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IEEE Int. An efficient multiple hypothesis filter for bearing-only SLAM. Inverse depth parametrization for monocular SLAM. Iterated filters for bearing-only slam. Mapping large loops with a single hand-held camera. On the use of inverse scaling in monocular slam. In IEEE. International Conference on Robotics and Automation, An atlas framework for scalable mapping. Robotics and Automation, pp. Consistent, convergent and constant time SLAM.

In Int. Joint Conf. Artificial Intelligence, Acapulco, Mexico, August Accepted in Transactions on Robotics in Print , 24 5 , October Accepted in Transactions on Robotics in print. Unified inverse depth parametrization for monocular SLAM. Dr Est. Avanzada, arlopezm ipn. The combinatorial process was implemented in a test lab using Mexican crude oil samples.

The results were encouraging show that microwave heating and gravity sedimentation are alternatives for the separation of Mexican Oil emulsions. Keyword: Microwave heating, Demulsification, Separation, Water-in-oil emulsions. Water and oil sometimes combine emulsify during industrial processes. An oil-in-water emulsion has water as the continuous phase, while the water-in-oil emulsion has oil in the continuous phase. Either type of emulsion may contain other contaminating materials solids, dirt, metal particles, emulsifiers, cleaners, soaps, Dyna, year 81, no.

Emulsions can be found in a variety of industries and formed by a variety of processes. Since formation of emulsions is so specific to the industry and process, the emulsion breaking product selection is somewhat difficult and requires bench testing [2].

For water-in-oil emulsions which usually have high viscosity, the required mixing of these chemicals with the emulsion is difficult. Also when a high dosage of chemicals is used to overcome the difficulty, it leads to a secondary pollutant, since the separated water may contain too high a level of chemicals to be discharged to public water. The concept of microwave heating of emulsion was first introduced by Klaila [3] and Wolf [4] in their patent applications.

Recently, research continues. Today the Mexican oil fields have a high content of water and oil, and the water usually contains dissolved salts forming brines. A graphic user interface GUI was designed to visualize the temperature inside the sample to be irradiated with microwaves in real time see Figure 2. The use of microwaves is an alternative, effective, clean and chemicals free method for oil desalting and dehydration.

This publication shows that microwaves are an efficient alternative to heating oil emulsions. The variables studied are the temperature and the irradiation time during microwave irradiation. Equipment was built to irradiate emulsions and measure the temperature at a predetermined time.

Modules were designed for measuring the temperature and controlling the magnetron. Magnetron Control Module The magnetron operates at a working frequency of 2. The control module magnetron has a graphical interface which controls the magnetron, the duration of microwave irradiation and emergency protections see Figure 2,3.

Which can measure temperature in real time while the samples are being irradiated. Modules magnetron and temperature control. Figure 1. Infrared Sensor. Figure 4. Injection plant, Tamaulipas-Constituciones field. Each sample contained 50 ml. Although at 25 seconds there is a sudden temperature increase associated with interaction between microwaves and chemical properties of oil, as shown in Figure 12 FTIR. Comparison Chart irradiated samples. The main functional groups of absorption resins and asphaltenes are qualitatively identical.

To facilitate the study of the results of this analysis, the spectrum is divided into four regions that can be interpreted as follows:. Group III: dubbing vibrations out of the plane. Valence vibrations low energy region between cm Group IV: Region valence vibrations of single and double bonds very strongly coupled, a region is observed in the range of cm-1 band as a matter of oxygen valency vibrations.

This may also relate to an increase in the degree of hydrogen substitution in aromatic structures. This is attributed to the recovery of polar compounds solubilized in the added water, such as alcohols, esters, acids and acid anhydride. Group I: hydrogen valence vibrations small in the region of cm Group II: Vibrations valence double or partially double bonds, this region. Using the temperature module with the infrared sensor the temperature could be measured in real time, without the need to enter any sensor within the sample, as this would contaminate the oil sample or damage the sensor.

Using this module the signal representative of. The crude oil, after being irradiated with microwaves, qualitatively retains the functional groups that it is compose of, there are only quantitative changes that are assumed to be due to the recovery of soluble compounds in injection water. Asphaltenes, the main emulsion stabilizers present in the injection water are recovered.

Microwave radiation, breaks the film of surfactant present in the water. The spectra show that the time corresponding to 30 seconds irradiation, gave better results recovery of dissolved hydrocarbons Figure Establishing the. Emulsion Stability and Microwave Demulsification of Crude Oil Emulsion: Emulsion characterization, mechanisms of microwave heating technology, chemical demulsification, Lambert Academic Publishing, , p.

The Nalco Water Handbook, , p. Patent 4,, Patent 7,, B2. The parameters for a given material are estimated by the repeated numerical solutions of the IBVP direct problem under systematic variation of the model parameters, with the aim of successively minimizing a cost functional that measures the distance between a space-dependent observation and the corresponding numerical solution.

Two important features of this paper are the following. In the first place, the method proposed for the efficient and accurate numerical solution of the direct problem. We implement a wellknown explicit, monotone three-point finite difference scheme enhanced by discrete mollification.

