Weight Of Mixture Research Articles

Plasticity-Based Method for the Design and Analysis of Cold Recycled Pavement Layers

Abstract Asphalt cold recycling technologies allow the use of up to 100 % reclaimed asphalt pavement (RAP) from an existing asphalt pavement to construct new base layers and new subbase layers. Bituminous stabilized materials (BSM), obtained from cold recycling technologies, are susceptible to traffic-induced accumulation of permanent deformation. In the current design methods, BSM pavement layers are typically assumed to have a linear elastic response under traffic loading application, and this does not account for plasticity initiation and accumulation in the material. This research study provides insight on how to integrate plasticity behavior in numerical simulations of rehabilitated pavement structures with BSM. A BSM mixture prepared with 1.5 % cement by weight of total mixture and 1.5 % foamed asphalt binder content by weight of dry aggregates is characterized in the laboratory. Subsequently, a three-dimensional elastic-perfectly plastic finite element model is developed for the simulation of triaxial shear strength tests. Lab measured force-displacement curves are matched with the numerical simulations at different confining pressures. The calibrated mechanical properties are then used as input parameters in multilayer pavement models for pavement evaluation. Different pavement structures with and without BSM layers are compared in terms of a maximum allowable number of loading repetitions before reaching a 20-mm rut depth on the surface of the pavement. The results indicate that structures with BSM and traditional granular base layers yield comparable results in terms of rutting potential. In addition, the study presents a framework for the design and analysis of cold recycled pavement layers and a method to integrate the plasticity behavior of partially-bonded and unbounded layers for pavement evaluation.

Characterization of Incorporating RAP Materials to the Asphalt Layers of Pavement Structure

Recycling the old paving waste and reusing it in the construction of new highways was resorted to, and this is a good step from an economic point of view, as well as from an environmental and health point of view, as it reduces carbon emissions and eliminates a large amount of disposable reclaimed asphalt pavement materials (RAP). This study aims to evaluate the best layer of pavement structure; base, binder, and surface layers for inclusion (RAP) materials based on stability and indirect tensile strength. In addition, highlight the best percentage that can be added from RAP to achieve positive results and better than that associated reference mixture in terms of Marshall test and Indirect tensile strength test RAP materials collected from different sources Karbala and Fallujah, were adopted in this study at percentages of 20%, 30%, and 40% by weight of the asphalt mixture. Two scenarios of incorporating RAP materials have been adopted : The first is considered that RAP as a black rock in which the effect of aged binder surrounding the aggregate of RAP is neglected while the second is not considered RAP as black rock and the influence of aged binder in RAP materials has been taken into consideration. Dora bitumen has been adopted in the current study which is used commonly in Iraq. It has been highlighted that the best layer in which RAP can be incorporated is the base layer, with a percentage up to 40% that RAP without considering RAP black rocks regardless of the sources of RAP

On a Modified Weighted Exponential Distribution with Applications

Practitioners in all applied domains value simple and adaptable lifetime distributions. They make it possible to create statistical models that are relatively easy to manage. A novel simple lifetime distribution with two parameters is proposed in this article. It is based on a parametric mixture of the exponential and weighted exponential distributions, with a mixture weight depending on a parameter of the involved distribution; no extra parameter is added in this mixture operation. It can also be viewed as a special generalized mixture of two exponential distributions. This decision is based on sound mathematical and physical reasoning; the weight modification allows us to combine some joint properties of the exponential and weighted exponential distribution, which are known as complementary in several modeling aspects. As a result, the proposed distribution may have a decreasing or unimodal probability density function and possess the demanded increasing hazard rate property. Other properties are studied, such as the moments, Bonferroni and Lorenz curves, Rényi entropy, stress-strength reliability, and mean residual life function. Subsequently, a part is devoted to the associated model, which demonstrates how it can be used in a real-world statistical scenario involving data. In this regard, we demonstrate how the estimated model performs well using five different estimation methods and simulated data. The analysis of two data sets demonstrates these excellent results. The new model is compared to the weighted exponential, Weibull, gamma, and generalized exponential models for performance. The obtained comparison results are overwhelmingly in favor of the proposed model according to some standard criteria.

Permanent Deformation Characterization of Stone Matrix Asphalt Reinforced by Different Types of Fibers

This paper focused on the stone matrix asphalt (SMA) technology that was developed essentially to guard against rutting distress. For this procedure, fibers play a racy role in stabilizing and preventing the drain down problem caused by the necessity of high binder content coupled with their strengthening effect. A set of specimens with cylindrical and slab shapes were fabricated by inclusions jute, polyester, and carbon fibers. For each type, three contents of 0.25%, 0.5%, and 0.75% by weight of mixture were added by lengths of 5, 7.5, and 10 mm. The prepared mixtures were tested to gain the essential pertained parameters discriminated by the values of drain down, Marshall quotient, rut depth, and dynamic stability. It has appeared that the fibers rate of 0.5% and 7.5 mm length is much appropriate to yield the best performance of modified mixtures. At these values, carbon fibers recorded the highest increase level of rutting resistance and dynamic stability by 53% and 100%, respectively while, jute fibers exhibited the lowest improvement by only 34% and 63%, respectively; nevertheless, they produced mixtures having the lowest drain down value. Regarding the index of plastic stiffness, polyester fibers embedded mixtures occupied the first rank of increasing by 38%.

