Transportation projects are unique projects that have many issues such as ROW acquisition, traffic control, and utilities. To help solve some of these issues projects should utilize constructability. Over the past 25 years research on constructability has consistently shown to have substantial cost and schedule benefits. To fully obtain those benefits, constructability should be utilized from the very beginning of the project at the conceptual planning phase. One of the tools to support implementation is 3D and 4D visualization. The benefits and applications of 3D and 4D for transportation project research is still lagging behind building projects. This thesis aims to provide a frame work for how 3D and 4D visualization could have an impactful role if used in the early planning and design process. Two case studies are used for developing that frame work, the Woodall Rodgers Deck Plaza and the Eastern Extension of President George Bush Turnpike projects in Dallas, Texas. Information taken from interviews of Texas Department of Transportation staff are used to develop a list of issues for each project, as well as the impacts those issues have had on the project. For each of those issues a proposal of how using 3D and 4D visualization could help mitigate those issues when implemented during the early planning phases. / text

Construction progress monitoring allows schedule and/or cost deviations to be identified early enough to effectively implement corrective actions. At least 77% of transportation projects experience cost overruns, and as much as 75% of these overruns have been attributed to “real” construction management factors like progress monitoring. Progress is measured on road construction sites in terms of completion percentages at various activity and work package levels. This percentage is then used to identify schedule deviations and support the earned value analysis often used as the baseline for contractor progress payments. Unfortunately, the current methods for producing these completion percentages are not as correct or time efficient as they should be to enable effective project control. The objective of this research is to develop, test, and validate a novel solution for automatically producing completion percentages and progress status determinations that are more correct and time efficient than those generated in current practice. The proposed solution seeks to automatically detect incremental progress on road design layers in 3D as-built point cloud data generated using unmanned aerial photogrammetry and a novel data simulation approach. A parallel as-planned progress estimate is also automatically prepared using 4D information, and the progress status determinations are made by comparing the two results. This solution was tested on 15 datasets (13 simulated and 2 real-world) representing a variety of road designs and progress conditions. The method achieved an average 95% F1 score in layer detection on the real-world data, and mostly outperformed current practice in correctness. The automated processing of as-built and as-planned data to produce the progress estimate took 12 seconds for the real world data, which was indeed faster than the current practice equivalent. Although the research objectives were met, there remains room for further improvement, particularly in regards to the solution’s robustness to occlusions on the monitored surfaces.

There is an increasing need to reduce energy consumption to tackle the adverse effects of climate change. The UK government has established numerous directives and policies to encourage carbon dioxide (CO2) emission and energy reduction within the non-domestic sector. However these measures are primarily focused towards reducing operational energy (i.e. energy used during building occupier activity), largely overlooking initial embodied energy. The trend towards reduced operational energy consumption due to energy efficient design is leading initial embodied energy to become a more significant part of project life cycle energy. Initial embodied energy relates to the energy use during the material, transportation and construction phases up to project practical completion, which is of keen interest to contractors due to their significant role in project procurement and delivery. Opportunities to address project life cycle energy are typically identified through a Life Cycle Assessment (LCA). However at present there is little validated data, no coherent method for data capture and limited incentive for project stakeholders to address initial embodied energy consumption. In response, this research project presents a contractor s practical approach towards assessing initial embodied energy consumption within UK non-domestic construction projects. An action research methodological approach enabled the assessment and potential reduction of initial embodied energy to be explored within a large principal contractor through five research cycles which included diagnosing and action planning, action taking, evaluating and specified learning. A comprehensive framework is designed to highlight the significance of initial embodied energy consumption relative to specific construction packages, activities and sub-contractors. This framework is then explored within three UK non-domestic construction projects (i.e. two industrial warehouses and one commercial office). Capturing information from live projects enables practical challenges and opportunities inherent when addressing initial embodied energy consumption to be identified. A series of contractor current practices are reviewed, and subsequently improved, to enhance their compliance with the framework requirements. The findings emphasise the importance of material phase impacts, especially construction packages which primarily contain steel and concrete-based materials (i.e. ground and upper floor, external slab and frame). The importance of project type, site area, building lifespan and waste consumption are also recognised to reduce initial embodied energy consumption. The framework provides a practical approach for initial embodied energy assessment which can readily be adopted to help highlight further opportunities to reduce energy consumption. The research project concludes by presenting a number of recommendations for consideration by the construction industry and associated stakeholders, along with requirements for future research.

This work describes selected the technical monuments in South Bohemia and the technical monuments are described in detail. This work technical monuments shows the basic technical functions and the use of known physical phenomena in their construction. These monuments are grouped into thematic groups with respect to mining, transporting and processing of raw materials. Selection specific monuments was carried out on the basis of their importance and uniqueness in the context of South Bohemia.