The mollified scheme occupies a larger stencil but converges under a less restrictive CFL condition, which allows the use of a larger time step. The second feature is the thorough sensitivity and stability analysis of the parametric model functions that play the roles of initial guess and observation data, respectively. Keywords: Sedimentation of suspensions, sensitivity analysis, degenerate parabolic equation, parameter estimation, discrete mollification.

Scope Our goal is the numerical identification of unknown parameters in the flux and diffusion terms for the following initial-boundary value problem IBVP for a strongly degenerate parabolic equation in one space dimension: Dyna, year 81, no. The diffusion function a is assumed to be integrable and is allowed to vanish on u-intervals of positive length, on which 1a turns into a first-order hyperbolic conservation law, so that 1a is a strongly degenerate parabolic.

On the other hand, we assume that f is piecewise smooth and Lipschitz continuous. We focus our attention on Equation 1 as a model of the sedimentation-consolidation process of a solid-liquid suspension [8].

For the definition, existence and uniqueness of entropy solutions of 1 we refer to [7, 8, 10]. In the present work we are interested in a stability and sensitivity analysis of the parametric model functions. In order to perform the tests, we first proceed with a numerical estimation procedure based on repeated numerical solutions of the direct problem 1 under successive variation of parameters appearing in the coefficient functions f and a. In this phase the main components are the efficient and stable solver of the direct problem and the optimization procedure based on the Nelder- Mead Simplex Method.

Our goal is the stability and sensitivity analysis of the resulting inverse problem. Theoretical aspects related to identifiability are not our concern in this paper but cf. By sensitivity analysis we mean an intensive set of tests for the numerical identification of parameters with or without noisy observation data. Our approach follows the methodology of [4] but we acknowledge the existence of other ways to perform a sensitivity analysis, for instance [19].

Related work and outline of the paper The discrete mollification method is a convolutionbased filtering procedure suitable for the regularization of ill-posed problems and for the stabilization of. For the numerical identification of diffusion coefficients by discrete mollification, see [16] and its references. Inverse problems for strongly degenerate parabolic equations are of particular interest in the context of the sedimentation-consolidation model. In fact, in applications such as wastewater treatment and mineral processing, the reliable extraction of material-specific parameters appearing in the model functions f and a from laboratory experiments allows the operation and control of continuous clarifier-thickeners handling the same material to be simulated [10, 21].

In the presence of sediment compressibility, closed-form solutions are not available and one has to resort to numerical techniques to solve the parameter identification problem [5, 11]. The paper is organized as follows. Section 2 presents the sedimentation-consolidation model along with details on the schemes for the solution of the direct problem, including a brief description of the mollification method. Section 3 deals with the parameter identification problem, the proposed algorithm, the sensitivity analysis and the effect of noisy observation data.

This section ends with some conclusions. The material specific function f describes the effect of hindered settling. Details can be found in [1, 2, 3, 16, 20]. We solve 1 numerically using two convergent finite difference methods. Scheme 5 is monotone and convergent under the CFL condition. The second finite difference method is the mollified scheme [2], which is also monotone and convergent and takes the form.

The parameter dependent cost function is. See [2] for more details on this scheme. Since the functions f and a depend on a vector of parameters, the inverse problem corresponds to the following parameter identification problem:. There are many options for the numerical implementation of the optimization procedure. We selected a globalized bounded Nelder-Mead Method with restarts MATLAB function fminsearch, see [15] for details , which is a major improvement over the basic simplex method.

The strategy is described by the following algorithm. Step 3 End. Numerical examples The reference solution is generated by the corresponding numerical scheme 5 or 7 on a very fine grid. Our experiments include clean and noisy observation data. Example 1: Sensitivity to mollification parameters. The results are summarized in Table 2.

Example 2: Sensitivity to initial guess. We randomly generate initial guesses and carry out the identification task. The results are indicated in Table 3. Figure 2. Example 3: Effect of noisy observation data. We randomly generate final profiles and associate them to the previously generated initial guesses. The corrupted profile is generated as follows:. The results are in Table 4. Table 1. Example 1: initial guesses used for identification experiments. Table 2. Table 3.

Table 4. The results in Table 3, corresponding to Example 2, illustrate how by improving the spatial resolution i. Table 4 indicates that the level of noise influences the quality of the recovery but stability is never lost.

Summarizing, this parameter identification procedure yields good results for both the basic scheme and its mollified versions but the mollified approach returned advantages not only in CPU time in s , but also in the error level, the sensitivity to the initial guess and the effect of noise in the data. This well-posed behavior was already suggested by the convex-shape of the cost functional Figure 3.

RB acknowledges support by. Difference schemes stabilized by discrete mollification for degenerate parabolic equations in two space dimensions. IMA J. Monotone difference schemes stabilized by discrete mollification for strongly degenerate parabolic equations. Partial Diff. Stabilization of explicit methods for convection-diffusion problems by discrete mollification.

