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- Casas, Joan Ramon, et al.
(author)
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Guideline for Load and Resistance Assessment of Existing European Railway Bridges : Advices on the use of advanced methods
- 2007
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Reports (peer-reviewed)abstract
- The bridge assessment in many aspects is very similar to the bridge design. The same basic principles lie at the heart of the process. Nevertheless, an important difference lies in the fact that when a bridge is being designed, an element of conservatism is generally a good thing that can be achieved with very little additional costs. When a bridge is being assessed, it is important to avoid unnecessarily conservative measures because of the financial implications that may follow the decision of ratingthe bridge as deficient. Therefore, the design codes (e.g. EC codes) may not always be appropriate for assessment of existing bridges and some additional recommendations or guidelines are required that will lead to less conservative assessment of theirs load carrying capacity. Such guidelines have been already proposed for assessment of highway bridges in Europe. However, there is a lack of this type of documents that can be applied for the assessment of railway bridges.The present "Guideline for Load and Resistance Assessment of Existing European Railway Bridges - advices on the use of advanced methods" is providing guidance and recommendations for applying the most advanced and beneficial methods, models and tools for assessing the load carrying capacity of existing railway bridges. This includes systematized step-level assessment methodology, advanced safety formats (e.g. probabilistic or simplified probabilistic) refined structural analysis (e.g. non-linear or plastic, dynamic considering train-bridge interaction), better models of loads and resistance parameters (e.g. probabilistic and/or based on the results of measurements) and methods for incorporation of the results form monitoring and on-site testing (e.g. Bayesian updating).Basis for the "Guideline for Load and Resistance Assessment of Existing EuropeanRailway Bridges - advices on the use of advanced methods" is the research work carried out in the work package WP4 of the Sustainable Bridges project combined with the best practical experience and know-how of all the partners involved.The research activities within the work package WP4 have been carried out in the following five groups:− Loads and dynamic effects, with focus on train loads and dynamics (Deliverables D4.3, also referred as SB 4.3 Dynamic (2007), or just SB4.3 (2007));− Safety and probabilistic modelling (Deliverables D4.4, also referred as SB4.4Safety (2007), or just SB4.4 (2007));− Concrete bridges, with focus on non-linear analysis (Deliverables D4.5, also referred as SB4.5 Concrete (2007), or just SB4.5 (2007));− Metal bridges, with focus on riveted bridges (Deliverables D4.6, also referredas SB4.6 Metal (2007), or just SB4.6 (2007));− Masonry arch bridges including soil/structure interaction (Deliverables D4.7,also referred as SB4.7 Masonry (2007), or just SB4.7 (2007)).The results of these activities are reported in corresponding Background Documents (Deliverables) listed above within parenthesis.The main results from the research activities performed and the know-how of all the partners in the specific areas of bridge assessment are tried to be presented in this Sustainable Bridges SB-LRA 2007-11-30 6 (428) Guideline in such a way that the target reader of the Guideline, a structural engineer experienced in assessment of railway bridges, is able to apply them in the everyday practice, without necessity of searching for several specific scientific publications. Nevertheless, in some cases it has been necessary to refer to public available literature and Background Documents prepared in the Sustainable Bridges project.The present Guideline has been prepared aiming to follow somehow the structure of the EC codes and it is divided into 10 chapters and 12 Annexes concerning:− Assessment procedure (Chapter 2);− Requirements, safety formats and limit states (Chapter 3, Annexes 3.1-3.7);− Basic information for bridge assessment (Chapter 4);− Load and dynamic effects (Chapter 5, Annex 5.1);− Concrete bridges (Chapter 6);− Metal bridges (Chapter 7, Annex 7.1);− Masonry arch bridges (Chapter 8, Annexes 8.1 and 8.2);− Foundations and transition zones (Chapter 9);− Improvement of assessment using information from testing and monitoring (Chapter 10, Annex 10.1).In most of the topics related to railway bridges assessment the Guideline uses the current state-of-the-art knowledge and the presently best practice. Nevertheless, in many subjects it propose the use of original methods and models that have been developed, obtained or systematized due to research performed within one of the five groups of work package WP4.
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- Kamaluddin, Noor Azreena, et al.
(author)
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Self-reporting traffic crashes – a systematic literature review
- 2018
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In: European Transport Research Review. - : Springer Science and Business Media LLC. - 1867-0717 .- 1866-8887. ; 10:2
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Journal article (peer-reviewed)abstract
- Purpose: A traffic safety analysis that is based on registered crashes often suffers from underreporting, which may result in biased conclusions and lead to misguided crash-prevention strategies. Self-reporting traffic crashes is a complementary method to obtain crash information that is often not available in official databases. By surveying studies from around the world, this paper aims to map the current practices in the collection of data from self-reporting traffic crashes. Method: A systematic literature search was carried out in three databases, ScienceDirect, Scopus and Transport Research International Documentation (TRID), resulting in 134 reviewed studies. Results: Self-reported crash studies were found to be more common in Europe, North America and Australasia, but there are few studies in developing countries. The reviewed studies mostly focused on adult road users (i.e. legal age of obtaining driving license and with no upper limit) and car users. Questionnaires (either paper based or online) were the most often used method, and 1 year was the most common recall period used. Regardless of its drawbacks, the reviewed studies showed that researchers ‘trust’ self-reports. Conclusion: More studies should be conducted, especially targeting adolescent and young adults (age of 15–30 years) and vulnerable road users (VRUs). Developing countries should increase their efforts when it comes to using self-reporting to better assess the actual traffic safety situation and produce knowledge-based appropriate safety measures. Utilisation of smartphone application to assist data collection in self-reporting study for in-depth crash analysis should be explored further.
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- Wolever, Thomas M S, et al.
(author)
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Measuring the glycemic index of foods: interlaboratory study.
- 2008
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In: The American journal of clinical nutrition. - 0002-9165 .- 1938-3207. ; 87:1
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Journal article (peer-reviewed)abstract
- BACKGROUND: Many laboratories offer glycemic index (GI) services. OBJECTIVE: We assessed the performance of the method used to measure GI. DESIGN: The GI of cheese-puffs and fruit-leather (centrally provided) was measured in 28 laboratories (n=311 subjects) by using the FAO/WHO method. The laboratories reported the results of their calculations and sent the raw data for recalculation centrally. RESULTS: Values for the incremental area under the curve (AUC) reported by 54% of the laboratories differed from central calculations. Because of this and other differences in data analysis, 19% of reported food GI values differed by >5 units from those calculated centrally. GI values in individual subjects were unrelated to age, sex, ethnicity, body mass index, or AUC but were negatively related to within-individual variation (P=0.033) expressed as the CV of the AUC for repeated reference food tests (refCV). The between-laboratory GI values (mean+/-SD) for cheese-puffs and fruit-leather were 74.3+/-10.5 and 33.2+/-7.2, respectively. The mean laboratory GI was related to refCV (P=0.003) and the type of restrictions on alcohol consumption before the test (P=0.006, r2=0.509 for model). The within-laboratory SD of GI was related to refCV (P<0.001), the glucose analysis method (P=0.010), whether glucose measures were duplicated (P=0.008), and restrictions on dinner the night before (P=0.013, r2=0.810 for model). CONCLUSIONS: The between-laboratory SD of the GI values is approximately 9. Standardized data analysis and low within-subject variation (refCV<30%) are required for accuracy. The results suggest that common misconceptions exist about which factors do and do not need to be controlled to improve precision. Controlled studies and cost-benefit analyses are needed to optimize GI methodology. The trial was registered at clinicaltrials.gov as NCT00260858.
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