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Jassim, H., Krantz, J., Lu, W. & Olofsson, T. (2019). A Model to Reduce Earthmoving Impacts.
Open this publication in new window or tab >>A Model to Reduce Earthmoving Impacts
2019 (English)Article in journal (Refereed) Submitted
National Category
Construction Management Infrastructure Engineering
Identifiers
urn:nbn:se:ltu:diva-73322 (URN)
Available from: 2019-03-26 Created: 2019-03-26 Last updated: 2019-07-17
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 ()
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: 2019-10-08Bibliographically 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: 2019-03-26Bibliographically 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, ISSN 2071-1050, 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: 2019-02-22Bibliographically 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
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2018 (English)In: Sustainability, ISSN 2071-1050, 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: 2019-02-27Bibliographically 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)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: 2019-09-13Bibliographically approved
Sandberg, K., Pousette, A., Norén, J., Sandberg, M., Olofsson, T. & Mukkavaara, J. (2018). Hållbarhetsutvärdering av byggnader: Case Ripan i Kiruna. RISE
Open this publication in new window or tab >>Hållbarhetsutvärdering av byggnader: Case Ripan i Kiruna
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2018 (Swedish)Report (Other academic)
Abstract [en]

Sustainability includes several parameters, and these can be measured and valued in many different ways. This study focuses on balancing the various parts to achieve sustainability by minimizing energy for heating and energy to produce the materials used in the building as well as minimizing cost for material investment and cost for heating using optimization techniques. This is balanced together with the environmental impact. This report describes an initial study for sustainability optimization of a smaller building. The goal is to develop a comprehensive approach to provide a broader basis of decisions for new construction.

The calculation included the building envelope (exterior walls, roof and floors), interior walls and stabilizing elements for different frames of wood (timber frame and CLT).

The result from the Ripan Case shows that the timber frame design has the lowest embodied energy and operating energy, and lowest cost for investment and heating during the operating phase. The environmental impact of the timber frame design was also low.

Abstract [sv]

Hållbarhet innefattar flera parametrar och dessa kan mätas och värderas på många olika sätt. Att väga ihop de olika delarna för att uppnå hållbarhet genom att minimera förbrukad energi för uppvärmning och energi för att producera material till bygget samt investeringskostnader för material och kostnader för uppvärmning är fokus i denna rapport. Detta vägs samman med miljöpåverkan. En inledande studie för hållbarhetsoptimering av en mindre byggnad är genomförd med målet är att utveckla en övergripande metod för att ge bredare beslutsunderlag vid nybyggnad.

Beräkningar av inbyggd energi, driftsenergi, investerings- och uppvärmningskostnader har genomförts för ett planerat hus på Camp Ripan i Kiruna. I beräkningen av byggnaden inkluderades klimatskärm (ytterväggar, stomstabiliserande element och grund) för två olika stommar av trä (träregelstomme och KL-trä). För miljöberäkningarna användes främst indata från EPDer och resultatet redovisas i form av klimatpåverkan, CO2-ekvivalenter.

Den utvecklade metoden ger potential för bättre ekologisk och ekonomisk hållbarhet genom ett optimerat val av byggnadsmaterial för byggnader. Optimeringsalgoritmen ger förslag på byggnadsmaterial med minst energiåtgång vid produktion, den sk inbyggda energin, samt vid uppvärmning under driftsfasen samt lägst kostnader. Miljöaspekten vägs också in i bedömningen för att få ett mer heltäckande beslutsunderlag för beställare och projektörer. Metoden är tänkt att i fortsatta studier vidareutvecklas för användning på mer komplexa byggnader som till exempel flerbostadshus.

Resultatet från Case Ripan visar att regelkonstruktionen har lägst inbyggd energi, driftsenergi, investeringskostnad samt kostnad för uppvärmning under driftsfasen. Även miljöpåverkan från regelkonstruktionen var låg.