Centrifugal settling of flocculated suspensions: a sensitivity analysis of parametric model functions. Drying Technology, pp. Numerical solution of an inverse problem for a scalar conservation law modelling sedimentation. In: Tadmor, E. Proceedings of Symposia in Applied. Mathematics, vol. Convexity-preserving flux identification for scalar conservation laws modelling sedimentation.

Inverse Problems 29 paper 30pp. Closed-form solutions for batch settling height from model settling flux functions. Evje, S. On strongly degenerate convection-diffusion problems modeling sedimentation-consolidation processes. On some upwind schemes for the phenomenological sedimentation-consolidation model. On a diffusively corrected kinematic-wave traffic model with changing road surface conditions.

Models Methods Appl. A mathematical model of continuous sedimentation of flocculated suspensions in clarifier-thickener units. SIAM J. Numerical identification of parameters for a model of sedimentation processes. Inverse Problems, pp. One-sided difference approximations for nonlinear conservation laws. Monotone difference approximations of BV solutions to degenerate convection-. Globalized Nelder— Mead method for engineering optimization.

Computers and Structures, pp. Numerical identification of a nonlinear diffusion coefficient by discrete mollification. John Wiley, New York, Mollification and space marching. In: K. Woodbury ed. Sensitivity analysis of differential-algebraic equations and partial differential equations. Computers and Chemical Engineering pp. Multiscale analysis by means of discrete mollification for ECG noise reduction. DYNA pp. Parameter estimation protocol for secondary clarifier models based on sludge volume index and operational parameters.

ICT have become a key element for business development and the improvement of activities in all departments. Those techniques have resulted in the emergence of technological challenges such as interoperability between different systems in order to exchange and coordinate information.

In this context, the application of business process modelling is a crucial methodology to understand and implement those maintenance techniques. In this paper, we use business process modelling approach to design a system architecture that integrates CMMS, CBM and e-maintenance methods, tools, and processes.

At that time computer systems were limited to performing only certain scheduling tasks for preventive actions [3]. Over time, several technologies have been evolving and with them, the integration of maintenance systems. A CMMS is a software tool for maintenance management that incorporates open access to information that facilitates the decision making process regarding maintenance activities [4]. CBM is a technique used to monitor machines for the purpose of diagnostics and prognostics [5].

E-maintenance is the set of maintenance processes that uses the e-technologies to Dyna, year 81, no. The implementation of these techniques, tools and processes on the shop floor is not a trivial issue. Overall, integrating them into a single software platform is the most challenging concern. Therefore several academics and professionals underline the need for a structured approach to support their actual implementation, use, and integration [7, 8].

In this paper we use business process modelling to develop such a structured approach. Secondly, we use the Unified Modelling Language UML to represent the principal objects constituting the e-maintenance platform, their relations and static operation structure. Finally, the variety of technologies related to the proposed platform, implies the existence of multiple communication protocols, data connections, configurations, etc. Section 3 contains a literature review and problem statement.

Section 4 briefly introduces the business process modelling techniques we use in this paper. Finally, Section 6 provides conclusions and future directions. CMMS The main objective of a CMMS is to provide a tool to analyze maintenance and equipment information in order to optimize the management and support for strategic, tactical and operational decisions.

An important requirement for these systems is the compatibility and integration with other systems that contains organizational information. Fumagalli et al. CMMS allows access to information that can be used to prioritize actions and make better decisions in maintenance activities.

The CMMS can also provide adequate control of the system. CBM CBM is defined as the preventive maintenance based on monitoring the operation, the parameters of the element, and the subsequently executed actions [12]. Monitoring is the manual or automatic task of observing the current state and behaviour of a given shop floor element commonly the thermal and vibratory behaviour [13].

The final goal of the monitoring task is to adopt a condition-based maintenance approach in order to reduce the probability of failure and prevent irreversible damage to the equipment. CBM allows maximizing the service life of equipment and its components, anticipating failures by monitoring significant parameters.

For these reasons, CBM is a key component of proactive maintenance. In recent years, both the reduction of the price of sensors and the increase of information processing capacity have enhanced the development of automatic diagnostic tools. In this context, one of the most widespread applications is the e-CBM, as it is technically feasible, economically viable, and offers many benefits. E-Maintenance Although the term e-Maintenance has been used since as a component of eManufacturing, at the present time there is not yet a standardized definition of eMaintenance given by an official institution.

Those maintenance processes and methods required to operate them technologies, procedures, standards,. This means that, for different organizations, e-Maintenance could involve different spheres of activities. Frequently, these activities include: e-monitoring, e-prognosis, e-diagnosis, e-management, e-service, remote maintenance and, collaborative maintenance. Such activities are supported by means of a variety of hardware and software technologies such as wireless and mobile devices, embedded systems, web based applications, P2P networks, multiagent applications, specific software architectures, communication protocols, among others.

