Pavement Engineering for Forest Roads: Development and Opportunities

Pavement is an essential component of roads as it carries the traffic and provides the required riding comfort. Considering that numerous forest roads are approaching their end of life, the critical issue is identifying the best rational pavement design methods to reengineer existing and build new pavement structures. The purpose of this contribution was (1) to review the big development lines of pavement systems, (2) to have a critical look at the pavement engineering framework, and (3) to bring selected empirical design equations into a comparable scheme. The study resulted in the following significant findings. First, the Trésaguet and McAdam pavement systems represented the state of the art from the beginning of a formal forest road engineering discipline at the beginning of the 19th century and remained for almost 150 years. Second, the emergence of soil mechanics as a scientific discipline in the 1920s resulted in the optimal grading of aggregates and improvement of soils and aggregates with binders, such as lime, cement, and bitumen. Third, the rational pavement design consists of five essential components: (1) bearing resistance of the subsoil, (2) bearing resistance of the pavement structure, (3) lifecycle traffic volume, (4) uncertainties that amplify deterioration, and (5) the limit state criterion, defining thresholds, above which structural safety and serviceability are no longer met. Fourth, rational, formal pavement design approaches used for forest roads were »downsized« from methodologies developed for high-volume roads, among which the approaches of the American Association of State Highway and Transportation Officials (AASHTO) and US Army Corps of Engineers (USACE) are of primary interest. Fifth, the conversion of the AASHTO ‘93 and USACE ‘70 methods into the SI system indicated that both equations are sensitive to soil bearing resistance, measured in California Bearing Ratio (CBR). However, there is a lack of validation for the AASHTO and USACE equations for forest road conditions. Consequently, a factorial observational study to gain a basis for validation should be developed and implemented. Additionally, the conversion of simple soil bearing resistance measures, such as CBR, into the resilient modulus will be improved

Quantitative Verification: Formal Guarantees for Timeliness, Reliability and Performance

Computerised systems appear in almost all aspects of our daily lives, often in safety-critical scenarios such as embedded control systems in cars and aircraft or medical devices such as pacemakers and sensors. We are thus increasingly reliant on these systems working correctly, despite often operating in unpredictable or unreliable environments. Designers of such devices need ways to guarantee that they will operate in a reliable and efficient manner. Quantitative verification is a technique for analysing quantitative aspects of a system's design, such as timeliness, reliability or performance. It applies formal methods, based on a rigorous analysis of a mathematical model of the system, to automatically prove certain precisely specified properties, e.g. ``the airbag will always deploy within 20 milliseconds after a crash'' or ``the probability of both sensors failing simultaneously is less than 0.001''. The ability to formally guarantee quantitative properties of this kind is beneficial across a wide range of application domains. For example, in safety-critical systems, it may be essential to establish credible bounds on the probability with which certain failures or combinations of failures can occur. In embedded control systems, it is often important to comply with strict constraints on timing or resources. More generally, being able to derive guarantees on precisely specified levels of performance or efficiency is a valuable tool in the design of, for example, wireless networking protocols, robotic systems or power management algorithms, to name but a few. This report gives a short introduction to quantitative verification, focusing in particular on a widely used technique called model checking, and its generalisation to the analysis of quantitative aspects of a system such as timing, probabilistic behaviour or resource usage. The intended audience is industrial designers and developers of systems such as those highlighted above who could benefit from the application of quantitative verification,but lack expertise in formal verification or modelling

Abstract State Machines 1988-1998: Commented ASM Bibliography

An annotated bibliography of papers which deal with or use Abstract State Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm

Requirements modelling and formal analysis using graph operations

The increasing complexity of enterprise systems requires a more advanced analysis of the representation of services expected than is currently possible. Consequently, the specification stage, which could be facilitated by formal verification, becomes very important to the system life-cycle. This paper presents a formal modelling approach, which may be used in order to better represent the reality of the system and to verify the awaited or existing system’s properties, taking into account the environmental characteristics. For that, we firstly propose a formalization process based upon properties specification, and secondly we use Conceptual Graphs operations to develop reasoning mechanisms of verifying requirements statements. The graphic visualization of these reasoning enables us to correctly capture the system specifications by making it easier to determine if desired properties hold. It is applied to the field of Enterprise modelling

UI-Design driven model-based testing

Testing interactive systems is notoriously difficult. Not only do we need to ensure that the functionality of the developed system is correct with respect to the requirements and specifications, we also need to ensure that the user interface to the system is correct (enables a user to access the functionality correctly) and is usable. These different requirements of interactive system testing are not easily combined within a single testing strategy. We investigate the use of models of interactive systems, which have been derived from design artefacts, as the basis for generating tests for an implemented system. We give a model-based method for testing interactive systems which has low overhead in terms of the models required and which enables testing of UI and system functionality from the perspective of user interaction

Workshop on Verification and Theorem Proving for Continuous Systems (NetCA Workshop 2005)

Oxford, UK, 26 August 200