Change search
Link to record
Permanent link

Direct link
Alternative names
Publications (10 of 197) Show all publications
Jassim, H., Krantz, J., Lu, W. & Olofsson, T. (2020). A Model to Reduce Earthmoving Impacts. Journal of Civil Engineering and Management, 26(6), 490-512
Open this publication in new window or tab >>A Model to Reduce Earthmoving Impacts
2020 (English)In: Journal of Civil Engineering and Management, ISSN 1392-3730, E-ISSN 1822-3605, Vol. 26, no 6, p. 490-512Article in journal (Refereed) Published
Abstract [en]

Meeting increasingly ambitious carbon regulations in the construction industry is particularly challenging for earthmoving operations due to the extensive use of heavy-duty diesel equipment. Better planning of operations and balancing of competing demands linked to environmental concerns, costs, and duration is needed. However, existing approaches (theoretical and practical) rarely address all of these demands simultaneously, and are often limited to parts of the process, such as earth allocation methods or equipment allocation methods based on practitioners’ past experience or goals. Thus, this study proposes a method that can integrate multiple planning techniques to maximize mitigation of project impacts cost-effectively, including the noted approaches together with others developed to facilitate effective decision-making. The model is adapted for planners and contractors to optimize mass flows and allocate earthmoving equipment configurations with respect to tradeoffs between duration, cost, CO2 emissions, and energy use. Three equipment allocation approaches are proposed and demonstrated in a case study. A rule-based approach that allocates equipment configurations according to hauling distances provided the best-performing approach in terms of costs, CO2 emissions, energy use and simplicity (which facilitates practical application at construction sites). The study also indicates that trucks are major contributors to earthmoving operations’ costs and environmental impacts.

Place, publisher, year, edition, pages
VGTU Press, 2020
Keywords
earthmoving operations, optimization framework, optimum configuration, tradeoff duration, cost, emissions
National Category
Construction Management
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-73322 (URN)10.3846/jcem.2020.12641 (DOI)000544410400001 ()2-s2.0-85088745185 (Scopus ID)
Note

Validerad;2020;Nivå 2;2020-07-23 (cisjan)

Available from: 2019-03-26 Created: 2019-03-26 Last updated: 2020-09-02Bibliographically approved
Chen, S., Lu, W., Olofsson, T., Dehghanimohammadabadi, M., Emborg, M., Nilimaa, J., . . . Kailun, F. (2020). Concrete Construction: How to Explore Environmental and Economic Sustainability in Cold Climates. Sustainability, 12(9), Article ID 3809.
Open this publication in new window or tab >>Concrete Construction: How to Explore Environmental and Economic Sustainability in Cold Climates
Show others...
2020 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 12, no 9, article id 3809Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
MDPI, 2020
Keywords
cold climate, discrete event simulation, concrete maturity analysis, curing measures, decision support
National Category
Other Materials Engineering Construction Management Other Civil Engineering
Research subject
Structural Engineering; Construction Management and Building Technology; Building Materials
Identifiers
urn:nbn:se:ltu:diva-78824 (URN)10.3390/su12093809 (DOI)000537476200307 ()2-s2.0-85085985324 (Scopus ID)
Note

Validerad;2020;Nivå 2;2020-05-11 (johcin)

Available from: 2020-05-08 Created: 2020-05-08 Last updated: 2022-02-10Bibliographically approved
Shadram, F., Bhattacharjee, S., Lidelöw, S., Mukkavaara, J. & Olofsson, T. (2020). Exploring the trade-off in life cycle energy of building retrofit through optimization. Applied Energy, 269, Article ID 115083.
Open this publication in new window or tab >>Exploring the trade-off in life cycle energy of building retrofit through optimization
Show others...
2020 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 269, article id 115083Article in journal (Refereed) Published
Abstract [en]