To this aim, we adopt a business process modelling approach and more specifically we use a BPMN a standard for business process modelling to design the process of integration of the CMMS, CBM and E-Maintenance components; b the UML class diagram a standard for software system design to design the main software components of the e-maintenance platform and their relationships; c MIMOSA for standardizing the interoperability of the platform.

In the next section we give a brief overview of the business process modelling languages and standards. We performed a literature review to recognise similar previous attempts at integration of CMMS, CBM and e-maintenance on a single system. Specifically, we found 10 studies focused on these issues. A list of these papers is reported in Table 1. In this Table we also reported a summary of the specific problem they deal with and the approach and methodology they use to solve that problem.

Although the referred papers focus on CMMS, CBM, e-maintenance, none of those works clearly propose a structured approach to integrate all of these tools and techniques in a unique platform. From then on, business process modelling has been used in industry to obtain a global vision of processes by means of support, control and monitoring activities [17], to facilitate the comprehension of the business key mechanisms, to be a base for the creation of appropriate information systems [18], to improve the business structure and operations, etc.

Business process modelling, means the use of methods, techniques and software to design, control and analyze operational processes involving humans, organizations, applications, documents and other sources of information [15].

Developing of a complete solution package for Integrated Diagnostics ID It includes some reliability equations. One of its key requirements to enable CBM is the ability to track machinery performance and diagnose machinery health. This paper reviews the philosophies and techniques that focus on improving reliability and reducing unscheduled downtime by monitoring and predicting machine health. It proposes the use of qualitative information, extracted from failure mode and effects analysis FMEA or fault tree analysis FTA into a quantitative analysis that generates diagnostic recommendations.

NET platform. This paper shows that the integration method for CBM is feasible through a demo program. It shows the main elements to perform complex diagnostic analysis in a transformer system. This paper presents a management system for monitoring and diagnosis. A reliability-centered analysis is presented that defines the method to correctly select the CBM as a technically and economically viable maintenance solution. This paper proposes a diagram to decide whether or not to implement CBM.

It does not integrate CMMS. In this paper, a framework is proposed to reduce the development complexity of CBM systems, enabling CBM modules independently constructed and dynamically integrated. Maintenance chain integration using Petrinet enabled multiagent system modeling and implementation approach.

This research proposes a collaborative environment integrated by a service center of diagnosis, prognosis, and asset operations. To realize the automation of communication and negotiation, multi-agent systems, Petri-net modeling and UML are applied. It presents a conceptual framework for e-operations with the capability of e-maintenance, integrating e-diagnostic, among other processes.

UML is used as the tool to accomplish the object-oriented analysis and to design the system. Process modelling is the subject of interest in many different fields, such as the managerial area [30] and software engineering. This is due to the fact that it does not only describe processes, but in addition it represents a preparatory stage for the improvement of business processes, process reengineering, technological transference and processes standardization [31].

There are several standards for business process modelling. Among other advantages of using BPMN and UML, the easy translation of their models into software code is probably the factor most responsible for their diffusion. This architecture show a maintenance system that combines the registers of CMMS with the information provided by sensors, providing a data model to allow the development of a system that combines the features of CMMS and CBM in an e-maintenance platform.

In the next subsections we present the main e-maintenance process and the data model for the integration platform. E-maintenance process The general operation of the proposed system integration is shown in Figure 1. The tangible output documents are indicated by using the artifact notation.

As already mentioned, the third element constituting the e-maintenance integrated platform is the e-maintenance process itself. Indeed, although e-maintenance can be viewed as a technique or set of techniques , the general idea of our approach is to consider e-maintenance as the whole process of integrating all the maintenance components and elements. In accordance with [33] we consider e-maintenance a philosophy supporting the operation of the entire system and making information exchange possible among remote elements.

This is why, there is no pool in the BPMN diagram representing this component, but, instead, it is represented by the flow of activities and. Data model Figure 2 is a UML class diagram that shows the main software components, their relationships, and the exchanged information. On the contrary, NEW attributes are newly defined and have been added only when necessary. Analogously, we omitted from the model those attributes of the MIMOSA specification that are not useful in the scope of this work.

For this. A short description now follows in order to help the reader navigate the model. Alert represents an alarm. Here a simplification and synthesis is adopted. EventHistory is a new class introduced to describe the information that is normally stored in a CMMS as records of events happened in the past like failures, preventive maintenance tasks, etc.

More in-depth, an item can have more than one MeasLoc measurement location , i. The main idea behind this concept is that common sensors are generally related to an IP. This IP could be the IP of the controller that connects more than one sensor and it is wired to them. There could be also a field-bus to which all the sensors are connected. In these two cases a sub-IP for each sensor can be identified.

Moreover, due to new development of smart-sensors [34] it could be envisioned that each sensor is connected to the overall network through its own IP identifier. Following the chain of activities, the MeasLoc is then related with one data event, namely a signal. It is in fact established that a MeasLoc sensor can provide only one DataEvent so the relationship is one to one. If the reader. More precisely, in this project the MeasLoc is the soft entity used to identify the transducer in the scope of the integrated system.