In order to investigate the etiology of and evaluate interventions for work-related back injuries, researchers need efficient, accurate occupational exposure assessment methods suitable for large samples. The chapters in this thesis examine critical decisions using electromyography (EMG): How should exposure be measured? For what duration? Who should be measured, and how many times? Low-back EMG, or muscle activity data, was collected during 138 full-shift field measurements over 30 different job titles at 50 different worksites in 5 heavy industries: forestry, transportation, wood products, construction, and warehousing. Observations and self-reports of posture, manual materials handling (MMH), and driving exposures were collected concurrently. 1) Variability of EMG calibration measurements was investigated on right/left sides, multiple trials, 4 positions, and pre/post-shift. Position accounts for the majority of explained variability; there is little to gain by measuring multiple trials or pre- and post-shift, but measuring both sides and multiple positions is worthwhile. 2) Observation and self-report data were easier to collect and cheaper than the EMG direct measure. Costs and successful field performance need to be weighed against the added data detail when making choices about exposure assessment techniques for epidemiological studies. 3) Observed and self-reported exposures were used to predict EMG exposure metrics using mixed multiple linear regression models. Regression models using observed variables predicted 43-50% of the variability in the EMG metrics, while self-reported variables predicted 21%-36%. The observation exposure model provides a low-cost alternative to direct measurement. The self-reported exposure model should be considered with more caution. 4) Full-shift EMG data was resampled for 4, 2, and 1 hour, and for 10 and 2 minute durations to determine the optimal sampling duration. Bias was consistently low, but shorter durations had higher absolute error, percentage error, and limits of agreement. Durations of 4 and 2 hours may be acceptable but those less than 1 hour had large errors. 5) Components of EMG variance were calculated between- and within-subject, and between- industry, company, job, and post hoc grouping. Resolution, contrast, and exposure-response relationship attenuation were calculated for each grouping scheme. The post hoc scheme had the highest contrast and lowest resolution.

In order to investigate the etiology of and evaluate interventions for work-related back injuries, researchers need efficient, accurate occupational exposure assessment methods suitable for large samples. The chapters in this thesis examine critical decisions using electromyography (EMG): How should exposure be measured? For what duration? Who should be measured, and how many times? Low-back EMG, or muscle activity data, was collected during 138 full-shift field measurements over 30 different job titles at 50 different worksites in 5 heavy industries: forestry, transportation, wood products, construction, and warehousing. Observations and self-reports of posture, manual materials handling (MMH), and driving exposures were collected concurrently. 1) Variability of EMG calibration measurements was investigated on right/left sides, multiple trials, 4 positions, and pre/post-shift. Position accounts for the majority of explained variability; there is little to gain by measuring multiple trials or pre- and post-shift, but measuring both sides and multiple positions is worthwhile. 2) Observation and self-report data were easier to collect and cheaper than the EMG direct measure. Costs and successful field performance need to be weighed against the added data detail when making choices about exposure assessment techniques for epidemiological studies. 3) Observed and self-reported exposures were used to predict EMG exposure metrics using mixed multiple linear regression models. Regression models using observed variables predicted 43-50% of the variability in the EMG metrics, while self-reported variables predicted 21%-36%. The observation exposure model provides a low-cost alternative to direct measurement. The self-reported exposure model should be considered with more caution. 4) Full-shift EMG data was resampled for 4, 2, and 1 hour, and for 10 and 2 minute durations to determine the optimal sampling duration. Bias was consistently low, but shorter durations had higher absolute error, percentage error, and limits of agreement. Durations of 4 and 2 hours may be acceptable but those less than 1 hour had large errors. 5) Components of EMG variance were calculated between- and within-subject, and between- industry, company, job, and post hoc grouping. Resolution, contrast, and exposure-response relationship attenuation were calculated for each grouping scheme. The post hoc scheme had the highest contrast and lowest resolution.

In order to investigate the etiology of and evaluate interventions for work-related back injuries, researchers need efficient, accurate occupational exposure assessment methods suitable for large samples. The chapters in this thesis examine critical decisions using electromyography (EMG): How should exposure be measured? For what duration? Who should be measured, and how many times? Low-back EMG, or muscle activity data, was collected during 138 full-shift field measurements over 30 different job titles at 50 different worksites in 5 heavy industries: forestry, transportation, wood products, construction, and warehousing. Observations and self-reports of posture, manual materials handling (MMH), and driving exposures were collected concurrently. 1) Variability of EMG calibration measurements was investigated on right/left sides, multiple trials, 4 positions, and pre/post-shift. Position accounts for the majority of explained variability; there is little to gain by measuring multiple trials or pre- and post-shift, but measuring both sides and multiple positions is worthwhile. 2) Observation and self-report data were easier to collect and cheaper than the EMG direct measure. Costs and successful field performance need to be weighed against the added data detail when making choices about exposure assessment techniques for epidemiological studies. 3) Observed and self-reported exposures were used to predict EMG exposure metrics using mixed multiple linear regression models. Regression models using observed variables predicted 43-50% of the variability in the EMG metrics, while self-reported variables predicted 21%-36%. The observation exposure model provides a low-cost alternative to direct measurement. The self-reported exposure model should be considered with more caution. 4) Full-shift EMG data was resampled for 4, 2, and 1 hour, and for 10 and 2 minute durations to determine the optimal sampling duration. Bias was consistently low, but shorter durations had higher absolute error, percentage error, and limits of agreement. Durations of 4 and 2 hours may be acceptable but those less than 1 hour had large errors. 5) Components of EMG variance were calculated between- and within-subject, and between- industry, company, job, and post hoc grouping. Resolution, contrast, and exposure-response relationship attenuation were calculated for each grouping scheme. The post hoc scheme had the highest contrast and lowest resolution. / Medicine, Faculty of / Population and Public Health (SPPH), School of / Graduate