Thesis--Auburn University, 2006. / Abstract. Vita. Includes bibliographic references (p.68-71).

Airport pavements and longitudinal elevation profiles, in conjunction with the aircraft, form a system where vertical displacements are produced that can compromise their performance. Rough pavements are generally responsible for the occurrence of dynamic responses such as vertical accelerations and pavement loads that affect the aircraft, increase stopping distance and difficult to read the cockpit instrumentation. To approach this problem, the International Roughness Index (IRI) and the Boeing Bump Index (BBI) are currently used to quantify airport pavement roughness and to identify sections that need maintenance and rehabilitation (M&R) activities. However, such indices were developed only based on the dynamic responses of an automobile at 80 km/h to the irregularities of road pavements, and from the physical characteristics of the irregularities, respectively, without considering the effect of the aircraft dynamic response. In addition, current critical limits for IRI and BBI can misjudge the real condition of the pavement. This research aims to evaluate the effect of airport pavement roughness on aircraft dynamic response in terms of vertical accelerations at the aircraft cockpit (VACP) and at the center of gravity (VACG), as well of dynamic loads at the nose, main and rear landing gear (NGPL, MGPL, and RGPL), which may compromise the aircraft safety and the pavement performance. The ProFAA software was used to compute both indices and to simulate the responses of 4 representative aircraft traversing 20 runway profiles at 10 operational speeds varying from 20 to 200 knots (37 to 370 km/h). Statistical comparisons and regression analyses between roughness indices and dynamic responses were carried out. Principal results indicated that VACP was 50% higher than VACG and that NGPL was approximately 80% higher than MGPL. In addition, it was observed that VACP exceeds 0.40 g when the IRI is higher than 3.7 m/km and that NGPL doubles the static load when the IRI is higher than 3.3 m/km. A case study presented to compare these limits shown that decision-making based on the dynamic response of the aircraft can bring significant differences in the number and quality of M&R activities. / Os pavimentos aeroportuários e os perfis de elevação longitudinal, em conjunto com as aeronaves, formam um sistema onde são produzidos deslocamentos verticais que podem comprometer seu desempenho. Pavimentos irregulares são geralmente responsáveis pela ocorrência de respostas dinâmicas como acelerações verticais e carregamentos no pavimento que podem danificar a aeronave, aumentar a distância de parada e dificultar a leitura dos instrumentos de navegação na cabine dos pilotos. Para abordar esse problema, os índices International Roughness Index (IRI) e Boeing Bump Index (BBI) são utilizados atualmente para quantificar a irregularidade longitudinal dos pavimentos aeroportuários e identificar seções que demandem atividades de manutenção e reabilitação (M&R). No entanto, tais índices foram desenvolvidos apenas com base nas respostas dinâmicas de um automóvel a 80 km/h às irregularidades dos pavimentos rodoviários e a partir das características físicas das irregularidades, respectivamente, sem considerar o efeito da resposta dinâmica das aeronaves. Ainda, os limites críticos atuais para IRI e BBI podem subestimar a condição real do pavimento. Esta pesquisa objetiva avaliar o efeito da irregularidade longitudinal na resposta dinâmica das aeronaves em termos de acelerações verticais na cabine dos pilotos (VACP) e no centro de gravidade (VACG) assim como os carregamentos no trem de pouso de nariz, principal e traseiro (NGPL, MGPL e RGPL, respectivamente), que podem comprometer a segurança das aeronaves e o desempenho do pavimento. O software ProFAA foi utilizado para calcular os dois índices e para simular as respostas de 4 aeronaves representativas operando 20 pistas de pouso e decolagem em 10 velocidades de operação variando de 20 a 200 nós (37 a 370 km/h). Comparações estatísticas e análises de regressão entre índices e respostas dinâmicas foram realizadas. Os principais resultados indicaram que VACP foi 50% maior do que VACG e que NGPL foi aproximadamente 80% maior do que MGPL. Além disso, observou-se que VACP ultrapassa 0,40 g quando o IRI está acima de 3,7 m/km e que NGPL dobra a carga estática quando o IRI está acima de 3,3 m/km. Um estudo de caso apresentado para comparar esses limites indicou que a tomada de decisão baseada na resposta dinâmica das aeronaves pode trazer diferenças significativas na quantidade e qualidade das atividades de M&R.