More than one DataEvent can then be related to an AlertRegion. This defines the boundaries upper and lower levels in which a signal is considered normal; out of these bounds something wrong is occurring. One AlertRegion can then provide one or more Alerts. Following the described chain of relations we can state that one Item. However, we should map one Alert to failure modes to be sure that the system can then properly work, in order to provide information about a specific failure coming from an Alert.

This describes all the related events stored in the CMMS data base. One or more failure modes are then associated with a Function and an Item can have one or more functions. To be able to identify one single failure mode by an Alert enough information must be collected. It often happens that one alert is associated with multiple failure modes. So, in order to directly connect one alert to a specific failure mode, one solution is that there are enough monitored variables to assign one alert to each failure mode.

In this way, the user is able to connect an Alert with each single failure mode, i. Besides mapping failure modes to alerts, the user could also be called to connect each failure mode the HypotheticalEvent in the UML model with records that represent events that occurred in the real system, related to the failure mode, either as a failure or as a preventive maintenance task planned to avoid the failure this is the EventHistory in the UML model. When this last relation has been set up, the CMMS database can update in real time the occurrence of an event in the HypotheticalEvent and EventHistory classes.

More specifically, we show how business process modelling facilitates the process of implementing a system that integrates CMMS, CBM and e-maintenance. A BPMN model was applied to represent the whole process of integration. A UML Class diagram was adopted to show the main elements and relations of the e-maintenance integrated platform. Both researchers and professionals are expected to benefit from the presented research.

Researchers can keep exploring different business process modelling. However, the presented research has a strong practical vein. The proposed framework provides practitioners with a methodological approach that concretely support them in developing, implementing and integrating e-maintenance tools.

Future developments of this work should consider the validation of the model proposed by means of representative case studies. Mechanical Systems and Signal Processing, 14 4 , pp. Quality and Reliability Engineering Int, 27 6 , pp.

La Diega, S. International Journal of Production Research, vol 44, no. Disponible en: wwwibm. VV, Predonzani, P. Systems Modeling for Business Process Improvement. Artech House, London, pp. Annual Reviews in Control, 33, pp. Candidate, Dept. Each section is classified as excellent, good, fair, or poor based on the normalized deflections obtained from FWD tests, spreadability, load transfer, and joint support ratio parameters.

The overall performance of the analyzed sections is from good to excellent. The field testing methodology along with the performance data analyses presented in this publication are a valuable tool to evaluate the actual structural condition of pavements and as a result short or medium term rehabilitation programs can be issued to ensure the serviceability of the pavement.

Due to its stiffness and structure, the traffic load applied to the PCC pavement layer is transmitted under a wider area of subgrade, inducing a moderate stress and strain to the soil [1]. JRCP is not as common as the JPCP and the only difference is that the former consists of slabs with transversal joints at intervals of up to 50 ft.

CRCP does not require transversal joints because is reinforced entirely over its length with longitudinal and transverse steel bars to prevent cracking due to variability in environmental conditions and traffic loading. There are several parameters involved in the PCC pavement performance, load transfer being the most.

Load transfer is the ability of the slab to transmit the load to the adjacent slab through the joint to decrease the acting stresses and thus improve the pavement performance. Two of the most common mechanisms used to increase joint efficiency are dowel bars and aggregate interlock. Dowel bars have proved to effectively improve joint performance.

Their main advantage is to allow slab movement in the horizontal direction and restrict the movement in the vertical direction while transferring the load. The dowel bars have a diameter between 32 and 38 mm, a length of mm and are normally spaced mm from each other. The dowel bars also limit the most common distress mechanisms in PCC pavement such as faulting, pumping, and corner break. The total load transfer between slab sections is due to the contribution of both the aggregate interlock and the dowel bars.

However, the contribution due to the aggregate interlock can be considered negligible in cracks wider than 0. A study of the most significant design and construction parameters affecting long-term pavement performance of Although some of the sections were exposed to extreme weather and traffic conditions, they had excellent performance during their design life. The study was conducted by analyzing data from field surveys collected since The database included a variety of information for each one of the pavements such as: section location, slab thickness, steel reinforcement content, base type and thickness, average annual temperature and precipitation.

From this study, it was found that among the parameters affecting the CRCP, the reinforcement content and the slab thickness had the most critical influence on the pavement performance. In a different study [4], the performance of transverse cracking on forty-nine JPCP sections located in the State of Michigan was presented. The purpose of this project was to determine the key parameters influencing the transverse cracking in JPCPs and the conclusions are as follows: a the average number of cracks per slab increases as the joint spacing increases; b the type of coarse aggregate of the concrete mix has a significant influence in the number of transverse cracks developed in the slabs; c joint performance is directly related to temperature i.

The causes leading to surface longitudinal cracking and punch-outs on IH Interstate Highway in the State of Texas are presented in Chen et al. Several field and laboratory tests were conducted to determine the causes of distress mechanisms. An evaluation of the performance of unbounded JRCP overlays used over existing concrete pavements is presented in Padilla-Llano [6].

