Article
Construction & Building Technology
Aicha Diakite-Kortlever, Nils Weber, Martine Knoop
Summary: This study examines the reconstruction accuracy of the spectral power distribution (SPD) of daylight and compares different reconstruction procedures. The results show that a localized procedure outperforms the CIE method in terms of accuracy. However, the improvement in reconstruction accuracy does not affect the assessment of non-image forming (NIF) effects. This implies that cost-effective sensors and simplified representation methods can be used for NIF purposes.
Article
Construction & Building Technology
Marshal Maskarenj, Bertrand Deroisy, Sergio Altomonte
Summary: This paper presents a tool and workflow based on 17 original Python-scripted Grasshopper components to simulate the non-image-forming (NIF) stimulation from indoor daylight. By evaluating the yearly variations of potential NIF stimulation, it aims to propose robust building design and modeling concepts that balance lighting energy use and occupants' comprehensive needs.
ENERGY AND BUILDINGS
(2022)
Article
Mechanics
Sedigheh Mohamadnejad Zanjani, Ali Basti, Reza Ansari
Summary: Forming limit diagram is an important tool for investigating the plastic deformation ability of sheet metals. It can predict forming limits for various strain paths. Strain path has a significant effect on forming limits, while it has a minor impact on stress forming limit diagrams. By combining crystal plasticity method and Marciniak-Kuczyniski (M-K) method, forming limits of different crystal materials can be anticipated.
MECHANICS OF TIME-DEPENDENT MATERIALS
(2022)
Article
Engineering, Electrical & Electronic
Yuanyi Fan, Ran Zhang, Ze Liu, Jinkui Chu
Summary: This paper studies the polarization characteristics of scattered skylight and proposes a novel skylight orientation sensor with advantages of simple structure and good real-time performance. The sensor's angle measurement accuracy and uncertainty are verified through numerical simulation and outdoor experiments, demonstrating its potential application in autonomous navigation.
IEEE SENSORS JOURNAL
(2021)
Article
Construction & Building Technology
Chi Chen, Mitsuyoshi Akiyama, Sopokhem Lim, Soichiro Kondo, Yuka Hosono, Yudan Lai, Koki Aoki
Summary: This paper investigates the shear performance of centrifugally formed hollow circular steel fiber reinforced concrete (HSFRC) piles and develops an equation for shear strength assessment under practical manufacturing conditions. The centrifugal forming process optimizes the distribution and orientation of steel fibers, effectively enhancing shear performance. Even with a low steel fiber content, HSFRC piles achieve equivalent shear performance compared to traditional reinforced concrete piles.
CONSTRUCTION AND BUILDING MATERIALS
(2023)
Article
Transportation Science & Technology
Jinlong Yuan, Changzhi Wu, Kok Lay Teo, Jun Xie, Song Wang
Summary: Perimeter control manipulates traffic flow by adjusting traffic signals at border regions to alleviate urban traffic congestion. This paper addresses the issue of time delay dependence on traffic state in perimeter control and the unavailability of optimal reference points and equilibrium points in advance. An optimal feedback control problem is formulated, and a hybrid algorithm combining filled function method and gradient-based method is proposed to solve this challenging problem effectively.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2023)
Article
Materials Science, Multidisciplinary
Basavaraj H. Vadavadagi, H. Bhujle, Rajesh Kisni Khatirkar
Summary: The study focused on the microstructure evolution and forming behavior of interstitial free steels, showing that IF steel has higher formability compared to IF-HS steel. Microstructural developments play a crucial role in affecting forming limits and influencing forming limit diagrams.
JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE
(2021)
Article
Materials Science, Multidisciplinary
Yanju Wang, Aixue Sha, Xingwu Li, Chonglin Jia, Wenfeng Hao
Summary: In this study, the forming limit of the GH605 superalloy was determined using digital image correlation analysis to monitor strain evolution. Material constants were obtained through tensile experiments, and different forming limit test methods were compared to establish a complete forming limit diagram. Factors influencing the forming limit were analyzed, and forming limit diagrams for three types of GH605 superalloys were obtained, showing a typical 'V' shape curve with the minimum forming limit near plane strain.
JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE
(2021)
Article
Engineering, Multidisciplinary
Joaquim G. Sanctorum, Sam Van Wassenbergh, Van Nguyen, Jan De Beenhouwer, Jan Sijbers, Joris J. J. Dirckx
Summary: Geometric distortion in x-ray tomography can be effectively corrected by a dynamic method based on digital image correlation. The results demonstrate that three projections with a 120 degrees interval are sufficient to correct any frame, reducing the distortion errors by at least 96%. This new method improves system geometry calibration accuracy and enhances shape preservation in tomographic reconstruction.
MEASUREMENT SCIENCE AND TECHNOLOGY
(2021)
Article
Materials Science, Multidisciplinary
M. A. Bertinetti, A. Roatta, E. Nicoletti, M. Leonard, M. Stout, J. W. Signorelli
Summary: Digital-image correlation techniques can now be used to measure the forming-limit diagram (FLD) of metal sheets, and the relationship between Bragard-type and temporal FLDs varies depending on the metal's strain-rate sensitivity. The strain paths followed by different metals with the same MK sample geometries were found to be different, indicating the need to account for different FLDs for positive strain-rate sensitive metals.