Devido à grande predominÃncia do modal de transporte rodoviÃrio no Brasil, se faz cada vez mais necessÃrio um controle sobre as aÃÃes de manutenÃÃo e de conservaÃÃo das rodovias. Para isso, muitos ÃrgÃos rodoviÃrios adotam modernos sistemas informatizados, que à o caso do DER/CE, que utiliza o SIGMA (Sistema Integrado de GestÃo da ManutenÃÃo). O sistema, atravÃs do subsistema SGP (Sistema de GerÃncia de Pavimentos), possui um vasto banco de dados relativos à condiÃÃo das rodovias, que à alimentado com dados provenientes de levantamentos de campo, que trazem, periodicamente, informaÃÃes atualizadas da condiÃÃo das rodovias estaduais. Estes dados sÃo adquiridos utilizando metodologias definidas pela equipe tÃcnica do DER/CE, baseadas em procedimentos normalizados, sendo os principais: o levantamento de irregularidade longitudinal (IRI) e o Levantamento Visual ContÃnuo (LVC). O primeiro avalia o conforto ao rolamento e o segundo registra os defeitos de superfÃcie das rodovias. Esta pesquisa apresenta uma anÃlise comparativa entre dados de LVC e de IRI, avaliando a evoluÃÃo das quantidades de defeitos e do IRI e as metodologias e os equipamentos envolvidos nos levantamentos. Apresenta, ainda, uma tentativa de compreensÃo da evoluÃÃo dos parÃmetros medidos pelo LVC ao longo de oito anos. Espera-se que, com a contribuiÃÃo desta pesquisa, as metodologias e os dados relativos à condiÃÃo das rodovias sejam analisados considerando as limitaÃÃes encontradas e que sejam sempre adotados o equipamento e o procedimento mais apropriados. / Due to the large predominance of the transportation by highways in Brazil, it is necessary to control the actions related to maintenance and conservation of the roads. With this purpose, institutions make use of modern computational systems, such as the DER/CE, which uses the ISMA (Integrated System of Maintenance Administration). The referred system, using the subsystem PMS (Pavement Management System), has a large database related to the roads condition, filled with data provided by surveys that bring periodically up to date information of the state roads. These data are acquired by using methodologies defined by the technical staff of the DER/CE, based on the following normalized procedures: Visual Continuous Survey (LVC) and International Roughness Index Survey (IRI). The first one evaluates the comfort of the traffic rolling and the second registers the surface distresses of the roads. This research presents a comparative analysis between LVC and IRI data, evaluating the evolution of the distresses and the methodologies and equipments involved in the procedures. It is expected that, with the contribution of this research, the methodologies and road related data be analyzed considering the limitations of the equipments and procedures.

Research was performed to analyze the performance of the crack, seat, and overlay (CS&O) roadway rehabilitation technique in the Central Coast and Northern regions of California. This technique was evaluated through literature review to determine the state of practice and their conclusions. California highway sections rehabilitated using CS&O were selected for evaluation based on age and location. Pavement distresses and traffic data for these sections were collected and analyzed. Prior to beginning analysis this data was checked for errors, outliers, and omissions. The analysis consisted of checking the data for correlations among distresses and regions. The focus of this research is to develop performance prediction models for pavement distresses in CS&O sections. Using data collected from Caltrans’ Pavement Condition Reporting Software, performance models were developed based on dependent (distress) variables: alligator cracking, transverse cracking, longitudinal cracking, and International Roughness Index (IRI). And independent (explanatory) variables: age, traffic in the form of equivalent single axle load (ESAL), thickness of hot mix asphalt (HMA), thickness of Portland Cement Concrete (PCC), and cumulative traffic in the form of cumulative ESAL. Prediction models were then analyzed for preciseness and sensitivity to the variables included in each model.