Results from this investigation showed that environmental effects are more critical to the pavement than the effect of the traffic load. The strains induced to the pavement by the change in the environment are much greater than the strains induced during the FWD test. These sections were grouped based on the district location and classified either as excellent or average pavements depending on the structural condition at the time of testing.

Figure 1 shows the districts subdivision of the state of Ohio. Ohio [7]. The studied sections were a subset of data of those used to define Figure 2. Table 1 presents the location, length, district, year, and initial condition of the pavement sections.

The directions are referred as upstation U , downstation D or with the dual index DU for the cases when the section was tested in both directions. The year refers to construction date. The condition refers to the initial performance condition of the section as giving by the PCR index. A description of this equipment and testing procedures are presented in Sargand et al. The FWD device used for this project consisted of seven sensors, aligned radially from the application of the load, to measure and record the deflections induced by the FWD.

The separation between the sensors can be adjusted to measure settlements at different points of interest. The settlements measured from sensors 1 — 5 are used to evaluate the pavement structural condition, meanwhile settlements measured from sensors 6 and 7 are used to estimate the stiffness of the subgrade. Two additional parameters used to evaluate the structural pavement condition of PCC pavement sections are the load transfer parameter and the joint support ratio.

The load transfer parameter is an indicator of the joint performance that depends on the applied load, aggregate interlock, and temperature acting on the pavement. The load transfer is calculated using the following equations for the approaching and leaving joint positions, respectively:. The modulus of elasticity of the subgrade was calculated by taking an average of the values obtained from sensors 6 and 7, as described below [9], calibrated in U.

The normalized deflections and spreadability for each geophone were computed as follows [10], calibrated in U. S units:. The Joint Support Ratio JSR parameter is an indicator of the pavement condition under the slabs and is calculated as follows:. Table 2 shows the values of deflections, spreadability, load transfer, and joint support ratio used to classify the structural pavement condition [11].

Source Chou et al. Portland cement concrete pavement sections Proj. SLM Limits The modulus of elasticity of the subgrade was back-calculated from the FWD collected data. Figures 3 and 4 show a decrease in pavement stiffness, both concrete and subgrade layers, between SLM 0.

Figures show that the overall condition of the pavement joints is from good to excellent. Figure 8 presents the back-calculated modulus of elasticity of the subgrade. M R ranged from 31 ksi upstation to 36 ksi downstation , which in geotechnical terms is considered as a competent layer. From figures 3, 4, and 8, it can be concluded that the stiffness deficiency between SLM 0. Although the spreadability is classified as good. The pavement performance in both directions is similar and therefore the conclusions are applicable for both cases.

The average modulus of elasticity in the upstation and downstation directions is 31 ksi MPa and 36 ksi MPa , respectively. The determination of this parameter from actual field observations as presented in this research not only provides an indication of the pavement deterioration in comparison to the initial design modulus but also is a reliable parameter that can be used to estimate the pavement behavior and performance based on computer models.

Souce: Edward et al. A complete definition of these material specifications can be found in ODOT [13]. Tables show the structural condition of these pavement sections based on FWD deflections and spreadability, maximum joint deflection, and joint load transfer and joint support ratio, respectively.

In general, the structural condition of the studied sections are classified as excellent and good, except for project 4 that showed a load transfer deficiency in both the approaching and leaving positions. Good Fair Poor Exc. Based on the structural condition classification, short or long term rehabilitation programs can be implemented to assure satisfactory service and serviceability of the PCC pavement. The long term performance of seventeen Portland cement concrete sections located in the State of Ohio, USA, was studied.

The performance of PCC pavement was influenced by the climate conditions, material properties, construction practices, and traffic loads. The total length of the PCC pavement sections studied was 36 mi 58 km. The overall structural condition of the analyzed sections was as follows: a Excellent On the other hand, the overall condition of the pavement stiffness was: a Excellent The overall performance of the pavement system was influenced by the stiffness of the base layer and the thickness of the surface layer.

In general, the structural pavement condition of the PCC sections was classified as excellent and good, except for Project 4 in which the load transfer mechanism between the slabs negatively impacted the overall capacity of the rigid pavement. Antioquia 66 3 , pp. Department of Transportation, Department of Transportation. Universidad de Granada. Civil engineering.

The presence of moisture causes a reduction in aggregate-binder adhesion in the mix as well as in the internal cohesion of the bitumen. This leads to problems such as pot holes, aggregate peeling, stripping, etc. Currently, there are numerous laboratory tests that analyze the susceptibility of bituminous mixes to moisture, providing a qualitative or quantitative evaluation.

This study analyzes the performance of bituminous mixes in different experimental conditions. For this purpose, a comparative study of two laboratory tests was carried out. The tests differed in mix compaction method, the conditioning of the test specimens, and the type of load applied. The results obtained showed that in these tests the conditioning temperature had a greater impact on mix performance than the temporal duration of the conditioning process.

