology was proposed as a means to facilitate rapid evaluation and subsequent ranking of building envelope thermal performance. The results indicated that vignetting effect has an adverse impact on the accuracy of results, in particular for well-insulated walls where deviations of −42.31% to −83.33% were observed. However, when the proposed practical approach was implemented, substantial improvements in accuracy of walls’ U-value were obtained, ranging from −2.33% to −12.50% after correction versus −13.95% to −58.33% without correction. Moreover, the results indicated that the energy model was substantially more accurate when the effect of thermal bridges were accounted for, and the adverse effect of vignetting was addressed in the estimation of U-value. In this case, ASHRAE Guideline 14 criteria were satisfied: Normalized Mean Bias Error (NMBE) < 5%, and Coefficient of Variation of the Root Mean Square Error (CVRMSE) < 15%. The findings of the uncertainty budget demonstrated that the influence of parameters on U-value depends on the type of wall assembly. Ultimately, wall thermal performance rankings based on IRI were consistent with their U-value rankings, implying that IRI can be a reliable metric for relative quantitative comparison of building envelope thermal performance, regardless of boundary conditions.