Low-noise pavements are used as an effective method of traffic noise mitigation. Low-noise pavements reduce the noise that arises due to interactions between tires and road surfaces (tire/road) via the implementation of three main components: low pavement roughness, negative pavement texture, and a high pavement air-void content. The tire/road noise reduction capabilities of the wearing layer vary depending on the aggregate type, gradation, bitumen and air-void content, and density. Consequently, the demand for an accurate tire/road noise prediction model has arisen from the design of asphalt mixtures. This paper deals with how asphalt mixture components of the wearing layer influence tire/pavement noise reduction and presents a model for tire/road noise level prediction based on the asphalt mixture composition. The paper demonstrates that the noise reduction level of low-noise asphalt pavements is dependent on the composition of the asphalt mixture. Asphalt wearing layer mixture composition parameters were tested in the laboratory from cores taken from 18 road sections, where acoustic properties were measured using a close-proximity (CPX) method. The proposed linear model is based on the bitumen amount, the air-void content of the mixture and aggregate shape and involves materials that comply with the general requirements for high-quality asphalt mixtures. The model allows for the prediction of the tire/road noise level at the asphalt mixture design stage using asphalt mixture components and volumetric properties. The proposed model is the first stage in the building of a complex model with a much wider range of low-noise asphalts components, pavement profile depth and CPX-value relationships.

The authors of the present work offer the developed model of suggesting solutions to structural, technological and safety problems based on the use of a tree diagram as a tool for decision analysis and visualization. The model is aimed at integrating solutions worked out in the considered areas into a single variant as a research object. A multi-stage decision model reflecting a set of the available combinations of alternatives is developed. The branches of the tree diagram are interlinked based on the inherent relations between building structures, technologies and work safety. The interaction and interrelationship between the criteria describing the above issues affect each criterion in a very specific way. The performance of the system allows the authors to evaluate the effect of each criterion and its interaction with other criteria, which in turn helps with choosing appropriate solutions to solving structural, technological and safety problems.

Surveying the condition of the pavement is one of the most important processes in managing the road network. The information collected during these surveys allows for the calculation of the Pavement Condition Index, which is a derivative cumulative qualitative indicator that evaluates various pavement characteristics and defects. Deterioration modelling of these measured indicators and calculated indices is a critical element and its most accurate prediction brings the process of pavement management closer to a higher quality process by more efficiently allocating funds and repair work. Many different models – both extremely complex and simple – are used in the world to simulate the condition of individual pavement indicators. However, these models are developed based on the data of a certain country or region and are not suitable in another country due to different requirements for pavement structures and other reasons. In Lithuania, measurements of the quality indicators of road surfaces with new generation survey equipment have been carried out recently but the information stored in the databases about road sections is minimal, and it becomes difficult to adapt the models applied abroad due to the missing information. The aim of this study is to create pavement condition index prediction models by evaluating such quantitative and qualitative indicators as traffic loads, road surface unevenness, type of repair, pavement age, climatic zones, and pavement construction classes.

The performance and bearing capacity of the flexible pavement structure is ensured by providing necessary foundation comprised of unbound granular material (UGM) layers and subgrade. Whin this paper the compaction level parameters and deformation modulus relations determined for UGM layers and subgrade in construction site. The experimental data were tested applied standardized and improved test methods, such as an alternative falling weight deflectometer (FWD) test method with repetitive load, the plate load tester, lightweight deflectometer, dynamic cone penetrometer, and density Proctor tests. The data were analyzed based on statistical comparison of the compaction parameters, pairwise multiple comparison of test methods, clustering procedure for setting a level of compaction evidence and variance determination. Results proved capabilities of the alternative FWD test method under repetitive load to assess the relative compactness rate and the resilient responses, and provided the regression models of the dynamic modulus of the UGM layers and subgrade.

Daugiakriteriams sprendimo priėmimo uždaviniams spręsti taikant kiekybinius daugiatikslius sprendimo priėmimo metodus, dažniausiai neatsižvelgiama į galimas pradinių duomenų – rodiklių reikšmių paklaidas. Todėl neaišku, ar gautas sprendimas (alternatyvų išrikiavimas pagal racionalumą) nesikeis, jeigu keistųsi rodiklių reikšmės (± n %, n< 50 %). Šiame straipsnyje, taikant Monte Karlo modeliavimą, atliekama kiekybinių daugiatikslių sprendimo priėmimo metodų – TOPISIS, SAW ir COPRAS – jautrumo analizė. Jautrumo analizės pagrindas yra rodiklių reikšmių pasiskirstymas. Darbo tikslas – sukurti jautrumo analizės modelį, kuriuo būtų galima nustatyti daugiatikslių metodų jautrumą rodiklių reikšmių pasiskirstymo dėsnio atžvilgiu ir įvertinti šiais metodais gauto sprendimo patikimumą. Pateikto jautrumo analizės modelio etapai: 1) rodiklių pseudoatsitiktinių reikšmių generavimas pagal tolygųjį ir normalųjį dėsnius; 2) alternatyvų racionalumų vertinimas nagrinėjamais metodais, naudojant generuotas sprendimų matricas; 3) metodų jautrumo ir gauto sprendimo patikimumo vertinimas. Modeliuojant sprendimo paramos sistemas, atliekant skaičiavimus sprendimo priėmimo metodais, rekomenduojama atsižvelgti į planuojamų taikyti metodų jautrumą, kad padidėtų sprendimo patikimumas.The Sensitivity Analysis of the Multiattribute Decision Making Methods by Monte Carlo SimulationRūta Simanavičienė, Leonas Ustinovičius SummaryThe quantitative multicriteria decision making methods are used for decision making, but the biases of the values of the attributes are ignored often. Therefore it is not clear, if the final decision were changed, when changing the values of attributes. There are scientific research papers intended for the sensitivity analysis of multicriteria decisions, according to the significances of attributes. This paper analyses the sensitivity of quantitative multiattribute decision making TOPSIS – Technique for Order Preference by Similarity to Ideal Solution, SAW – Simple Additive Weighting, COPRAS – COmplex PRoportional ASsessment methods, according to attribute distribution. On this basis of Monte Carlo modeling (simulation) the generation of pseudorandom attribute values is being made, according to uniform and normal distribution. Using generated data the efficiency of alternatives is carried out by the above methods. As a result the sensitivity of the methods and the reliability of final decision are presented. When multiattribute decision making methods are used on the modeling decision support systems it is recommended to consider the sensitivity of these methods.

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