Building retrofit is considered as a vital step to achieve energy and climate goals in both Europe and Sweden. Nevertheless, retrofitting solutions based merely on reducing operational energy use can increase embodied energy use, mainly due to altering the existing trade-off between the two. Considering this trade-off is vitally important, especially for retrofitting buildings located in cold climate regions, as reduction of operational energy use to meet standards of energy-efficient buildings may require a deep retrofitting that can considerably increase the embodied energy and thus be unfavorable from a Life Cycle Energy (LCE) perspective. This article presents a case study in which multi-objective optimization was used to explore the impact of a wide range of retrofitting measures on the aforementioned trade-off for a building in Sweden located in a subarctic climatic zone. The studied building was a typical 1980s multi-family residence. The goal was to explore and compare the optimal retrofitting solution(s) for the building, aiming to achieve Swedish energy-efficient building standards (i.e. new-build and near-zero energy standards). The results of the optimization indicated that (1) use of additional insulation in walls and roof, (2) replacement of existing windows with more energy-efficient ones, and (3) change of traditional mechanical extract ventilation to heat recovery ventilation are the primary and optimal retrofitting measures to fulfill the new-build Swedish energy standard and achieve highest LCE savings. However, to fulfill more far-reaching operational energy savings, application of additional retrofitting measures was required, increasing the embodied energy use considerably and resulting in lower LCE savings compared to the optimal retrofitting solution that only reached the Swedish new-build energy standard. The LCE difference between the optimal retrofitting solutions that fulfilled the new-build standard and the strictest near-zero (passive house) standard was 1862 GJ, which is equivalent to almost four years of operational energy use for the original building. This indicates that there is a limit to the reduction of operational energy use when retrofitting existing buildings, beyond which additional reductions can considerably increase the embodied energy and thus be unfavorable in terms of LCE use.

Place, publisher, year, edition, pages
Elsevier, 2020
Keywords
Building retrofit, Embodied energy, Life cycle energy, Multi-objective optimization, Operational energy, Retrofitting measures
National Category
Construction Management
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-78989 (URN)10.1016/j.apenergy.2020.115083 (DOI)000537619800048 ()2-s2.0-85084475658 (Scopus ID)
Note

Validerad;2020;Nivå 2;2020-05-26 (johcin)

Available from: 2020-05-26 Created: 2020-05-26 Last updated: 2023-03-10Bibliographically approved
Wang, Y., Olofsson, T. & Shen, G. Q. P. (Eds.). (2020). ICCREM 2020: Intelligent Construction and Sustainable Buildings: Proceedings of the International Conference on Construction and Real Estate Management 2020. Paper presented at 2020 International Conference on Construction and Real Estate Management (ICCREM 2020), 24-25 August, 2020, Virtual. American Society of Civil Engineers (ASCE)
Open this publication in new window or tab >>ICCREM 2020: Intelligent Construction and Sustainable Buildings: Proceedings of the International Conference on Construction and Real Estate Management 2020
2020 (English)Conference proceedings (editor) (Refereed)
Abstract [en]

Proceedings of the International Conference on Construction and Real Estate Management 2020, held in Stockholm, Sweden, August 24–25, 2020. Sponsored by the Modernization of Management Committee of the China Construction Industry Association and the Construction Institute of ASCE.

This collection contains 97 peer-reviewed papers on sustainable development in the construction industry and the advancement of intelligent construction theories and technologies.

Topics include: intelligent construction and construction informatization; green construction and sustainable buildings; project management and construction industrialization; and construction industry and knowledge management.

These papers will be of interest to researchers, engineering practitioners, developers, and planners from universities, consulting firms, and financial institutions.

Place, publisher, year, edition, pages
American Society of Civil Engineers (ASCE), 2020. p. xiii, 847
National Category
Construction Management
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-81175 (URN)10.1061/9780784483237 (DOI)978-0-7844-8323-7 (ISBN)
Conference
2020 International Conference on Construction and Real Estate Management (ICCREM 2020), 24-25 August, 2020, Virtual
Available from: 2020-10-19 Created: 2020-10-19 Last updated: 2020-10-19Bibliographically approved
Jassim, H., Lu, W. & Olofsson, T. (2019). Determining the environmental impact of material hauling with wheel loaders during earthmoving operations. Journal of the Air and Waste Management Association, 69(10), 1195-1214
Open this publication in new window or tab >>Determining the environmental impact of material hauling with wheel loaders during earthmoving operations
2019 (English)In: Journal of the Air and Waste Management Association, ISSN 1096-2247, E-ISSN 2162-2906, Vol. 69, no 10, p. 1195-1214Article in journal (Refereed) Published
Abstract [en]

