Predict Field Performance Research Articles

Scaling-up laser cladding of rails

With rail travel getting more popular more demands are being put on rail infrastructure. The wheel/rail contact is the one of the main parameters that is key to maintaining a high performing network. With increasing demands for higher loads and higher speeds, wear and rolling contact fatigue (RCF) are the main two problems.New maintenance techniques can overcome some problems, but new solutions that reduce the damage are needed. Laser cladding is one of the best methods for improving wear and RCF of rail steels by adding layers of more durable materials to the rail.In this article full-scale tests of clad layers have been carried out at realistic contact conditions to verify outcomes seen in twin-disc testing to see if the results can be scaled to predict field performance of clad layers. Martensitic Stainless Steel (MSS) and Stellite 6 were used for the clad layers and R260 was used as the base material. Un-clad R260 was used as reference material.Results of full-scale tests in terms of wear rates, sub-surface deformation, hardness and roughness evolution were comparable. This showed that the clad layers deposited on actual rail performed very well compared to un-clad rail and that the tests run at the small-scale were appropriate for predicting full-scale behaviour.

Морфометрические критерии оценки качества контейнерных сеянцев хвойных пород

The quality of planted forest crops depends significantly on the qualities of the planting stock. Numerous studies have been carried out to find clear seedling quality criteria and work out methods for their quantitative assessment to optimize the cultivation regime. Indicators of planting stock that are available for measurement under nursery conditions are needed to predict the success of forest crop establishment. This paper provides a review of the studies that applied different morphological criteria to evaluate coniferous planting stock quality and different determination methods. The suitability of planting stock quality indicators is determined by the effectiveness of predicting the outplanting survival rate (%) and growth. The key morphometric attributes of planting stock are the linear dimensions and biomass of whole seedlings and their individual organs: root collar diameter (RCD), seedling height (SH), dry mass of needles (NDM), stem (SBDM), roots (RDM), shoot/aboveground part of the seedling (SDM), seedling’s total dry matter (TDM), number of needles (NN). Effective indicators of seedling quality are morphometric indicators of roots: total length (TRL), volume (TRV), dry mass (RDM), number of first- (FOLR N), second- (SOLR N), and third-order (TOLR N) lateral roots, root surface area (TRS). TRL is a fairly reliable indicator of absorbent surface area. To minimize errors in the use of one or two traits, integrated seedling quality indices based on two or more indices have been developed. Widely used indices include: SQ = SH(cm)/RCD(mm); SDM/RDM ratio; Dickson quality index DQI = TDM/ ((SH / RCD) + (SDM / RDM)). RCD was the most suitable parameter to indicate seedling quality for many species due to its higher correlation level with the Dickson quality index. The SH index proved to be an effective indicator for analysis only when used together with RCD. When studying the formation of frost resistance, a number of morphological parameters are used: initiation of needle primordia, size of primordial shoots, cell volume, mitotic index (MI) of terminal primordia. Despite advances in testing planting stock quality and predicting field performance, not a single test is universally applicable for all woody plant species and environmental conditions. According to the target seedling concept, the application of morphometric criteria for assessing seedling quality in forest nurseries is a prerequisite for predicting outplanting success and maximizing the predictability of the outcomes of highproductivity forest crop planting. For citation: Robonen E.V., Chernobrovkina N.P., Egorova A.V., Zaitseva M.I., Nelaeva K.G. Morphometric Criteria for Assessing the Containerized Conifers Seedlings Quality. Lesnoy Zhurnal = Russian Forestry Journal, 2023, no. 5, pp. 42–57. (In Russ.). https://doi.org/10.37482/0536-1036-2023-5-42-57

