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Open Access
Article
Publication date: 22 June 2022

Serena Summa, Alex Mircoli, Domenico Potena, Giulia Ulpiani, Claudia Diamantini and Costanzo Di Perna

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with…

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Abstract

Purpose

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

Design/methodology/approach

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

Findings

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

Originality/value

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

Details

Construction Innovation , vol. 24 no. 7
Type: Research Article
ISSN: 1471-4175

Keywords

Open Access
Article
Publication date: 25 March 2024

Divya Surendran Nair and Seema Bhandare

The purpose of this study was to examine how well a strength-based program grounded in positive psychology principles can advance the practical critical thinking skills of those…

Abstract

Purpose

The purpose of this study was to examine how well a strength-based program grounded in positive psychology principles can advance the practical critical thinking skills of those pursuing the teacher training course.

Design/methodology/approach

This study used a single-group pre-test post-test design with 35 teacher-trainees from the Bachelor of Education course. The two-and-a-half-week strength-based program used the values in action survey to identify strengths. Pre- and post-test scores, measured with the Cornell Critical Thinking Test – Level Z, underwent Statistical Package for Social Sciences analysis including paired samples t-test for subcomponent and overall composite analysis.

Findings

Analysis of the pre- and post-test scores demonstrated a statistical significance in the critical thinking scores obtained by the teacher-trainees. Post-test scores were consistently significant. Out of the elements of critical thinking, induction, meaning, observation and credibility were more prominent. Deduction and assumption identification were also having a significant effect.

Originality/value

Most critical thinking programs focus on evaluating specific teaching methods for improving critical thinking skills. In education, positive psychology studies often center on students’ well-being, attention spans and academic success, aligning with wellness programs. Despite the importance of strengths in positive psychology, there is a lack of research on using a strength-based approach to boost critical thinking skills. This study aims to enhance teacher-trainees’ critical thinking by leveraging their individual strengths, moving away from traditional instructional strategies.

Article
Publication date: 2 April 2024

Yixue Shen, Naomi Brookes, Luis Lattuf Flores and Julia Brettschneider

In recent years, there has been a growing interest in the potential of data analytics to enhance project delivery. Yet many argue that its application in projects is still lagging…

Abstract

Purpose

In recent years, there has been a growing interest in the potential of data analytics to enhance project delivery. Yet many argue that its application in projects is still lagging behind other disciplines. This paper aims to provide a review of the current use of data analytics in project delivery encompassing both academic research and practice to accelerate current understanding and use this to formulate questions and goals for future research.

Design/methodology/approach

We propose to achieve the research aim through the creation of a systematic review of the status of data analytics in project delivery. Fusing the methodology of integrative literature review with a recently established practice to include both white and grey literature amounts to an approach tailored to the state of the domain. It serves to delineate a research agenda informed by current developments in both academic research and industrial practice.

Findings

The literature review reveals a dearth of work in both academic research and practice relating to data analytics in project delivery and characterises this situation as having “more gap than knowledge.” Some work does exist in the application of machine learning to predicting project delivery though this is restricted to disparate, single context studies that do not reach extendible findings on algorithm selection or key predictive characteristics. Grey literature addresses the potential benefits of data analytics in project delivery but in a manner reliant on “thought-experiments” and devoid of empirical examples.

Originality/value

Based on the review we articulate a research agenda to create knowledge fundamental to the effective use of data analytics in project delivery. This is structured around the functional framework devised by this investigation and highlights both organisational and data analytic challenges. Specifically, we express this structure in the form of an “onion-skin” model for conceptual structuring of data analytics in projects. We conclude with a discussion about if and how today’s project studies research community can respond to the totality of these challenges. This paper provides a blueprint for a bridge connecting data analytics and project management.

Details

International Journal of Managing Projects in Business, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1753-8378

Keywords

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