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.

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

The 2022 edition of the AISC Specification for Structural Steel Buildings allows member and system instability effects to be accounted for by using advanced analysis methods that model these effects directly or through the use of the B1 (P-δ) and B2 (P-Δ) multipliers. For compression members subject to end moments only, the B1 multiplier is expressed as a function of the smaller to larger end moment ratio. This ratio is taken as positive when the member bends in reverse curvature and negative when it bends in single curvature. This code equation for B1 often overestimates the P-δ effect for double curvature bending under a high axial force but underestimates the P-δ effect for single curvature bending under almost all values of axial force. The reason for the overestimation is because the derivation of the B1 equation uses the equivalent moment concept and ignores the actual location where the maximum moment occurs in the member. When this condition is taken into consideration, it is shown herein that the equation is no longer applicable for members bent in reverse curvature under any value of axial force. The reason for the underestimation is because the effect of axial force on the moment ratio is ignored. By incorporating this effect in a new equation for B1, it is shown that this underestimation is drastically reduced. The validity of this proposed B1 multiplier is established by comparison with the corresponding theoretical values.

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.

This study investigates the decoding and comparison of brain signals associated with spoken Thai and English words using deep learning techniques and EEG equipment.In the field of Brain-Computer Interfaces (BCI), researchers have extensively explored methods to decode brain signals into text.Two primary approaches exist: invasive (e.g., ECoG) and non-invasive (e.g., EEG).Invasive methods require surgery and offer highquality signals but carry infection risks.Conversely, non-invasive methods employ scalp electrodes, resulting in lower signal quality but greater practicality for daily use.The present research utilizes three datasets each for Thai and English to evaluate the effectiveness of EEG and compare the outcomes for both languages.The Thai word data consists of three sets: single words ( , , , , ), two-word phrases ( , , , , ), and three-word sentences ( , , , , ).The English word datasets correspond semantically to each Thai set.All results are tested and compared using two machine learning approaches: Multi-Layer Perceptron (MLP) with statistical features and Convolutional Neural Network (CNN) with stacked spectrogram features.The MLP achieved an overall accuracy of 98%, while the CNN achieved 64%.

In this paper, the existing data from previous research projects was analyzed to determine the reliability of the 2022 AISC Specification block shear equations. Additionally, the 1989 AISC Specification provisions and the design equations proposed by Driver et al. (2006), Kamtekar (2012), and Teh and Deierlein (2017) were analyzed. The analysis was limited to normal-strength steels. The data set included a total of 279 experimental tests from 25 research projects. For the data set with only U-shaped block shear patterns, the reliability analysis showed that both the 2022 AISC Specification and the 1989 AISC Specification block shear provisions are conservative.Based on the results, revisions to the AISC Specification were proposed. The proposed design method combines attributes from the available design methods to develop a general design method that is applicable to several common connection types. A secondary intention is to enhance clarity and transparency, where the variables affecting the strength are included explicitly in the equations.

A concise review is provided of the classical elastic lateral-torsional buckling moment for steel beams as utilized in the AISC Specification (2022). Rather than make assumptions regarding the cross-section properties, the derivation is provided in its general form for an arbitrary steel beam—that is, one that may be asymmetric and may include any manner of varying geometry, thickness, or cross-section shape. The cross-section properties that underpin the calculation are fully detailed. The assumptions that are inherent in the classical derivations (no shear, no cross-section distortion, etc.) are also fully detailed. The manner in which the generalized lateral-torsional buckling formula may be simplified for particular sections (e.g., a singly symmetric channel) with no loss of accuracy is explained. Adaptations and approximations utilized in the 2022 edition of the AISC Specification for elastic lateral-torsional buckling moment of specific sections (e.g., mono-symmetric I-section, angles, etc.) are assessed against the actual elastic solution, and the accuracy and clarity of the assumptions utilized are evaluated. The generalized formula, consistent with current assumptions but applicable to all structural steel cross sections, is recommended for future reference in the main body of the AISC Specification.

This study aims to examine the influence of incorporating zeolite (Z) and graphene oxide (GO) on the efficiency of self-compacting concrete (SCC).Conventional tests are employed to assess the influence of the change on the microstructure, mechanical properties and durability of the alteration.There is a stronger focus on studying the longlasting nature of waste expulsion.The chosen tests to investigate durability are the Rapid Chloride Penetration Test (RCPT), the rebound hammer test, the acid, alkaline and sulfate resistance test, the Ultrasonic Pulse Velocity (UPV) test, the SEM and XRD examinations of the mineral composition and microstructure.The identified optimum mix Z10G2 (Zeolite 10% and Graphene oxide 0.02%) mixture exhibited superior chemical resistance and mechanical integrity in comparison to conventional concrete (CC).This enhanced both the microscopic arrangement and the physical characteristics of the material.Based on these discoveries, it seems that identified mixes have the capacity to enhance the effectiveness and durability of concrete constructions.The overall findings indicate that inducing identified mix into concrete mixtures has the potential to enhance durability and performance in various environmental conditions.To accurately assess the potential benefits of enhancing the longevity of concrete structures, further investigation is needed to examine the long-term effects on these structures.

This study focuses on developing a scheduling model for sequencing a set of jobs with different release times in a single machine to meet non-similar due dates as well as to reduce total sequence-dependent setup time. A constraint programming (CP) model is proposed to solve the scheduling problem by minimizing makespan under multiple constraints, namely release times, sequence-dependent setup time, and due dates. The proposed constraint programming model is tested and compared with the baseline method derived from as-is scheduling of alloy wheels manufactures. The computational experiments show the proposed constraint programming model outperforms the baseline method in the average improvement in makespan and total setup time. For small-size problems, the proposed scheduling model were optimally solved in a short time, achieving the best average improvement in makespan of 4.8826% and the best average improvement in total setup time of 45.7924%. Despite increasing problem sizes, the proposed scheduling model's computational time deteriorates but continues to provide the best solutions, achieving the best average improvement in makespan of 7.4891% and the best average improvement in total setup time of 55.4033%.

This research examines an ocular prosthesis centre's operation and incorporates scheduling decision techniques to optimise its fabrication.A customised eye prosthesis is a make-to-order product which involves several labour-intensive processes and inherently poses scheduling challenges.As a result, patients' fitment dates are appointed with extra time to account for potential delays.The objective of scheduling is to minimise both total completion time and tardiness.The methodology begins with a process review of the customised eye prosthesis fabrication and criteria.Subsequently, a Mixed Integer Linear Programming (MILP) model is formulated to solve the assignment and sequencing problems.It is found during this stage that computational time increases significantly as the number of orders increases.To solve this problem, a Genetic Algorithm (GA) is proposed to find a near-optimal solution in a reasonable computational time.Instances selected for experiment are based on characteristics of a tertiary hospital's ocular prosthesis centre.Small instances are experimented to validate the proposed algorithm against the MILP model.The GA demonstrates near-optimal solutions with a variance of one percent, with reasonable computational time.Practical-size problems are subsequently solved using the proposed algorithm.In conclusion, the proposed GA yields satisfactory solutions with acceptable runtime for this application.