POMS and eye movement: Two indicators for performance in athletics

BackgroundRegularly and scientifically participating in athletics is beneficial for physical and mental health. Mood or emotions are important component of psychology and a major indicator of physical and mental health. Positive and negative mood or emotions can have a strong impact on physical responsiveness. The aim of the present study was to explore whether mood or emotional state influence performance in athletics. MethodsMood, analyzed by Profile of Mood States, and emotional state, reflected by eye movement (looking at times and length), were used to predict track or field performance in training and competition. Results1. The profile of track training (except 3rd week) resembled an iceberg profile (highest vigor scores) and the profile on the 3rd week resembled a “melting” iceberg profile, in which positive mood (vigor and self-esteem) was decreased and negative mood, particularly depression and anger, was significantly increased. The profile of field training almost overlapped, with the exception of depression decreasing markedly on the 3rd and 4th weeks. 2. Positive mood overpowered negative mood, particularly following a track competition; positive emotions exceed negative emotions following track and field competition. 3. The results of the regression analysis showed that an improvement in track performance was negatively correlated with a rise in total mood disturbance (TMD), and field performances were positively correlated with positivity of emotion, as tested by eye movement. 4. Good performance in track events appeared to be associated with decreased vigor and increased fatigue during 3rd and 4th track training; decreased depression and fatigue, and increased vigor as well as low observe length of watching negative emotional pictures (NEPs) before track competition. A good performance in field events appeared to be associated with anger decrease and confusion increase, increased fixation counts of watching positive emotional pictures (PEPs), and decreased fixation and observe counts of watching NEPs before field competition. ConclusionsThe present study proved that different indicators appeared to measure different sport performances: More indicators of Profile of Mood States inclined to predict track performance, while more eye movement indicators could predict field performance. Mixed methods could provide a better understanding of performance than a single approach alone. These findings provided theoretical support and supplementary data for practical applications in the design of comprehensive training programs.

Comparison of Bond Strength Evaluation Methods Between Pavement Layers

Tack coats are generally used to facilitate a bonding between pavement layers in construction of hot-mix asphalt pavements and overlays. The goal of applying a tack coat material is to ensure the new or consecutive pavement layers respond monolithically under loading and avoid premature failure caused by debonding, mat slippage, or fatigue cracking. Multiple different in-situ and laboratory tests have been developed to evaluate bond strength of tack coat materials under tension, shear, and mixed-mode loading mechanisms. However, there is no universally accepted bond strength test method or performance criteria for tack coats within the United States. While some specifying agencies have gained familiarity and comfort with a particular bond strength test, a gap exists for many states that have not adopted a testing procedure. The objective of this paper is to compare current and newly developed tack coat bond strength tests to help determine which is most indicative in predicting field performance. Field cores from four different pavement sections with varying traffic loading conditions and early bond strength performance were sampled and tested in the laboratory using four different bond strength evaluation methods. Statistical analysis of bond strength testing results shows a strong linear correlation between pull-off and shear strength testing. Meanwhile, a novel approach to tack coat bond testing under cyclic tensile loading was explored and showed appreciable discrimination between sample locations and agreement with early field performance.

A Critical Review of Existing Test-Methods for External Sulfate Attack.

External sulfate attack (ESA) of cementitious materials has been studied worldwide for a very long time. This physical/chemical interaction between sulfate ions and the cement hardened elements affects the long-term durability of concrete structures: cracking, spalling or strength loss of concrete structures. To study these damaging phenomena, some standardized and non-standardized accelerated aging tests are used to evaluate the performance of cements in sulfate-rich environments. However, these existing methods do not adequately predict field performance and some shortcomings or deficiencies still exist: change of degradation mechanisms when using high concentrations of sulfate, variable boundary conditions and small specimens compared to the real concrete structures. In this work, a critical review of some existing test methods and foreign national standard methods for ESA are presented, analyzed, and discussed. This results in some proposed recommendations for improving these methods to meet the needs of structure managers.

