Buckling-restrained braced frames (BRBFs) are a widely used lateral system comprised of beams, columns, and diagonal buckling restrained braces (BRBs). The BRBs within these frames are typically oriented concentrically. Current U.S. design provisions limit the eccentricities in BRBFs to less than the beam depth, which results in less architectural flexibility as compared to eccentrically braced frames (EBFs). The purpose of the present study is to investigate the design and performance of BRBFs with larger beam eccentricities. BRBFs were designed with beam eccentricities ranging from 0 (control case) to 2 times the beam depth in the chevron (inverted-V) and single-diagonal configurations. In each case, the beams were designed to remain elastic under the maximum forces that could be delivered by the braces, including the effects of the brace eccentricity on the beam. Nonlinear response history analysis and pushover analysis were used to quantify the performance of the various frames under design earthquake shaking and to investigate the relationship between BRBF beam eccentricity and seismic performance for the cases considered. The results of this study are presented in a two-part paper. This paper, constituting Part 1, describes the design procedures for BRBFs with eccentricity in chevron and single-diagonal configurations. Analysis methods for determining force demands in braces, beams, and columns are presented. The analysis methods are illustrated through the design of nine case study buildings. The designs show the impact that eccentricities have on member sizing and overall frame weight. For chevron BRBFs, eccentricities of 1 to 2 times the beam depth resulted in overall frame weight increase of 1.07 to 1.32 times, due to heavier beams. For single-diagonal BRBFs, eccentricities of 2 times the beam depth resulted in a slight reduction of overall weight, due to moment frame action associated with the eccentric beam stub. The accompanying paper, Part 2 (Li et al., 2026), presents the nonlinear analysis studies, including response history analyses and pushover analysis, for evaluating the seismic performance of these nine case study designs.

Errata to Vol. 62, No. 1 paper Generalized Elastic Lateral-Torsional Buckling of Steel Beams

Concrete-filled composite plate shear walls (C-PSW/CF) are an emerging structural system in building construction. The composite wall-to-base connection is a critical component influencing system behavior and design. Different types of composite wall-to-base connections are possible, but the noncontact lap splice connection between the dowel bars of the reinforced concrete (RC) base and the steel faceplates of the composite walls is of interest due to its constructability and potential structural efficiency. This type of wall-to-base connection can govern the lateral resistance of the overall wall system, which may be acceptable for wind loading situations and, depending on ductility, may also be acceptable for seismic loading conditions. This study presents the design and detailing of noncontact dowel bar lap splice connections for composite walls-to-RC foundations or walls. Design parameters include embedment length and arrangement of dowel bars within the composite wall cross section and the interfacial shear strength provided using ties or a combination of ties and stud anchors (shear studs) to transfer forces from the dowel bar to the steel faceplates. Previous recommendations for these parameters, provided in the literature, are used and verified experimentally. Three large-scale specimens with different connection details are designed, constructed, and tested to failure. The experimental results are evaluated, and design recommendations are proposed along with methods to calculate the flexural stiffness and flexural strength of the composite wall-to-base connections.

This is the second of two companion papers discussing the seismic design and performance of buckling-restrained braced frames (BRBFs) with braces oriented in eccentric configurations. The companion paper (Li et al., 2026) introduces the proposed design procedures for the BRBFs with eccentricities and presents the elastic design results of nine case study buildings representing two building heights (12- and 3-story), two bracing configurations (chevron and single-diagonal), and various eccentricities. This paper first presents nonlinear response history analysis (NLRHA) results for the nine design case study buildings subjected to 16 ground motions scaled to the design basis earthquake (DBE) and maximum considered earthquake (MCE) levels. The analytical results demonstrate that BRBFs with eccentricities equal to twice the beam depth—double the current code limit of one beam depth—perform satisfactorily under seismic loading, provided they are properly capacity designed to account for brace eccentricities. The paper explores the relationship between brace eccentricity and key response parameters. The NLRHA results also validate the accuracy of the proposed analysis methods in estimating beam force demands in capacity design. Subsequently, nonlinear pushover analysis results for specific stories in selected chevron design cases are presented, with a focus on the effects of connection geometry, specifically combined and split gusset configurations, on local stress state in the beam region, analyzed through detailed finite element modeling. Lastly, the NLRHA results suggest that intentionally introducing brace eccentricities in single-diagonal BRBFs could potentially lead to more economical designs with enhanced seismic performance (e.g., reduced residual story drifts) as compared to concentric frames. Accordingly, design implications for single-diagonal eccentric BRBFs are explored, particularly concerning column capacity design with moment demands and the approximate story drift distribution for preliminary brace sizing.

The purposes of this paper are to summarize the research on the torsional performance of square and rectangular hollow section members and compare the available experimental results to the applicable provisions in the AISC Specification (2022). A review of the research on the torsional strength of square and rectangular hollow section members revealed 49 experimental tests from 11 projects. A first-order reliability analysis was used to calculate appropriate resistance factors for the current design equations, revealing inconsistent reliability indices that are dependent on the predicted failure mode. Revisions are proposed for the provisions in AISC Specification Section H3.1 that result in a simpler design method with increased accuracy. Also, the accuracy of serviceability rotation calculations is evaluated using the available experimental data.