Place, publisher, year, edition, pages
RISE, 2018. p. 33
Keywords
Sustainability, low energy house, energy optimization, LCA, timber house
National Category
Engineering and Technology
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-73467 (URN)978-91-88907-33-2 (ISBN)
Funder
Swedish Agency for Economic and Regional Growth
Available from: 2019-04-05 Created: 2019-04-05 Last updated: 2019-04-11Bibliographically approved
Jansson, G., Mukkavaara, J. & Olofsson, T. (2018). Interactive visualization for information flow in production chains: Case study industrialised house-building. In: Proceedings of the 35th ISARC, Berlin, Germany: . Paper presented at 35th International Symposium on Automation and Robotics in Construction (ISARC 2018), Berlin, July 20-25 2018 (pp. 382-388). IAARC Publications, 35
Open this publication in new window or tab >>Interactive visualization for information flow in production chains: Case study industrialised house-building
2018 (English)In: Proceedings of the 35th ISARC, Berlin, Germany, IAARC Publications , 2018, Vol. 35, p. 382-388Conference paper, Published paper (Refereed)
Abstract [en]

Predefinitions in house-building platforms is developed as routines to manage project building information models over to production data by documents and digital drawings. Visualisation of the information flow in the industrialised house-building process is hard to track and information are often presented as islands, seldom described in the flow for the entire process. Interactive visualisation, using game technology, has open up for new applications of data -transformation, -visualization and -simulation of project information which is less studied in the context of industrialised house-building. This paper tries to address this issue via a combination of game engine technology and the predefined industrialised house-building process. The game engine technology allow development for end -user demands and functionality to express and visualise values for the daily planning and execution of processes. In a case study approach the development and analysis of four building projects were studied and chosen to the range of product platform predefinitions. Based on object structure for different views, models and the related metadata were visualised with an immersive virtual environment prototype. The prototype, based on game engine technology, was developed to manage incoming building projects variations that followed house-building platform predefinitions. As a visualising tool of engineering, on-site planning and production process the game engine technology simulates and visualize views on product structures, production information, assembling and operation instructions by interactive functions in the game environment.

Place, publisher, year, edition, pages
IAARC Publications, 2018
Keywords
Game engines, industrialised, house-building, information flow, visualization
National Category
Building Technologies Construction Management
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-71305 (URN)10.22260/ISARC2018/0054 (DOI)2-s2.0-85053901208 (Scopus ID)
Conference
35th International Symposium on Automation and Robotics in Construction (ISARC 2018), Berlin, July 20-25 2018
Available from: 2018-10-23 Created: 2018-10-23 Last updated: 2018-10-23Bibliographically approved
Jassim, H., Lu, W. & Olofsson, T. (2018). Quantification of Energy Consumption and Carbon Dioxide Emissions During Excavator Operations. In: Advanced Computing Strategies for Engineering: 25th EG-ICE International Workshop 2018, Lausanne, Switzerland, June 10-13, 2018, Proceedings, Part I. Paper presented at 25th EG-ICE International Workshop 2018, Lausanne, Switzerland, June 10-13, 2018 (pp. 431-453). Cham
Open this publication in new window or tab >>Quantification of Energy Consumption and Carbon Dioxide Emissions During Excavator Operations
2018 (English)In: Advanced Computing Strategies for Engineering: 25th EG-ICE International Workshop 2018, Lausanne, Switzerland, June 10-13, 2018, Proceedings, Part I, Cham, 2018, p. 431-453Conference paper, Published paper (Refereed)
Abstract [en]