Warm Mix Asphalt Demonstration Projects in Louisiana: Case Study of Five to Eight Years of Field Performance

Warm mix asphalt (WMA) technology has gained popularity in recent years because of its ability to enhance mixture compaction at relatively low temperatures and to improve environmental sustainability. The role of WMA in sustainable pavement technology means that there is a need for comprehensive research in relation to its field performance. The objective of this study was to evaluate the field performance of WMA pavement sections that have been in service for five to eight years. Four rehabilitation projects were evaluated throughout the State of Louisiana. The study included field and laboratory experiments. In the field experiment, WMA test sections were evaluated along with companion conventional hot mix asphalt (HMA) mixture sections on each project. Pavement performance indicators (rutting, roughness, and cracking) from the Louisiana Pavement Management System (PMS) were analyzed. The laboratory experiment consisted of evaluation of mixtures from each project to determine mechanical performance indicators such as loaded wheel tracking (LWT) rut depth, flow number, semi-circular bend energy release rate (SCB Jc), and dissipated creep strain energy (DCSE). An analysis was conducted to rank the capability of laboratory mechanical performance properties to predict field performance. Generally, WMA test sections were found to exhibit similar or better rutting and cracking performance compared with their companion control HMA sections. In addition, the LWT rut depth was found to be a better indicator of field rutting performance than the flow number parameter. It is worth noting that the SCB Jc parameter was found to correctly rank more field cracking indicators than the DCSE parameter and therefore it may be a better indicator of field cracking performance.

Nursery fertilization affected field performance and nutrient resorption of Populus tomentosa Carr. ploidy levels

Nutrient resorption (NuR) is an important nutrient conservative strategy but little information is available about the effect of nursery fertilization on NuR in the field. In this study, diploid and triploid one-year-old plants of Populus tomentosa Carr. were fertilized with 9 g N per plant, and non-fertilized plants as control. Initial functional attributes, i.e., height, diameter, stem mass, mineral nutrients and non-structural carbohydrate (NSC) levels of each tissue, were measured before planting. Field performance (survival, total height, diameter, stem volume and their growth, leaf nutrient status, and NuR) were measured in the field. Compared to control, 9 g N per plant was benefit for plant growth, mineral nutrients and NSC accumulation of diploids, but declined plant size of triploids before planting. While in the field, fertilization effect on plant size was inversed for each ploidy level. Nursery fertilization increased nitrogen resorption efficiency (NRE) of triploids and decreased phosphorus resorption efficiency (PRE) of both ploidy levels. Initial plant size were the most effective parameters predicting field performance and NuR. Furthermore, NRE was multi-elements controlled as indicated by the correlation of N and P in green and senesced leaves, while PRE was only positively correlated with P in green leaves. However, there was no relationship between field growth and NuR. This study deepened our understanding of NuR from the perspective of artificial managements, for instance nursery fertilization.

Prediction of one-third-octave band sound and vibration levels from heavy-hard impacts

Noise and vibration due to dropping hard heavy weights is a common source of disturbance and complaint in residential, commercial, and mixed-use building types. The authors and others have worked on developing methodologies to accurately, repeatably, and conveniently measure heavy-hard impact noise and vibration in the field based on a standard weight drop. Separately, systems have been created to measure the force being injected into a building from heavy-hard impact. It has been shown that this force data can be used to successfully predict vibration levels in buildings if in-situ transfer functions are known. In this paper, the authors will present a novel one-third-octave band prediction method using the laboratory force data and a reference impact sheet to predict field performance without the need to measure transfer function. The method is evaluated using both noise and vibration measurements.

Experimental Assessment of Mineral Filler on the Volumetric Properties and Mechanical Performance of HMA Mixtures