Research under way on large-format metallic additive manufacturing for structural steel applications is highlighted. Dr. Ryan Sherman, Associate Professor in the School of Civil and Environmental Engineering at the Georgia Institute of Technology, leads this study. Dr. Sherman’s research on steel bridge and ancillary highway structures encompasses large-scale laboratory testing, field monitoring, material characterization, and finite element simulation. Research interests include fatigue, fracture, and additive manufacturing for civil engineering infrastructure. The Terry Peshia Early Career Faculty Award (AISC), the Robert J. Dexter Memorial Award Lecture (Steel Bridge Task Force), and Georgia Tech’s Student Recognition of Excellence in Teaching are among Dr. Sherman’s accolades. An AISC Milek Fellowship, awarded in 2023, supports this research, building on work with Lincoln Electric Additive Solutions and funded by the Federal Highway Administration (FHWA). As part of that effort, AISC Undergraduate Research Fellow Shirin Raschid Farrokhi investigated fatigue performance under the mentorship of PhD candidate Hannah Kessler. Kessler, the 2025 Reidar Bjorhovde Outstanding Young Professional recipient, also conducted tension, impact, and fatigue testing for the FHWA project and, with PhD student Zachary de Haaff, has been integral to the research team. Selected highlights from completed and planned research are presented.

Digital transformation (DX) is imperative for every business entity that wants to be competitive in its industrial sector. The rapid rise and widespread propagation of the coronavirus (COVID-19) has hastened DX across various industries, especially the construction industry. As a result, construction companies are on the verge of radical DX, which is primarily driven by digital innovation and advancement. However, knowledge regarding DX implementation for construction firms is limited and fragmented, leading to unsuccessful DX implementation for most of the construction companies. This paper investigates the interrelationship of the critical success factors (CSFs) for DX implementation by construction contractors. A fuzzy cognitive map (FCM) is adopted to analyze the interrelationship of these factors, constructed based on inputs from 17 experts with extensive experience in construction and digital technologies. The outdegree, indegree, and total degree values of the FCM indicate the factors that influence other factors the most, the factors that are influenced by other factors the most, and the most important factors, respectively. It is found that effective leadership has the highest outdegree value and total degree value, whereas the research and development capability of organizations has the highest indegree value. These findings provide the fundamentals of DX implementation in construction businesses and their interrelationship. For example, understanding that effective leadership strongly influences other success factors enables firms to prioritize leadership development initiatives early in the DX process. Likewise, recognizing that research and development capability is highly influenced by other factors helps contractors identify which upstream capabilities must be strengthened first. By leveraging these insights, construction contractors can embrace digital innovations and technologies for their businesses successfully.

The class imbalance, characterized by an unequal distribution between normal and abnormal classes, is predominantly observed in the field of fault diagnosis. Abnormal classes typically represent a minority, leading to a biased learning process favoring the majority class. Therefore, class balancing techniques are essential when applying deep learning approaches to ensure accurate classification of minority fault classes. In this study, we investigate and propose weighted approach for the gated recurrent unit (GRU) algorithm. The proposed weighted approach adjusts all three weights-input, recurrent, and bias inside the GRU architecture. Additionally, the synthetic minority over-sampling (SMOTE) technique with vanilla GRU and long short-term memory (LSTM) as well as the combination of SMOTE and the proposed weighting technique for GRU and LSTM, are compared to the proposed weighting architecture with GRU. We evaluate the effectiveness of this technique using operational data from a real multi-stage flash desalination plant, synthesizing datasets with varying imbalance ratios (4, 9, and 14) for evaluation. Performance metrics such as accuracy is employed for evaluation. Among the models tested, the weighted GRU (WGRU), the proposed model, consistently outperforms others across all variables and imbalance ratios.

As immersive technologies continue to evolve, the metaverse has emerged as a promising direction in smart education. This study presents the design and evaluation of ChulaVerse World, a virtual reality platform developed to replicate Chulalongkorn University’s campus and support immersive learning through 3D navigation and virtual classrooms. The system integrates a detailed 3D university map and an interactive communication layer to facilitate spatial orientation and collaborative academic experiences. Two pilot courses were conducted using an exploratory case study approach: the first, “Beginner to Metaverse,” involved on-site training for first-year engineering students, while the second, “Full Experience Online Metaverse,” was delivered entirely online. Quantitative data were collected using a structured survey instrument based on the Unified Theory of Acceptance and Use of Technology (UTAUT), with qualitative feedback captured through open-ended responses and in-class observations. The results showed strong student interest in using the platform in future courses and moderate satisfaction with its performance, interface, and usability. These outcomes align with previous studies in metaverse-based education, emphasizing the importance of onboarding support, user interface clarity, and scalable technical design. The study highlights the potential of ChulaVerse World to enhance accessibility, engagement, and digital transformation in university-level education.

Given the intricacy of the cocoa supply chain and the abundance of relevant data, effectively managing factor variations proves to be a challenge, making traditional mathematical optimization methods insufficient for practical applications. This study formulates a three-phase optimization approach combining Mixed-Integer Linear Programming (MILP) and Simulation-Based Optimization (SBO), where MILP determines strategic decisions (i.e., supplier selection and establishment of distribution centers), and the simulation derives tactical plans (i.e., inventory levels) under demand uncertainty. The proposed approach combines the strengths of both methods and helps compensate for their weaknesses. Moreover, this study demonstrates the necessity of maximizing Economic Value Added (EVA) by prioritizing the capital charge from an investment when designing the network instead of the operating profit maximization, which considers the short-term gains. Employing a case study on the food industry in Southern Vietnam, the effectiveness of this approach and its ability to derive valuable managerial insights can be demonstrated. The proposed three-phase approach can enhance a significant methodological deficiency by introducing a hybrid approach that effectively encapsulates the structural and dynamic intricacies inherent in supply chain systems, while simultaneously optimizing for EVA, the financial performance metric that has been overlooked in many existing supply chain modeling approaches.