| 1. |
- Lu, Chujie, et al.
(författare)
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A hybrid ensemble learning framework for zero-energy potential prediction of photovoltaic direct-driven air conditioners
- 2023
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Ingår i: Journal of Building Engineering. - : Elsevier. - 2352-7102. ; 64
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Tidskriftsartikel (refereegranskat)abstract
- Integrating renewable energy is a promising solution for buildings to achieve the net-zero-energy goal. Expanding real-time matching between renewable energy generation and building energy demand can help realize more enormous zero-energy potential in practice. However, there are few studies to investigate the real-time energy matching in renewable energy building design. Therefore, in this study, a hybrid ensemble learning framework is proposed for analyzing and predicting zero-energy potential in the real-time matching of photovoltaic direct-driven air conditioner (PVAC) systems. First, the datasets of zero-energy probability (ZEP) are generated under the three main climate regions in China, which are with consideration of the load flexibility of air conditioners and based on six important design variables. Second, a novel ensemble learning method named Extreme Gradient Boosting (XGBoost) is selected to predict ZEP and the Bayesian Optimization (BO) is adopted to identify the optimal hyperparameters and further improve the prediction performance. The statistical analysis shows that ZEP distributions are very different from one region to another one and the PVAC systems in Beijing are the easiest to achieve the zero-energy goal. Among all the variables, PV capacity is the most significant and positively related to ZEP. The prediction results show BO-XGBoost achieves more than 99% accuracy and outperforms other benchmark models in the ZEP prediction of three cities. In a word, this paper reveals BO-XGBoost is the most effective model for ZEP prediction and provides the framework for designers to utilize zero-energy potential analysis and prediction for the first time.
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| 2. |
- Lu, Chujie, et al.
(författare)
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An improved attention-based deep learning approach for robust cooling load prediction : public building cases under diverse occupancy schedules
- 2023
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Ingår i: Sustainable cities and society. - : Elsevier. - 2210-6707. ; 96
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Tidskriftsartikel (refereegranskat)abstract
- Space cooling in buildings is responsible for massive energy consumption and carbon emissions. Accurate cooling load prediction can facilitate the implementation of energy-efficiency cooling control strategies in practice. In this paper, an improved attention-based deep learning approach is proposed for robust ultra-short-term cooling load prediction. First, a novel time representation learning is introduced to extract the periodicity and non-periodicity of cooling loads efficiently. Then, long short-term memory with an attention mechanism extracts properly the time steps by identifying the relevant hidden states and learns high-level temporal dependency. The approach additionally incorporates extreme gradient boosting through the error reciprocal method, enhancing the elimination of prediction errors and improving robustness. The study takes Guangzhou as an example and generates cooling loads using diverse occupancy schedules of five building types based on the Chinese National Standard and Typical Meteorological Year data. The approach is evaluated on datasets comprising the cooling loads, meteorological data, and contextual information. Through results analysis, the approach outperforms other models in terms of prediction accuracy and robustness across all building types. Additionally, model interpretation is provided regarding feature importance and attention matrixes, which enhances the understanding and transparency of the final prediction from the proposed approach.
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| 3. |
- Chen, Shiwei, et al.
(författare)
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A Discrete Event Simulation-Based Analysis of Precast Concrete Supply Chain Strategies Considering Suppliers’ Production and Transportation Capabilities
- 2019
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Ingår i: ICCREM 2019. - Reston, VA : American Society of Civil Engineers (ASCE). ; , s. 12-24
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Konferensbidrag (refereegranskat)abstract
- The production and transportation capabilities of a precast concrete (PC) component supplier have great impact on the construction of a PC building project. In China, the production and transportation capabilities of different PC suppliers can vary greatly, which will influence contractors’ selection of PC supply chain strategies. However, previous studies often considered the capabilities of PC suppliers to be ideal and failed to compare different PC supply chain strategies under different levels of suppliers capabilities. This study collects detailed data from a PC building project and uses discrete event simulation (DES) to compare different supply chain strategies under different production and transportation capability levels of PC suppliers. Construction duration, construction cost, and greenhouse gas emissions are selected as indicators to compare three different supply chain strategies: just-in-time, on-site storage, and off-site storage. The strengths and weaknesses of each strategy under different capabilities of PC suppliers are found. The results provides guidance for contractors in selecting supply chain strategies when considering PC suppliers’ production and transportation capabilities.
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| 4. |
- Chen, Shiwei, et al.
(författare)
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A Simulation-Based Optimisation for Contractors in Precast Concrete Projects
- 2019
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Konferensbidrag (refereegranskat)abstract
- PurposeThis paper aims to provide decision support for precast concrete contractors about both precastconcrete supply chain strategies and construction configurations.Design/Methodology/ApproachThis paper proposes a simulation-based optimisation for supplychain and construction (SOSC) during the planning phase of PC building projects. The discrete eventsimulation is used to capture the characteristics of supply chain and construction processes, and calculate construction objectives under different plans. Particle swarm optimisation is combined with simulation tofind optimal supply chain strategies and construction configurations.FindingsThe efficiency of SOSC is compared with the parametric simulation approach. Over 70 per centof time and effort used to simulate and compare alternative plans is saved owing to SOSC.Research Limitations/ImplicationsBuilding simulation model costs a lot of time and effort. The data requirement of the proposed method is high.Practical ImplicationsThe proposed SOSC approach can provide decision support for PC contractorsby optimising supply chain strategies and construction configurations.Originality/ValueThis paper has two contributions: one is in providing a decision support tool SOSC tooptimise both supply chain strategies and construction configurations, while the other is in building aprototype of SOSC and testing it in a case study.