This research is conducted to evaluate the influence of mineral filler on the volumetric properties, mechanical and field performance of Hot Mix Asphalt (HMA). Two mineral filler types, namely, Hydrated Lime (HL) and Dust Plant (DPt) were used. Three filler proportions were utilized greater than 1% which represents the most applicable percentage, especially for HL, used by the Ministry of Transportation Ontario (MTO). The effect of filler on various volumetric properties including Voids In Mineral Aggregates (VMA), Voids Filled With Asphalt (VFA), dust to binder ratio (Dp) is examined. Mechanical and predicted field performance of HMA to the best filler proportion that meets all the MTO limitations is also investigated. The obtained results indicated that the Optimum Asphalt Content (OAC), VMA, and VFA decrease as the filler content is increased. HMA mixtures that includes DPt filler had the higher values of VMA, VFA, and OAC compared to the hydrated lime. The addition of filler with 2.5% percentage is very successful for both filler types due to satisfying all MTO requirements for volumetric properties of HMA. Based on MTO specifications, the addition of 2.0% filler seems to be unsuccessful for both filler types due to lowering the Dp ratio. Mix design with 3.0% filler was also unsuccessful because of the lower value of OAC meaning that the mix is dry and there is insufficient asphalt binder to coat the aggregate particles. Besides, filler type has a significant effect on the mechanical properties of the HMA mixtures. As a filler in HMA mixtures, the utilization of HL as a portion of 2.5 % leads to a significant improvement in mixture resistance to water and freezing and thawing. The mixtures that included HL have a higher cracking resistance, greater stiffness, and a higher fracture stress than the mixtures that included DPt. Furthermore, predicted field performance indicated better outcomes for mixes with HL compared to DPt mixes. Doi: 10.28991/cej-2020-03091619 Full Text: PDF

Field and simulated rutting behavior of hot mix and warm mix asphalt overlays

Research implementing new pavement technologies often focuses on material characterization; however, expanding the research to study and validate how new technologies influence pavement design is needed for continual improvement. Numerical analysis approaches use laboratory mixture data to predict field performance. This study compares predicted rutting by MEPDG design, estimated rutting from Finite Element (FE) simulations, and actual rutting performance in the field. Ten years ago, warm mix asphalt research was underway to measure the effect of warm mix asphalt (WMA) additives and lower production temperatures on performance. WMA benefits include reduced mixing/compaction temperatures, reduced fuel consumption, and improved compatibility. In 2009, three asphalt overlay projects were constructed in Iowa using both hot mix asphalt (HMA), and WMA mixes to compare their performance. A series of dynamic modulus tests were conducted to determine dynamic modulus and phase angles of HMA and WMA mixtures. The dynamic modulus results were used to develop FE viscoelastic simulations to predict the rutting of HMA/WMA pavement sections. Iowa’s pavement management system provided field rutting of WMA/HMA sections. Also, pavement sections were evaluated using mixture input parameters in the Mechanistic-Empirical Pavement Design Guide (MEPDG). The results showed MEPDG based on linear elastic theories might overestimate the rutting of asphalt pavements, especially overlays placed on Jointed Plain Concrete Pavement (JPCP). In contrast, the FEM based on viscoelastic theories more accurately predicted the rutting of pavements. Calibration coefficients are proposed by this study, which may be useful for design engineers and industrial applications to correct and modify MEPDG overlay design thicknesses for HMA/WMA mixes placed on HMA and JPCP surfaces.

Model-based decision analysis applied to petroleum field development and management

This work describes a new methodology for integrated decision analysis in the development and management of petroleum fields considering reservoir simulation, risk analysis, history matching, uncertainty reduction, representative models, and production strategy selection under uncertainty. Based on the concept of closed-loop reservoir management, we establish 12 steps to assist engineers in model updating and production optimization under uncertainty. The methodology is applied to UNISIM-I-D, a benchmark case based on the Namorado field in the Campos Basin, Brazil. The results show that the method is suitable for use in practical applications of complex reservoirs in different field stages (development and management). First, uncertainty is characterized in detail and then scenarios are generated using an efficient sampling technique, which reduces the number of evaluations and is suitable for use with numerical reservoir simulation. We then perform multi-objective history-matching procedures, integrating static data (geostatistical realizations generated using reservoir information) and dynamic data (well production and pressure) to reduce uncertainty and thus provide a set of matched models for production forecasts. We select a small set of Representative Models (RMs) for decision risk analysis, integrating reservoir, economic and other uncertainties to base decisions on risk-return techniques. We optimize the production strategies for (1) each individual RM to obtain different specialized solutions for field development and (2) all RMs simultaneously in a probabilistic procedure to obtain a robust strategy. While the second approach ensures the best performance under uncertainty, the first provides valuable insights for the expected value of information and flexibility analyses. Finally, we integrate reservoir and production systems to ensure realistic production forecasts. This methodology uses reservoir simulations, not proxy models, to reliably predict field performance. The proposed methodology is efficient, easy-to-use and compatible with real-time operations, even in complex cases where the computational time is restrictive.