In the field of vehicle durability, many individuals are focusing on methods for better replicating the durability a user will experience throughout the typical design lifespan of a vehicle (e.g., 100,000 miles). To estimate user durability a means of understand the types of damaging events and driving styles of uses must be understood. The difficulty with accurately estimating customer usage is, firstly, there is a large pool of possible roads for a user to drive along, for example, there are over 4 million miles of public roads in the United States, alone [1]. In addition, while measurements of these surfaces could be collected it would be impractical for two reasons, the first is the financial and extreme time burden this would take. Second, when collecting measurements of a road surface only the current state of a road surface can be measured, thus as a road deteriorates or is repaved the measurements collected would no longer be an accurate representation of the road. It should be mentioned that even, if all of the road surfaces were measured performing simulation and analysis of all of these road surfaces would be computationally intensive. Instead, it would be beneficial if select events that account for a significant portion of the damage a vehicle experiences can be identified. These damaging events could then be used in more complex vehicle simulation models and as input and validation of proving ground and laboratory durability testing. The objective of this research is to provide a means for improved estimation of vehicle durability, specifically a means for identifying, characterizing, and grouping unique separable damaging events from a road profile measurement. In order to achieve this objective a measure that can be used to identify separate damaging events from a road profile is developed. This measure is defined as Localized Pseudo Damage (LPD), which identifies the amount of damage each individual road excitation makes to the total accumulated damage for a single load path in a vehicle system. LPD is defined as a damage density to minimize the effect of measurement spacing on the resulting metric. The developed LPD measure is causal in that the value of LPD at a location is not affected by any future locations. In addition, for a singular event (e.g., impulse or step) in the absences of other excitations, the LPD value at the singular event location is equivalent to the total pseudo damage divided by the step size at the location. Once a measure of pseudo damage density is known at multiple locations along a road profile for multiple load paths of interest, then separable damaging events can be identified. To identify separable damaging events the activity of the vehicle system must be considered because separate damaging events can only occur when a region of inactivity is present across all load paths. Subsequently, an optimization problem is formed to determine the optimal active regions to maintain. The cost function associated with the optimization problem is defined to minimize the cost (number of locations maintained in damaging events) and maximize the benefit (the amount of pseudo damage maintained). Lastly, a statistical test is developed to assess if separate damaging events can be considered to be from the same general class of events based on their damage characteristics. The developed assessment methods establish the similarity between two more separable damaging events based on application specific user defined inputs. In the development, two example similarity metrics are defined. The first similarity metric is in terms of distance and the second is in terms of likelihood (probability). The developed statistical analysis uses the current state-of-the-art in clustering algorithms to allow for multiple damaging events to be identified and grouped together. / Doctor of Philosophy / In the automotive field determining the level of damage a typical production vehicle experiences over its lifetime has always been a desirable criterion to identify. This criterion is commonly referred to as customer usage. By understanding the typical customer usage of a vehicle over the lifetime of a vehicle, automotive engineers are able to improve the design of vehicle components. The issue with defining customer usage is that there are millions of miles of roads that a customer can travel on and millions of customers that all have unique driving characteristics. While it is possible to collect measurements of these road surfaces to use in further vehicle simulations, it is not feasible both from a financial and time perspective. In addition, the simulation and analysis of all road surfaces would be computationally intensive. However, if select damaging events (regions of the road surface that excessively contribute to accumulated damage) are identified, then they can be used in more complex vehicle durability analyses with lower computational efforts. In conventional damage analysis a total amount of accumulated damage is established for a known road surface. The issue with defining damage this way is that unique events which likely contributed a large amount of the accumulated damage cannot be identified. The first objective of this research is to define damage as a function of the vehicle's location along a road surface. Then, unique and separable damaging events can be identified and separated from sections of the road that do not significantly contribute to the accumulated damage. After defining this measure, an optimization problem is developed to identify damaging events based on maximizing the benefit (amount of damage accounted for in damaging events) and minimizing the cost (amount of road surface retained). Unique and separable damaging events are identified by solving this optimization problem. While the optimization problem identifies unique, separable damaging events, it is likely that some damaging events contain similar characteristics to each other. When performing additional durability analysis, it would be beneficial to form connections between similar damaging events to allow for analysis to be performed based on groups of events. To identify damaging events with similar characteristics, a statistical analysis is developed as the last contribution of this work. By combining this analysis with current state-of-the-art clustering algorithms and user provided definitions based on applications, similar damaging events are able to be grouped together.