A method has been developed to estimate the environmental impact of wheel loaders used in earthmoving operations. The impact is evaluated in terms of energy use and emissions of air pollutants (CO2, CO, NOx, CH4, VOC, and PM) based on the fuel consumption per cubic meter of hauled material. In addition, the effects of selected operational factors on emissions during earthmoving activities were investigated to provide better guidance for practitioners during the early planning stage of construction projects. The relationships between six independent parameters relating to wheel loaders and jobsite conditions (namely loader utilization rates, loading time, bucket payload, horsepower, load factor, and server capacity) were analyzed using artificial neural networks, machine performance data from manufacturer’s handbooks, and discrete event simulations of selected earthmoving scenarios. A sensitivity analysis showed that the load factor is the largest contributor to air pollutant emissions, and that the best way to minimize environmental impact is to maximize the wheel loaders’ effective utilization rates. The new method will enable planners and contractors to accurately assess the environmental impact of wheel loaders and/or hauling activities during earthmoving operations in the early stages of construction projects.

Implications: There is an urgent need for effective ways of benchmarking and mitigating emissions due to construction operations, and particularly those due to construction equipment, during the pre-construction phase of construction projects. Artificial Neural Networks (ANN) are shown to be powerful tools for analyzing the complex relationships that determine the environmental impact of construction operations and for developing simple models that can be used in the early stages of project planning to select machine configurations and work plans that minimize emissions and energy consumption. Using such a model, it is shown that the fuel consumption and emissions of wheel loaders are primarily determined by their engine load, utilization rate, and bucket payload. Moreover, project planners can minimize the environmental impact of wheel loader operations by selecting work plans and equipment configurations that minimize wheel loaders’ idle time and avoid bucket payloads that exceed the upper limits specified by the equipment manufacturer.

Place, publisher, year, edition, pages
Taylor & Francis, 2019
National Category
Construction Management Environmental Analysis and Construction Information Technology
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-74570 (URN)10.1080/10962247.2019.1640805 (DOI)000482496000001 ()31291163 (PubMedID)2-s2.0-85071322959 (Scopus ID)
Note

Validerad;2019;Nivå 2;2019-10-08 (johcin);

Artikeln har tidigare förekommit som manuskript i avhandling.

Available from: 2019-06-14 Created: 2019-06-14 Last updated: 2025-01-15Bibliographically approved
Krantz, J., Feng, K., Larsson, J. & Olofsson, T. (2019). ‘Eco-Hauling’ Principles to Reduce Carbon Emissions and the Costs of Earthmoving: a Case Study. Journal of Cleaner Production, 208, 479-489
Open this publication in new window or tab >>‘Eco-Hauling’ Principles to Reduce Carbon Emissions and the Costs of Earthmoving: a Case Study
2019 (English)In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 208, p. 479-489Article in journal (Refereed) Published
Abstract [en]

Mitigating emissions of carbon dioxide and other greenhouse gases is critical if we are to meet the increasing threats posed by global warming. Previous studies have shown conclusively that a substantial part of all carbon dioxide emissions comes from transportation, and that Eco-Driving principles based upon strategic, tactical, and operational decisions have the potential to reduce these emissions. However, these well-established principles have been neglected within the construction industry despite the large number of transport-related activities that attend most construction projects. This paper therefore aims to increase awareness and understanding within the industry of the potential reductions of both carbon dioxide emissions and the costs of earthmoving activities that could be achieved through the use of Eco-Driving principles. A new concept labeled ‘Eco-Hauling’, which extends the Eco-Driving concept to earthmoving, is proposed. A case study of a road project has been conducted and used to demonstrate the new concept. Discrete-event simulation is used to support the data analysis as it enables modeling of the dynamic interactions between equipment and activities of multiple different construction scenarios. The presented findings show that a combination of decisions taken from the proposed Eco-Hauling concept can enable earthmoving contractors to substantially reduce carbon dioxide emissions and costs while maintaining productivity. This study has implications for the general advancement of Eco-Driving theory, as well as for project management as it sets out a viable approach for reducing greenhouse gas emissions in construction projects.