Drop Tower Testing—The next step in heavy weight impact testing

Over the last few years, research into heavy hard impacts from fitness activities has become an active field of investigation and product development. In order in facilitate our efforts, Pliteq has built a custom drop tower capable of repeatability dropping up to 150 kg from well over 2 m height. During the impact, the force, displacement, velocity, and acceleration can be obtained. This paper will give an overview of this apparatus, the type of data that it can collect, how this data can be used to make better products and how the data can be used to predict field performance.

Global Prediction of Photovoltaic Field Performance Differences Using Open-Source Satellite Data

Summary Accurate field-performance prediction is essential for the calculation of return-on-investment for photovoltaic projects. Leading software predicting field performance was developed for traditional technologies and markets. Yet emerging markets are projected to install over half of all solar cells by the end of this decade, with persisting interest in new technologies. In this study, we map photovoltaic system performance over the entire planet, for standard and emerging technologies, using open-source satellite data. We validate results using time-resolved field-performance data of cadmium telluride and silicon modules in temperate (Perrysburg, OH, USA) and hot-humid (Singapore) climates. Watt for watt, we find that CdTe produces up to 6% more energy than Si in tropical regions. This result emphasizes the significance of local performance evaluation to complement standard testing condition efficiencies. We extend our model to emerging materials including lead-halide perovskites and III-V thin films, and demonstrate that larger band gaps have performance advantages in hot and humid environments.

Predicting field performance of on-board diagnostics using statistical methods

On-board diagnostics will play a crucial role in the emerging era of the Internet of Things. With billions of devices deployed, traditional manual preventive maintenance approaches will be cost prohibitive. As we make these small autonomous devices intelligent, it is critical that we also give them a very advanced ability to assess and report their own health. Of course, on-board diagnostics are not a new concept. What is new with the Internet of Things is the extreme economic leverage that the on-board diagnostics will have due to the huge number of devices to be developed. If the on-board diagnostics perform poorly, the resulting surge of support costs could be enough to drive the organization deploying the Internet of Things systems out of business. As an organization gets ready to release millions of a certain type of Internet of Things device into the wild, how confident can the organization be that the on-board diagnostics will really perform as expected? As it turns out, we can learn from history. In the 1960s and 1970s, the mainframe and telecommunications industries developed powerful statistical methods for answering this exact question for the large mission-critical systems that they were deploying.

Power-velocity curve: relevance of the SRM Ergometer for simulated cycling performance and constant duration tests