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| 5. |
- Chen, Shiwei, et al.
(författare)
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Concrete Construction : How to Explore Environmental and Economic Sustainability in Cold Climates
- 2020
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 12:9
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Tidskriftsartikel (refereegranskat)abstract
- In many cold regions around the world, such as northern China and the Nordic countries,on‐site concrete is often cured in cold weather conditions. To protect the concrete from freezing or excessively long maturation during the hardening process, contractors use curing measures. Different types of curing measures have different effects on construction duration, cost, and greenhouse gas emissions. Thus, to maximize their sustainability and financial benefits, contractors need to select the appropriate curing measures against different weather conditions. However, there is still a lack of efficient decision support tools for selecting the optimal curing measures, considering the temperature conditions and effects on construction performance. Therefore, the aim of this study was to develop a Modeling‐Automation‐Decision Support (MADS) framework and tool to help contractors select curing measures to optimize performance in terms of duration, cost, and CO2 emissions under prevailing temperatures. The developed framework combines a concrete maturity analysis (CMA) tool, a discrete event simulation (DES), and a decision support module to select the best curing measures. The CMA tool calculates the duration of concrete curing needed to reach the required strength, based on the chosen curing measures and anticipated weather conditions. The DES simulates all construction activities to provide input for the CMA and uses the CMA results to evaluate construction performance. To analyze the effectiveness of the proposed framework, a software prototype was developed and tested on a case study in Sweden. The results show that the developed framework can efficiently propose solutions that significantlyreduce curing duration and CO2 emissions.
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| 6. |
- Chokwitthaya, Chanachok, et al.
(författare)
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Ontology for experimentation of human-building interactions using virtual reality
- 2023
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Ingår i: Advanced Engineering Informatics. - : Elsevier. - 1474-0346 .- 1873-5320. ; 55
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Tidskriftsartikel (refereegranskat)abstract
- Scientific experiments significantly enhance the understanding of human-building interactions in building and engineering research. Recently, conducting virtual reality (VR) experiments has gained acceptance and popularity as an approach to studying human-building interactions. However, little attention has been given to the standardization of the experimentations. Proper standardization can promote the reusability, replicability, and repeatability of VR experiments and accelerate the maturity of this emerging experimentation method. Responding to such needs, the authors proposed a virtual human-building interaction experimentation ontology (VHBIEO). It is an ontology at the domain level, extending the ontology of scientific experiments (EXPO) to standardize virtual human-building interaction experimentation. It was developed based on state-of-the-art ontology development approaches. Competency questions (CQs) were used to derive requirements and regulate the development. Semantic Web technologies were applied to make VHBIEO machine-readable, accessible, and processable. VHBIEO incorporates an application view (APV) to support the inclusion of unique information for particular applications. The authors performed taxonomy evaluations to assess the consistency, completeness, and redundancy, affirming no occurrence of errors in its structure. Application evaluations were applied for investigating its ability to standardize and support generating of machine-readable, accessible, and processable information. Application evaluations also verified the capability of APV to support the inclusion of unique information.
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| 7. |
- Erikshammar, Jarkko, et al.
(författare)
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Discrete Event Simulation Enhanced Value Stream Mapping: An Industrialized Construction Case Study
- 2013
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Ingår i: Lean Construction Journal. - 1555-1369. ; 10, s. 47-65
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Tidskriftsartikel (refereegranskat)abstract
- Research Question/Hypothesis: Can a production process design framework created by integrating Value Stream Mapping (VSM) and Discrete Event Simulation (DES) be used to assess the production system performance, as predicted by a future state design of small and medium sized enterprises (SMEs) working in industrialized construction?Purpose: To explore a production process design framework in which VSM is used to identify doable improvements and DES provides analytical evaluation of them.Research Method: The demonstration was carried out at a Swedish SME industrialized construction component manufacturerFindings: VSM is unable to evaluate analytically the performance of the future state design. This inability leads to unnecessary implementation iterations. VSM assumes a deterministic model and cannot describe the dynamic behaviors of a system. The dynamic behavior of the construction processes will result in the future state design not performing as expected. However, by analytically evaluating the future state with DES helped the case company to implement a new production process design.Limitations: DES modeling is still time-consuming and needs skilled professionals, the cost of whom can be prohibitive for SMEs and demonstrated in one case study.Implications: The integration of DES and VSM provides a framework to evaluate and communicate the outcome, hence enhancing the application of VSM.Value for practitioners: A lean framework, which can be used, for industrialized construction processes especially by SMEs with very limited resources, to validate changes before implementing them.
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| 8. |
- Erikshammar, Jarkko, et al.