Place, publisher, year, edition, pages
Elsevier, 2019
Keywords
Earthworks, Eco-Driving, Mass-Hauling, Off-Road dump truck, Discrete-Event simulation, Articulated hauler
National Category
Construction Management
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-71227 (URN)10.1016/j.jclepro.2018.10.113 (DOI)000451362200045 ()2-s2.0-85056193207 (Scopus ID)
Note

Validerad;2018;Nivå 2;2018-11-07 (johcin) 

Available from: 2018-10-16 Created: 2018-10-16 Last updated: 2023-09-05Bibliographically approved
Kadefors, A., Olofsson, T. & Ask, M. (2019). Innovation processes and dissemination of research-based knowledge in Swedish rock engineering: Experiences in the TRUST GeoInfra project. Stiftelsen Bergteknisk Forskning (BeFo)
Open this publication in new window or tab >>Innovation processes and dissemination of research-based knowledge in Swedish rock engineering: Experiences in the TRUST GeoInfra project
2019 (English)Report (Refereed)
Alternative title[sv]
Innovationsprocesser och spridning av forskningsbaserad kunskap inom svenskt bergbyggande : Erfarenheter från projektet TRUST GeoInfra
Abstract [en]

Innovation in the project-based construction industry is perceived as complex and poorly understood. Based on a study of a large collaborative R&D programme to develop knowledge and new engineering methods for Swedish underground construction, we discuss and analyse the innovation system in this area with a focus on dissemination and implementation of research-based knowledge in business projects. The result is primarily based on interviews performed with representatives of clients, contractors, consultants, researchers and funding bodies within the TRUST project. There are two main focus areas: the innovation system level and the TRUST project. The innovation system level describes drivers, organization and processes for engaging in R&D and implementing results within the Swedish Transport Administration (STA), contractor companies and consultancy firms, but also interviewee opinions about the innovation culture in Swedish rock engineering and construction more generally.

Abstract [sv]

Innovationsklimatet i den projektbaserade byggindustrin är komplext och dåligt undersökt på en övergripande nivå. Denna rapport beskriver innovationssystemet inom svenskt undermarksbyggande med utgångspunkt i en studie av kunskapsspridning och nyttiggörande i det stora forskningsprogrammet TRUST, Transparent Underground Structures. Resultatet baseras huvudsakligen på intervjuer med representanter för beställare, entreprenörer, konsulter, forskare och finansieringsorgan inom TRUST-projektet. Två nivåer har studerats: det övergripande innovationssystemet inom undermarksbyggande och hur spridning och implementering av forskningsbaserade resultat har skett inom TRUST-projektet. Innovationssystemnivån beskriver drivkrafter, strategier, organisation och processer för att engagera sig i FoU och implementera FoU-baserad kunskap i affärsprojekt inom Trafikverket, entreprenadföretag och konsultföretag, men även åsikter om innovationskulturen inom svenskt undermarksbyggande mer generellt.

Place, publisher, year, edition, pages
Stiftelsen Bergteknisk Forskning (BeFo), 2019. p. 41
Series
BeFo Report, ISSN 1104-1773 ; 183
National Category
Construction Management Geochemistry
Research subject
Construction Management and Building Technology; Applied Geochemistry
Identifiers
urn:nbn:se:ltu:diva-78473 (URN)
Available from: 2020-04-14 Created: 2020-04-14 Last updated: 2020-10-01Bibliographically approved
Sandberg, M., Mukkavaara, J., Shadram, F. & Olofsson, T. (2019). Multidisciplinary Optimization of Life-Cycle Energy and Cost Using a BIM-Based Master Model. Sustainability, 11(1), Article ID 286.
Open this publication in new window or tab >>Multidisciplinary Optimization of Life-Cycle Energy and Cost Using a BIM-Based Master Model
2019 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 11, no 1, article id 286Article in journal (Refereed) Published
Abstract [en]