JOURNAL OF MATERIALS ENGINEERING AND PERFORMANCE
(2021)
Article
Materials Science, Multidisciplinary
Danielle Cristina Camilo Magalhaes, Sergio Alberto Elizalde Huitron, Jose Maria Cabrera Marrero, Osvaldo Mitsuyuki Cintho, Andrea Madeira Kliauga, Vitor Luiz Sordi
Summary: Multilayered sheets of AA1050 and AA7050 Al alloys produced by hot accumulative roll bonding (ARB) were tested to estimate their forming limit diagrams (FLDs), and the mechanical behavior and microstructure were analyzed. The results showed that the multilayered sheets had a bimodal grain size distribution and texture components, and the sheets processed at 500 degrees C exhibited better formability.
ADVANCED ENGINEERING MATERIALS
(2023)
Article
Geography, Physical
Manuel Salvoldi, Aviv L. Cohen-Zada, Arnon Karnieli
Summary: This study demonstrates the concept validation of using Venus microsatellites with relatively low spatial resolution to detect moving vehicles in a single pass. The unique stereoscopic capability of the microsatellite's super-spectral camera enables the detection of moving vehicles without preprocessing or geometric corrections. The study shows successful detection of small to medium-sized vehicles and proves the effectiveness of the proposed methodology during the Covid-19 pandemic in 2020.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2022)
Article
Construction & Building Technology
A. K. Diakite-Kortlever, M. Knoop
Summary: This paper analyzes the forecast accuracy of current state-of-the-art, data-driven, spectral sky models. The results show that spectral sky models play an important role in predicting non-image-forming effects, but there is an issue of underestimation in the assumption of the CIE standard illuminant D65.
LIGHTING RESEARCH & TECHNOLOGY
(2021)
Article
Automation & Control Systems
Qiqi Zhu, Weihuan Deng, Zhuo Zheng, Yanfei Zhong, Qingfeng Guan, Weihua Lin, Liangpei Zhang, Deren Li
Summary: This article introduces a spectral-spatial-dependent global learning framework based on global convolutional long short-term memory and global joint attention mechanism to address insufficient and imbalanced HSI classification. Proposed hierarchically balanced sampling strategy and weighted softmax loss to tackle imbalanced sample problems, and achieved superior performance compared to other state-of-the-art methods in experiments on three public HSI datasets.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Crystallography
Ahmed Elsayed, Diego Gonzalez, Evgenia Yakushina
Summary: Within the framework of the formability limit assessment in sheet metal forming, the alternative of testing notched tensile samples coupled with digital image correlation (DIC) has been analyzed to overcome the implications of Nakajima testing. Specific notched sample geometries have been investigated to accurately identify the forming limits of Aluminium alloy AA6016 in T4 condition. The strain-rate-dependent method, which works in combination with DIC measurements, was found to be more accurate to determine the necking limits and provides more accurate information for the safe zone of forming.
Article
Construction & Building Technology
Samiran Khorat, Debashish Das, Rupali Khatun, Sk Mohammad Aziz, Prashant Anand, Ansar Khan, Mattheos Santamouris, Dev Niyogi
Summary: Cool roofs can effectively mitigate heatwave-induced excess heat and enhance thermal comfort in urban areas. Implementing cool roofs can significantly improve urban meteorology and thermal comfort, reducing energy flux and heat stress.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Qi Li, Jiayu Chen, Xiaowei Luo
Summary: This study focuses on the vertical wind conditions as a main external factor that limits the energy assessment of high-rise buildings in urban areas. Traditional tools for energy assessment of buildings use a universal vertical wind profile estimation, without taking into account the unique wind speed in each direction induced by the various shapes and configurations of buildings in cities. To address this limitation, the study developed an omnidirectional urban vertical wind speed estimation method using direction-dependent building morphologies and machine learning algorithms.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Xiaojun Luo, Lamine Mahdjoubi
Summary: This paper presents an integrated blockchain and machine learning-based energy management framework for multiple forms of energy allocation and transmission among multiple domestic buildings. Machine learning is used to predict energy generation and consumption patterns, and the proposed framework establishes optimal and automated energy allocation through peer-to-peer energy transactions. The approach contributes to the reduction of greenhouse gas emissions and enhances environmental sustainability.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Ying Yu, Yuanwei Xiao, Jinshuai Chou, Xingyu Wang, Liu Yang
Summary: This study proposes a dual-layer optimization design method to maximize the energy sharing potential, enhance collaborative benefits, and reduce the storage capacity of building clusters. Case studies show that the proposed design significantly improves the performance of building clusters, reduces energy storage capacity, and shortens the payback period.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Felix Langner, Weimin Wang, Moritz Frahm, Veit Hagenmeyer
Summary: This paper compares two main approaches to consider uncertainties in model predictive control (MPC) for buildings: robust and stochastic MPC. The results show that compared to a deterministic MPC, the robust MPC increases the electricity cost while providing complete temperature constraint satisfaction, while the stochastic MPC slightly increases the electricity cost but fulfills the thermal comfort requirements.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Somil Yadav, Caroline Hachem-Vermette
Summary: This study proposes a mathematical model to evaluate the performance of a Double Skin Facade (DSF) system and its impact on indoor conditions. The model considers various design parameters and analyzes their effects on the system's electrical output and room temperature.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Ruijun Chen, Holly Samuelson, Yukai Zou, Xianghan Zheng, Yifan Cao
Summary: This research introduces an innovative resilient design framework that optimizes building performance by considering a holistic life cycle perspective and accounting for climate projection uncertainties. The study finds that future climate scenarios significantly impact building life cycle performance, with wall U-value, windows U-value, and wall density being major factors. By using ensemble learning and optimization algorithms, predictions for carbon emissions, cost, and indoor discomfort hours can be made, and the best resilient design scheme can be selected. Applying this framework leads to significant improvements in building life cycle performance.
ENERGY AND BUILDINGS
(2024)