Introduction : When trying to obtain cycling performance capacity, a controlled laboratory setting is required to obtain valid and reliable results [1]. Ecological validity is important, as several studies found poor agreement between lab and field time trials [2,3]. To perform realistic time trials on an ergometer, it is important that the cyclist is able to 1) choose its own cadence, 2) that the ergometer accounts for changes in kinetic energy and 3) the ergometer accounts for the non-linear relation between air-frictional forces and velocity. The SRM Ergometer has a free mode with a gear box and a big flywheel, so requirements 1 and 2 are fulfilled. It is unknown if the brake algorithm of the ergometer is linear or non- linear and how this mimics real life cycling. The aim of the present study is therefore to determine the relationship between the mechanical power output and the velocity in the SRM ergometer compared to cycling on a velodrome. Methods : The relation between mechanical power output and velocity in incremental cycling on an SRM Ergometer (2Hz sampling rate) was determined with the ergometer set in the “Open End Test” mode, which allows the cyclist to freely choose his gear and self-select his pace. Power output and velocity were collected over 30 s intervals of steady state cycling per stage, resulting in the power-velocity curve. The SRM Ergometer was propelled using a dynamic calibration rig to simulate a pedalling cadence ranging from 60-160 rpm, with 10 rpm steps through gears 7- 12 of the Rohloff nave. The rig was attached to the crank of the SRM Ergometer via a counterbalanced double universal joint. The axle was centred at the bottom bracket of the SRM Ergometer and attached to the crank at the position of the left pedal. By upshifting gears and increasing cadence, a range of velocities and accompanying power outputs could be evaluated. The calibration rig was powered by a 3 Ph – AC electro motor with a maximum power output of 2.2 kW. Data of 2 elite track pursuit cyclists were obtained for comparison with the ergometer. Cyclist 1 rode in standard position and cyclist 2 in aerodynamic position on a 250 m indoor velodrome in Alkmaar, the Netherlands, with an air density of 1.19 and 1.20 kg.m3 respectively. The track bikes were equipped with a SRM 7 track system. Sample rate was set at 2 Hz. Two laps at six different velocities were cycled, starting at 30 km/h with an increase in velocity of 5 km/h to 55 km/h. For SRM ergometer cycling as well as for track cycling, trend lines were added based on least-squares fit, and coefficients of determination were obtained. The best fits were used to predict power output at fixed speeds between 25 and 60 km/h for the ergometer and track cyclists. From these data Pearson product-moment correlation coefficient and absolute and relative differences in power output between the ergometer and track cyclist were determined Purpose: The objective of this study was to determine if exercise mode played a part in the acute immune responses to exercise. Results : Power fit trend lines were found to resemble the best fit for the power-velocity curve for both the SRM Ergometer as well as in the real world situation (see Figure 1). This indicates that the SRM Ergometer uses a non- linear instead of a linear breaking algorithm, related to the velocity of the flywheel. The correlation for the predicted power output at fixed speeds was perfect (r=1.000) between the SRM ergometer and both cycling position on the track, with a standard error of the estimate of 1.64 and 2.96 respectively for standard and aero position. At high velocities, the SRM Ergometer required a similar power output as standard cycling but a higher power output than required in track cycling in aero position at the same velocity (see Table 1). Conclusion : The non-linear power-velocity curve of the SRM Ergometer that closely resembles the power-velocity curve of track cycling indicates that it mimics real life cycling behaviour and that it therefore could be used to simulate free ride efforts like time trials and constant duration tests to determine mean maximal power output. However, one must be cautious to use the velocity measured by the ergometer to predict field performance, as at the same power output the speed on the track is higher in aero position.

Assessment of drought tolerance and its potential yield penalty in potato.

Climate models predict an increased likelihood of seasonal droughts for many areas of the world. Breeding for drought tolerance could be accelerated by marker-assisted selection. As a basis for marker identification, we studied the genetic variance, predictability of field performance and potential costs of tolerance in potato (Solanum tuberosum L.). Potato produces high calories per unit of water invested, but is drought-sensitive. In 14 independent pot or field trials, 34 potato cultivars were grown under optimal and reduced water supply to determine starch yield. In an artificial dataset, we tested several stress indices for their power to distinguish tolerant and sensitive genotypes independent of their yield potential. We identified the deviation of relative starch yield from the experimental median (DRYM) as the most efficient index. DRYM corresponded qualitatively to the partial least square model-based metric of drought stress tolerance in a stress effect model. The DRYM identified significant tolerance variation in the European potato cultivar population to allow tolerance breeding and marker identification. Tolerance results from pot trials correlated with those from field trials but predicted field performance worse than field growth parameters. Drought tolerance correlated negatively with yield under optimal conditions in the field. The distribution of yield data versus DRYM indicated that tolerance can be combined with average yield potentials, thus circumventing potential yield penalties in tolerance breeding.