Virtual design tools and methods can aid in creating decision bases, but it is a challenge to balance all the trade-offs between different disciplines in building design. Optimization methods are at hand, but the question is how to connect and coordinate the updating of the domain models of each discipline and centralize the product definition into one source instead of having several unconnected product definitions. Building information modelling (BIM) features the idea of centralizing the product definition to a BIM-model and creating interoperability between models from different domains and previous research reports on different applications in a number of fields within construction. Recent research features BIM-based optimization, but there is still a question of knowing how to design a BIM-based process using neutral file formats to enable multidisciplinary optimization of life-cycle energy and cost. This paper proposes a framework for neutral BIM-based multidisciplinary optimization. The framework consists of (1) a centralized master model, from which different discipline-specific domain models are generated and evaluated; and (2) an optimization algorithm controlling the optimization loop. Based on the proposed framework, a prototype was developed and used in a case study of a Swedish multifamily residential building to test the framework’s applicability in generating and optimizing multiple models based on the BIM-model. The prototype was developed to enhance the building’s sustainability performance by optimizing the trade-off between the building’s life-cycle energy (LCE) and life-cycle cost (LCC) when choosing material for the envelope. The results of the case study demonstrated the applicability of the framework and prototype in optimizing the trade-off between conflicting objectives, such as LCE and LCC, during the design process.

Place, publisher, year, edition, pages
MDPI, 2019
Keywords
BIM, multidisciplinary optimization, middleware, master model, house-building
National Category
Construction Management
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-72517 (URN)10.3390/su11010286 (DOI)000457127300286 ()2-s2.0-85059672308 (Scopus ID)
Note

Validerad;2019;Nivå 2;2019-01-30 (svasva)

Available from: 2019-01-11 Created: 2019-01-11 Last updated: 2022-02-10Bibliographically approved
Feng, K., Lu, W., Olofsson, T., Chen, S., Yan, H. & Wang, Y. (2018). A predictive environmental assessment method for construction operations: Application to a Northeast China case study. Sustainability, 10(11), Article ID 3868.
Open this publication in new window or tab >>A predictive environmental assessment method for construction operations: Application to a Northeast China case study
Show others...
2018 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 10, no 11, article id 3868Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
MDPI, 2018
Keywords
environmental impacts, construction process simulation, process-based life cycle assessment, construction operations, supply chain
National Category
Infrastructure Engineering Construction Management
Research subject
Structural Engineering; Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-71690 (URN)10.3390/su10113868 (DOI)000451531700042 ()2-s2.0-85055572047 (Scopus ID)
Note

Validerad;2018;Nivå 2;2018-11-21 (jochin) 

Available from: 2018-11-21 Created: 2018-11-21 Last updated: 2022-02-10Bibliographically approved
Jassim, H. S. .., Lu, W. & Olofsson, T. (2018). Assessing energy consumption and carbon dioxide emissions of off-highway trucks in earthwork operations: an artificial neural network model. Journal of Cleaner Production, 198, 364-380
Open this publication in new window or tab >>Assessing energy consumption and carbon dioxide emissions of off-highway trucks in earthwork operations: an artificial neural network model
2018 (English)In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 198, p. 364-380Article in journal (Refereed) Published
Abstract [en]

Methods capable of predicting the energy use and CO2 emissions of off-highway trucks, especially in the initial planning phase, are rare. This study proposed an artificial neural networks (ANN) model to assess such energy use and CO2 emissions for each unit volume of hauled materials associated with each hauling distance. Data from discrete event simulations (DES), an off-highway truck database, and different site conditions were simultaneously analyzed to train and test the proposed ANN model. Six independent quantities (i.e., truck utilization rate, haul distance, loading time, swelling factor, truck capacity, and grade horsepower) were used as the input parameters for each model. The developed model is an efficient tool capable of assessing the energy use and CO2 emissions of off-highway trucks in the initial planning stage. The results revealed that the grade horsepower and haul distances yield a significant increase in the environmental impact of the trucks. In addition, the results demonstrated that, for a given set of project conditions, the environmental impact of trucks can reduced by improving their utilization rate and reducing the loading time.

Place, publisher, year, edition, pages
Elsevier, 2018
Keywords
Off-highway truck, energy consumption, CO2 emission, Simulation, ANN prediction model, initial planning stage
National Category
Construction Management
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-70115 (URN)10.1016/j.jclepro.2018.07.002 (DOI)000442973100032 ()2-s2.0-85053160594 (Scopus ID)
Note

Validerad;2018;Nivå 2;2018-08-08 (andbra)

Available from: 2018-07-12 Created: 2018-07-12 Last updated: 2020-08-26Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-5661-5237

Search in DiVA

Show all publications