(författare)
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Parametric Value Stream Mapping Framework : A Case Study of a Small Swedish Industrialized House-Building Supplier
- 2014
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Ingår i: Proceedings of IGLC22. - Oslo, Norway : Akademika forlag. - 9788232104598 - 9788232104604 - 9788232104611 ; , s. 425-436
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Konferensbidrag (refereegranskat)abstract
- Industrialized house-building is based on repetitive processes used in the supply, design, manufacturing and erection of pre-configured houses. Industrialized house-building contractors are dependent on many small suppliers and sub-contractors in their supply chain. These small suppliers, with limited resources and capabilities, need to be able to develop products and processes in order to deliver future customer value without wasting development resources on non-viable products. Our question is whether product development by small and medium-sized (SME) industrialized house-building suppliers could be supported by parametric Value Stream Mapping.The objective is to explore a process design framework in which Value stream Mapping (VSM) is used to identify improvements and to generate product development suggestions, based on a set of parameters defined as P1, P2..., Pn.The testing was carried out at a Swedish SME supplier to the industrialized house-building sector, using a newly-developed roofing board with an integrated membrane, with the parameters (P1) customer needs, (P2) waste on construction site and (P3) construction worker safety. Data were collected using interviews and video-recorded participant observations on two construction sites. Findings indicate that VSM cannot describe attributes of a product other than those associated with production flow. However, parametric VSM helped the case study company to stop current development and instead suggest valuable product attributes. The implications are that parametric VSM enhances the application of VSM. Parametric VSM can be used by SME suppliers as an input to product development in order to validate product attributes before launch. However, this is based on a single case study and further research is needed.
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| 9. |
- Feng, Kailun, 1991-, et al.
(författare)
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A predictive environmental assessment method for construction operations : Application to a Northeast China case study
- 2018
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 10:11
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Tidskriftsartikel (refereegranskat)abstract
- Construction accounts for a considerable number of environmental impacts, especially in countries with rapid urbanization. A predictive environmental assessment method enables a comparison of alternatives in construction operations to mitigate these environmental impacts. Process-based life cycle assessment (pLCA), which is the most widely applied environmental assessment method, requires lots of detailed process information to evaluate. However, a construction project usually operates in uncertain and dynamic project environments, and capturing such process information represents a critical challenge for pLCA. Discrete event simulation (DES) provides an opportunity to include uncertainty and capture the dynamic environments of construction operations. This study proposes a predictive assessment method that integrates DES and pLCA (DES-pLCA) to evaluate the environmental impact of on-site construction operations and supply chains. The DES feeds pLCA with process information that considers the uncertain and dynamic environments of construction, while pLCA guides the comprehensive procedure of environmental assessment. A DES-pLCA prototype was developed and implemented in a case study of an 18-storey building in Northeast China. The results showed that the biggest impact variations on the global warming potential (GWP), acidification potential (AP), eutrophication (EP), photochemical ozone creation potential (POCP), abiotic depletion potential (ADP), and human toxicity potential (HTP) were 5.1%, 4.1%, 4.1%, 4.7%, 0.3%, and 5.9%, respectively, due to uncertain and dynamic factors. Based on the proposed method, an average impact reduction can be achieved for these six indictors of 2.5%, 21.7%, 8.2%, 4.8%, 32.5%, and 0.9%, respectively. The method also revealed that the material wastage rate of formwork installation was the most crucial managing factor that influences global warming performance. The method can support contractors in the development and management of environmentally friendly construction operations that consider the effects of uncertainty and dynamics.
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| 10. |
- Feng, Kailun, 1991-, et al.
(författare)
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An Integrated Environment–Cost–Time Optimisation Method for Construction Contractors Considering Global Warming
- 2018
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Ingår i: Sustainability. - : MDPI. - 2071-1050. ; 10:11
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Tidskriftsartikel (refereegranskat)abstract
- Construction contractors play a vital role in reducing the environmental impacts during the construction phase. To mitigate these impacts, contractors need to develop environmentally friendly plans that have optimal equipment, materials and labour configurations. However, construction plans with optimal environment may negatively affect the project cost and duration, resulting in dilemma for contractors on adopting low impacts plans. Moreover, the enumeration method that is usually used needs to assess and compare the performances of a great deal of scenarios, which seems to be time consuming for complicated projects with numerous scenarios. This study therefore developed an integrated method to efficiently provide contractors with plans having optimal environment-cost-time performances. Discrete-event simulation (DES) and particle swarm optimisation algorithms (PSO) are integrated through an iterative loop, which remarkably reduces the efforts on optimal scenarios searching. In the integrated method, the simulation module can model the construction equipment and materials consumption; the assessment module can evaluate multi-objective performances; and the optimisation module fast converges on optimal solutions. A prototype is developed and implemented in a hotel building construction. Results show that the proposed method greatly reduced the times of simulation compared with enumeration method. It provides the contractor with a trade-off solution that can average reduce 26.9% of environmental impact, 19.7% of construction cost, and 10.2% of project duration. The method provides contractors with an efficient and practical decision support tool for environmentally friendly planning.
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