Furthermore, the application of tensile stress was found to be more suitable for studying moisture susceptibility since mixes were found to be more sensitive to this type of load. Key Words: Hot bituminous mixes, road, mix design, moisture susceptibility. Actualmente existen numerosos ensayos de laboratorio que permiten analizar la susceptibilidad al agua de las mezclas bituminosas, proporcionando una medida cualitativa o cuantitativa.

Los resultados obtenidos pusieron de manifiesto que, para los ensayos estudiados, la temperatura de acondicionamiento ejerce mayor influencia en el comportamiento de la mezcla que el tiempo de acondicionamiento. This material is a conglomerate with a mineral skeleton composed of a coarse fraction with a diameter.

It is also composed of a hydrocarbon binder that gives cohesion to the mineral skeleton bitumen or one of its byproducts from the distillation of crude oil , and sometimes, a Dyna, year 81, no. In order for the mix to be used in the road surface course, it must pass a series of laboratory tests that certify its suitability and good performance under various types of load or stresses to which it will be subjected during its service life traffic loads, extreme temperatures, water action, etc.

Of these stresses, those produced by water action are among the main causes of the pavement deterioration loss of aggregate, peeling, pot holes, etc. The presence of moisture in the mix reduces aggregate-binder adhesion i. This leads to a loss of aggregate, which in the medium and long term, and combined with other negative factors traffic loads, ice formation, binder ageing, etc.

As seen in Lu and Harvey [18], one of the key ways to mitigate the effect of water action on mixes is the design and application of laboratory tests capable of predicting the potential moisture damage during the service life of the pavement. This makes it possible for the mix to have an optimal design. Methods to predict the effect of moisture action on the bituminous mixes were initially developed in the s, and there are now a wide range of such tests available [].

A description of these methods can be found in Solaimanian et al. The objective of such methods is to reproduce mix performance in laboratory conditions when it is affected by water. They vary in reliability, depending on the characteristics of the test, the mix type, as well as the environmental conditions of the use case cold or hot temperatures, dry or rainy weather, etc. Most of these tests are performed with fixed temperatures and loads. This means that it is impossible to simulate the effect of moisture on the pavement when it is subjected to varying traffic loads and weather conditions [22].

Nevertheless, these experiments are often very complicated and timeconsuming to perform. Moreover, they are somewhat. It is thus necessary to analyze and compare the effect of these laboratory tests on the mix in order to evaluate its response. Only in this way will it be possible to predict the performance of a mix when it is actually used in road construction.

In the laboratory, methods for testing moisture susceptibility differ in the mix compaction method, the type of conditioning, and the application of the load. Although there are many tests used for this purpose e. Today there is a division of opinion regarding which test is the most suitable for studying the susceptibility of bituminous mixes to moisture action.

Consequently, in this study a comparative analysis was made of two of these methods, and the performance of the mix was analyzed in terms of characteristics, such as type of test specimen, compaction method, conditioning process, and load application. In this way it was possible to arrive at conclusions concerning the representativity of the results of each test. The laboratory tests selected were two that are commonly used in Spain: a the Immersion-Compression Test regulated by the Spanish Technical Standard NLT ; b the Water Sensitivity Test regulated by the European standard UNE-EN and implanted as a new reference test to analyze the susceptibility of bituminous mixes to moisture in all European Union countries.

Both tests differ in so far as the type of test specimen used dimensions and compaction methods , conditioning process, and applied load. However the result of both tests is a retained strength value, which makes it possible to compare them. This article analyzes the results obtained after performing the Immersion-Compression Test and the Water Sensitivity Test on samples of the same mix type with an identical mineral skeleton and the same percentage of bitumen.

The number of samples studied had to be sufficient to statistically validate the results obtained and thus extract representative conclusions. A total of 33 samples were used, and the central limit theorem was applied. The results of both laboratory tests were statistically analyzed, as well as the mix response in each. Materials The semi-dense mix used in the study was regarded as representative, a generic asphalt concrete that is commonly found in all type of road surfaces regardless of climate or traffic loads throughout Europe.

This made it resistant to plastic deformations and water action. The samples were made in different batches though the characteristics of the mix did not vary. The mineral skeleton of each batch was within the grain-size limits specified in the Spanish regulations [29], which establishes a reference particle size for this type of mix.

Nevertheless, in our samples, the mineral skeleton was slightly modified to obtain different air void contents so as to better study the effect of the water volume on the mix. The aggregate used in the mix was ophite for the coarse fraction and limestone for the fine fraction as well as mineral dust. The filler fraction chosen for the mix was limestone, given its good response to water action. This is due to the fact that the adhesion of limestone with the binder is greater since its alkaline surface reacts better to the acid composition of the bitumen [30].

The limestone had an apparent density in toluene of 0. The optimal bitumen content used to make the specimens was 4. Both tests offer a similar result retained strength. Nevertheless, test conditions compaction method, specimen conditioning, and load applied are not the same, so they can be used to analyze and compare the performance of the mix to water action In this study 33 samples of the same mix type AC 16 — S were tested.