A number of studies have assessed the energy consumed and carbon dioxide emitted by construction machinery during earthwork operations. However, little attention has been paid to predicting these variables during planning phases of such operations, which could help efforts to identify the best options for minimizing environmental impacts. Excavators are widely used in earthwork operations and consume considerable amounts of fuel, thereby generating large quantities of carbon dioxide. Therefore, rigorous evaluation of the energy consumption and emissions of different excavators during planning stages of project, based on characteristics of the excavators and projects, would facilitate selection of optimal excavators for specific projects, thereby reducing associated environmental impacts. Here we describe use of artificial neural networks (ANNs), developed using data from Caterpillar’s handbook, to model the energy consumption and CO2 emissions of different excavators per unit volume of earth handled. We also report a sensitivity analysis conducted to determine effects of key parameters (utilization rate, digging depth, cycle time, bucket payload, horsepower, load factor, and hauler capacity) on excavators’ energy consumption and CO2 emissions. Our analysis shows that environmental impacts of excavators can be most significantly reduced by improving their utilization rates and/or cycle times, and reducing their engine load factor. We believe our ANN models can potentially improve estimates of energy consumption and CO2 emissions by excavators. Their use in planning stages of earthworks projects could help planners make informed decisions about optimal excavator(s) to use, and contractors to evaluate environmental impacts of their activities. Finally, we describe a case study, based on a road construction project in Sweden, in which we use empirical data on the quantities and nature of the materials to be excavated, to estimate the environmental impact of using different excavators for the project

Place, publisher, year, edition, pages
Cham: , 2018
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10863
National Category
Construction Management
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-69572 (URN)10.1007/978-3-319-91635-4_22 (DOI)2-s2.0-85049074506 (Scopus ID)978-3-319-91634-7 (ISBN)978-3-319-91635-4 (ISBN)
Conference
25th EG-ICE International Workshop 2018, Lausanne, Switzerland, June 10-13, 2018
Available from: 2018-06-15 Created: 2018-06-15 Last updated: 2019-06-14Bibliographically approved
Mukkavaara, J., Jansson, G. & Olofsson, T. (2018). Structuring information from BIM: A glance at bills of materials. In: Proceedings of the 35th ISARC, Berlin, Germany: . Paper presented at 35th International Symposium on Automation and Robotics in Construction (ISARC 2018), Berlin, July 20-25 2018 (pp. 362-368). IAARC Publications, 35
Open this publication in new window or tab >>Structuring information from BIM: A glance at bills of materials
2018 (English)In: Proceedings of the 35th ISARC, Berlin, Germany, IAARC Publications , 2018, Vol. 35, p. 362-368Conference paper, Published paper (Refereed)
Abstract [en]

Industrialized house-builders are moving towards an enhanced production where management of information along the value chain is critical in order to deliver housing projects on time and with the desired quality. Today digital tools and systems are used in both design and production to produce, deliver and instruct actors throughout the phases of aproject. However, the information usually exists in different islands and manual transfers are required tokeep the flow of information between IT-systems and individuals continuous. A key to improving the ability for the members in different stages of a project to work with the same information is to facilitate different views. One of the building blocks for creating bridges between the islands of information is to introduce bills of materials which can be used to organize information for different purposes. Uniting the use of building information modeling (BIM) withbills of materials (BOM) is therefore our focus in this paper. This is done in the context of industrialized house-building and the facets which it brings to the subject. The aim of this paper is to present an early endeavor into a BOM based approach for structuring information from BIM models. A demonstration tool was developed, and together with application in a case project from an industrialized house-builder, the generation of BOMs from BIM data is illustrated and discussed. The findings illustrates that we can apply different structures to the information located in our BIM models and that we can produce a BOM perspective on our products. Also, it is highlighted that we still need further studies to better understand how application of BOMs in the context of industrialized house-building is realized.

Place, publisher, year, edition, pages
IAARC Publications, 2018
Keywords
Bills of Materials, BIM, Industrialized, House Building
National Category
Building Technologies Construction Management
Research subject
Construction Management and Building Technology
Identifiers
urn:nbn:se:ltu:diva-70333 (URN)10.22260/ISARC2018/0052 (DOI)2-s2.0-85053917327 (Scopus ID)
Conference
35th International Symposium on Automation and Robotics in Construction (ISARC 2018), Berlin, July 20-25 2018
Available from: 2018-08-13 Created: 2018-08-13 Last updated: 2018-10-23Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-5661-5237

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