No description available.

Engineers of off-road equipment, on-road vehicles, pavement, and tires must assess the roughness of a terrain surface for the design of their products. The International Roughness Index (IRI), a standardized means of assessing longitudinal road roughness, quantifies roughness based on the average suspension travel for a particular vehicle at a prescribed speed. The Discrete Roughness Index (DRI) developed in this work address fundamental limitations of the IRI. Specifically, the DRI is calculated for each discretely measured location along a terrain surface and is applicable to vehicles traveling at varying speeds and using parameters other than the Golden Quarter-Car on which the IRI is based. The development of the DRI begins with a consistent discretization of the terrain surface, vehicle response, and the IRI. Next the Fractional Response Coefficient is developed, the properties of which are critical in the development of the DRI. The DRI is developed and its properties are discussed through theory and simulation of the ASTM E1926-08 profile. One important property of the average DRI is that it converges to the IRI as the distance between sampled points becomes smaller, for the particular case when the Golden Quarter-Car model is simulated at 80 kph. The DRI is not an alternative to the standard IRI, therefore, but a widely applicable roughness measure of which the standard IRI is a single specialized application. / Master of Science

Road damage identification is still largely based on visual inspection methods and profilometer data. Visual inspection methods heavily rely on expert knowledge which is often very subjective. They also result in traffic flow interference due to the need for redirection of traffic to alternative routes during inspection. In addition to this, accurate high-speed profilometers, such as scanning vehicles, are extremely expensive often requiring strong economic justifications for their acquisition. The low-cost profilometers are very slow, typically operating at or less than walking speeds, causing their use to be labour-intensive if applied to large networks.This study aims at developing a road damage identification methodology for both paved and unpaved roads based on modelling the road-vehicle interaction system with an artificial neural network. The artificial neural network is created and trained with vehicle acceleration data as inputs and road profiles as targets. Then the trained neural network is consequently used for reconstruction of road profiles upon simulating it with vertical vehicle accelerations. The simulation process is very fast and can often be completed in a very short time thus making it possible to implement the methodology in real-time. Three case studies were used to demonstrate the feasibility of the methodology and the results on field tests carried out on mine vehicles with crudely measured road profiles showed a majority of the tested roads were reconstructed to within a fitting accuracy of less than 40% at a correlation level of greater than 55% which in this study was found to be practically acceptable considering the limitations imposed by the sizes of the haul trucks and their tyres as well as the quality of the road profiles and lack of control in the vehicle operation. / Thesis (PhD)--University of Pretoria, 2015. / Mechanical and Aeronautical Engineering / Unrestricted

The subject of the master thesis is to verify the possibility of application of geodetic methods to determine longitudinal and transverse pavement surface roughnesses. Geodetic techniques are compared to techniques specified in ČSN 73 6175. Subject of testing is absolute and relative accuracy of altitude measurement and accuracy of roughness parameter determination. As a result, the graphic interpretation of these parameters and deviations from reference values are presented in the current document. Practical use of the surveying methods is evaluated based on the application of the above mentioned techniques and the results of accuracy analysis.

Road roughness is the primary source of vehicle vibrations. This thesis investigates model-based methods for estimating road roughness in terms of the International Roughness Index (IRI) by measuring the chassis vibrations of the vehicle. This can provide NIRA Dynamics AB with a cost-effective pavement monitoring solution. Initially, system identification is performed on a physical car to estimate model parameters that reflect reality. Subsequently, two model-based IRI estimation methods are developed. One method relies on a transfer function between vertical chassis vibrations and the IRI according to a quarter-car model. The second method aims first to estimate the longitudinal road profile using a Kalman filter, and then calculate the IRI values from the estimated profile. This method can be implemented computationally efficiently and also offers the possibility of estimating the IRI using lateral vibrations. Both methods are validated using real-world data, and their performance is similar when using vertical vibrations, with the IRI estimation error’s standard deviation being roughly 10% to 20% of the reference value. However, the results are considerably worse when the estimation is purely based on lateral vibrations, indicating that lateral vibrations are not feasible for model-based IRI estimation, and the reasons for this are discussed.