The specimens had identical characteristics but belonged to different batches. The number of samples was based on the central limit theorem. According to this theorem, when the number of samples of a population is sufficiently large i. It is thus possible to derive scientifically valid conclusions from the results obtained. The Immersion-Compression Test involves the manufacturing of 10 test cylinders with a diameter of These cylinders are compacted by means of a static load produced by a double plunger.

There is an initial pre-load of 1 MPa in order to settle the mix after which the load applied steadily increases for 2. Then the density of the samples is determined by the saturated surface dry method. As part of the conditioning process before the test, the specimens are divided into two sets of five.

After 24 hours, both sets of specimens are subjected to a simple compression load at a constant deformation velocity of 5. In this way it is possible to obtain a mean retained strength value for each set. The Water Sensitivity Test involves manufacturing 6 specimens with a diameter of The specimens are compacted with an impact compactor by applying 50 blows on each. Then the density of the samples is determined by the saturated dry surface method.

As part of the conditioning process, the specimens are divided into two sets: a wet set and a dry set. In this study, the relation between the variables in each test and the mix response was obtained by using a simple linear regression. Once the straight regression line is fit to the cloud of data points, it is crucial to have a measurement of the goodness of fit, which shows whether the fit is sufficient. The determination coefficient was used for this purpose.

When a simple linear regression is performed, this coefficient coincides with the square of the linear correlation coefficient. The determination coefficient is interpreted as the percentage variation of the dependent explained by the model. In this type of study, the tests were very heterogeneous, and this meant that the results of the tests were, as well. Consequently, the determination coefficients of the linear fit lines were not very high. Apart from the simple linear regressions, and given that both tests had different characteristics, the retained strength values were studied according to a normal distribution in order to reinforce the comparative analysis.

Compression Test and the Water Sensitivity Test in relation to the mean values of the wet and dry sets of samples for fracture strength, density, and air void content of the test specimens. Coefficient of variation CV is calculated for the Immersion-Compression Test and the Water Sensitivity Test for fracture strength, density, and air void content for both wet and dry sets obtaining in all cases similar deviations see tables 1 and 2.

CV Immersion-Compression test. Since the samples in the study were manufactured with the same materials aggregate and bitumen , there is a close relation between the air void content and the density of the specimens in both tests despite the fact that they differ in compaction method. Accordingly, the samples with a lower density have a greater content of air voids in the mix. As can be observed in the results, in the ImmersionCompression Test, the air void content and the density of the specimens do not have a significant effect on the simple compressive strength Figure 1.

Therefore, a dispersed cloud of data points, and the extremely low determination coefficients of the regression lines, reflect the independence of both characteristics in the. This is due to the fact that in bituminous mixes, compression forces are endured mainly by the internal friction of the mineral skeleton. Consequently, the strength of the. Simple compression strength based on the density and air void content of the mix: dry set left and wet set right. In contrast, in the Water Sensitivity test, there is a closer relation between the air void content and density of the specimen and its indirect tensile strength.

This is reflected by a higher determination coefficient in the linear regression lines see Figure 2. This tendency implies that when a specimen has a lower density or a higher air void content, its strength is reduced. In this case, the application of the load varied, and the specimen was subjected to tensile stresses such that the internal cohesion of the mix the sum of binder.

This strength decreased as the air void content of the specimen increased. This was because the quantity of air voids spaces without aggregate or bitumen on the plane where the break occurred meant that there was less surface to withstand the strain. The test specimen was thus weaker. Indirect tensile strength based on the density and air void content of the mix: dry set left and wet set right. Moreover, it should be noted that the indirect tensile strength of the specimens in the Water Sensitivity Test was less than the simple compression strength in the Immersion-Compression test.

This response is logical since concrete-type stone materials, such as bituminous mixes, perform much better under compression loads than under tensile stresses. As can be observed, the retained strength in the Water Sensitivity Test was greater than in the ImmersionCompression Test. When the retained.

The analysis also showed that the Gaussian bell curve in the Water Sensitivity Test is sharper, which means that the results are more clustered. The samples thus have a lower variability, which signifies that the test is more reproducible and thus its results are more representative. However, it did not seem to have a significant influence on the results obtained. In this respect, the densities of the 33 samples in both studies were very similar, though they were slightly higher in the case of the ImmersionCompression Test Figure 5.

According to these results, the simple compression strength of the bituminous mix was potentially more affected by moisture action than its indirect tensile strength was. However, the simple compression strength mainly depends on the internal friction of the aggregate, and the indirect tensile strength on the internal cohesion of the mix, which is the sum of binder cohesion and aggregate-binder adhesion.

Both factors are significantly more sensitive to moisture action than the internal friction of the aggregate i. As a result, the retained strength of the Water Sensitivity Test should be lower. The temperature of the conditioning had a greater influence on mix performance than the temporal duration of the conditioning. The compaction method was the other variable in which the tests differed, apart from the conditioning.

Finally, in the analysis of the influence of the air void content and the density, on the retained strength, it was observed that both tests showed the same tendency. The greater the density i. Welcome to forex forum binary options trade. Please login or sign up. Entire forum.

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