An improved solution to estimate relative permeability in tight oil reservoirs

The relative permeability is a critical property to predict field performance by reservoir numerical simulation. However, determining the relative permeability curve by experiments is time consuming and difficult for tight oil reservoirs due to the extremely low permeability. Therefore, many studies focus on the analytical solution to determine the relative permeability curve. However, no exiting solutions take the effect of boundary layer, Jamin and wettability into account. This results in overestimated results because boundary layer is even up to 60 % of the throat and throat to pore ratio reaches up to 400 in tight oil reservoirs. Therefore, an improved analytical solution is desirable to solve these two problems. In this paper, based on the collected experimental results, the Purcell’s solution is modified and an improved solution considering the effect of boundary layer, Jamin and wettability is developed. Compared to the results of the relative permeability experiments, the improved solution is more accurate and reliable. Because the throat distribution of the tight oil reservoir in Daqing Field is narrower than that in Changqing Field, the productivity of the tight oil reservoir in Daqing Field is less than that in Changqing Field at first. However, the breakthrough time of the tight oil reservoir in Daqing Field is longer than that in Changqing Field. This improved solution can only be applied to tight oil reservoirs, because boundary layer and Jamin have little effect on the flow behavior in conventional reservoirs.

Effect of precipitation on LNAPL recovery performance: An integration of laboratory and field results

The recovery rate of light-non-aqueous-phase-liquids (LNAPLs) in an unconfined aquifer was affected by precipitation and the rise and fall of the water table at the 322.5K site in Taiwan. The field performance of LNAPL recovery can be generated in the laboratory waterflood experiments using undisturbed soil samples taken from the 322.5K site. A log–log type-curve-matching method was developed in this paper to compare the laboratory waterflood results with the performance of LNAPL recovery observed on the 322.5K site. Laboratory-observed LNAPL recovery can be scaled up to predict field performance of LNAPL recovery through the log–log type-curve.

Prediction of planted seedling survival of five Mediterranean species based on initial seedling morphology

Field performance can be predicted by evaluating nursery stock quality, but optimal morphological variables for use in these assessments may vary by species especially under dry Mediterranean conditions. Our objective was to identify initial seedling morphological characteristics that successfully predict field performance of five Mediterranean species (Pinus halepensis, Quercus ilex, Quercus coccifera, Ceratonia silqua and Pistacia lentiscus). Container seedling morphology was evaluated following the nursery phase, and then seedlings were outplanted in the field where field survival was monitored for two successive years. Results indicate that survival can successfully be predicted from seedling initial morphological characteristics for all these species, yet not all the initial characteristics were good predictors. Survival of P. halepensis and Pist. lentiscus seedlings was positively correlated to initial seedling root-collar diameter, total dry weight and Dickson’s quality index, and can be reliably predicted by these variables. In contrast, seedling field survival of the two Mediterranean evergreen oak species was correlated with few initial morphological attributes; initial diameter provided an accurate index to predict second-year outplanting survival for both species while height/diameter was a good survival predictor for Q. coccifera seedlings. For C. siliqua seedlings, seedlings with larger initial diameter and total biomass survive better in the field. Thus, diameter was the common variable that accurately predicted survival for all species, which should be >5 mm for P. halepensis seedlings and >7 mm for the remaining species.

Dynamic Modulus of HMA and Its Relationship to Actual and Predicted Field Performance Using MEPDG

AbstractA database of dynamic modulus values for typical Superpave mixes widely used in the state of Washington was developed and used to investigate the sensitivity of the dynamic modulus to aggregate gradation. Seven job-mix formulas (JMFs) were selected for study. The percent of these mixes passing a No. 200 sieve was changed by ±2% to prepare additional mixes referred to as modified mixes. Statistical analysis showed that using different JMF mixes significantly affected the dynamic modulus. This was not the case when the JMF was modified by changing the percent passing a No. 200 sieve. A simple evaluation of the prediction accuracy of the new Mechanistic-Empirical Pavement Design Guide (MEPDG) was conducted in which the measured dynamic modulus was used as a key input parameter to predict pavement distresses. Level 1 and Level 3 predictions of rutting, longitudinal cracking, alligator cracking, and International Roughness Index (IRI) were compared with field performance data. The MEPDG predicted IRI a...