Ensuring efficiency in broiler meat production with a set of innovative approaches to poultry feeding

The article deals with the study of the effect of synbiotic feed additive with pro-, prebiotic and sorption properties in the feeding of broiler chickens up to 37 days of age. The activity of specially selected specific bacterial strains of the feed additive increased due to the innovative approach to the selection of microbial strains composition, unique production method and lyophilic drying method. Adding the studied feed additive “Synbiosorb-2” in the amount of 0,10 % of the weight of the feed mixture proved to be the best dosage and increased the live weight of broiler chickens by 7,0 %, kept livestock by 3,0 %, muscle gain - by 25,4 % and reduced feed expenses per unit production by 6,8 %. Feeding synbiotic had a positive effect on the physiological and biochemical status of young poultry.

3D Multiple Sound Source Localization by Proposed T-Shaped Circular Distributed Microphone Arrays in Combination with GEVD and Adaptive GCC-PHAT/ML Algorithms.

Multiple simultaneous sound source localization (SSL) is one of the most important applications in the speech signal processing. The one-step algorithms with the advantage of low computational complexity (and low accuracy), and the two-step methods with high accuracy (and high computational complexity) are proposed for multiple SSL. In this article, a combination of one-step-based method based on the generalized eigenvalue decomposition (GEVD), and a two-step-based method based on the adaptive generalized cross-correlation (GCC) by using the phase transform/maximum likelihood (PHAT/ML) filters along with a novel T-shaped circular distributed microphone array (TCDMA) is proposed for 3D multiple simultaneous SSL. In addition, the low computational complexity advantage of the GCC algorithm is considered in combination with the high accuracy of the GEVD method by using the distributed microphone array to eliminate spatial aliasing and thus obtain more appropriate information. The proposed T-shaped circular distributed microphone array-based adaptive GEVD and GCC-PHAT/ML algorithms (TCDMA-AGGPM) is compared with hierarchical grid refinement (HiGRID), temporal extension of multiple response model of sparse Bayesian learning with spherical harmonic (SH) extension (SH-TMSBL), sound field morphological component analysis (SF-MCA), and time-frequency mixture weight Bayesian nonparametric acoustical holography beamforming (TF-MW-BNP-AHB) methods based on the mean absolute estimation error (MAEE) criteria in noisy and reverberant environments on simulated and real data. The superiority of the proposed method is presented by showing the high accuracy and low computational complexity for 3D multiple simultaneous SSL.

Comparative effect of fertilization on cocoyam and component crops on Cocoyam-based intercropping systems in Uyo, Southeastern Nigeria

Field experiment was conducted at University of Uyo Teaching, research farm during the 2018 and 2019 cropping seasons to assess the effect of fertilization on cocoyam-based intercropping systems. The experiment was laid out in a randomized complete block design with three replications. Treatments were six fertilizers rates - 0kg/ha, NPK200kg/ha, NPK400kg/ha, PM2.5t/ha, PM5.0t/ha, Mixture (NPK200kg/ha + PM2.5t/ha) and six crop mixtures - Sole Cocoyam, Sole Melon, Sole Maize, Cocoyam + Maize, Cocoyam + Melon and Cocoyam + Melon + Maize). Result analysed with analysis of variance revealed PM2.5t/ha, NPK400kg/ha and Mixture (NPK200kg/ha + PM2.5t/ha) gave higher plant height, leaf area, stem girth in sole cocoyam, maize and melon respectively. PM2.5t/ha favoured leaf area, stem girths of cocoyam, maize with cocoyam + maize, cocoyam + melon and cocoyam + melon + maize crop mixtures. PM5.0t/ha gave higher values of corm, cormels, cormels weight, cormels number and cormels length in both sole cocoyam and mixtures (cocoyam + melon, cocoyam + maize, cocoyam + melon + maize) in both seasons respectively. PM2.5t/ha gave higher values of maize grain yield with cocoyam + maize, cocoyam + melon + maize crop mixtures. PM5.0t/ha and NPK400kg/ha gave higher melon seed values with cocoyam + melon and cocoyam + Melon + maize. Conclusively, it is recommended that application of organic fertilizer promotes higher yields and yield components in both sole and crop mixtures of cocoyam and maize respectively.

Use of the feed additive “Toxinon” in feeding of replacement young chickens and laying hens

At the present time of the development of industrial poultry farming, the main tasks are to increase the productivity of poultry, reduce production costs and improve its quality. Under practical conditions, there is a shortage of minerals in compound feed for poultry, which leads to a violation of metabolism in the body, slowing down growth and development, deterioration of the work of organs and systems, a decrease in productivity and its quality, and an increase in the prime-cost of production. The purpose of the research was to study the effectiveness of the use of the feed additive “Toxinon” in feeding of replacement young chickens and laying hens. The research has been carried out under the conditions of OOO “Bogotolskaya Poultry Farm” in the Bogotolsky area in the Krasnoyarsk Territory. Comprehensive studies have been conducted to study the effect of the feed additive “Toxinon” on the growth and development, productivity and metabolism of replacement young chickens and laying hens of the industrial herd of the cross “Haysex brown”. The influence of different dosages of the feed additive “Toxinon” on the growth rate, livestock livability, digestibility and use of feed nutrients, egg productivity, egg quality, hematological and biochemical blood parameters of replacement young chickens and laying hens has been studied. The laying hens of the 3rd experimental group were distinguished by the highest egg productivity during the experiment period, which exceeded the control group in terms of the gross number of eggs by 6,4 %, the intensity of egg production by 5,02 abs.%, egg weight by 3,0 % (P > 0,95), the yield of egg mass on the average laying hen by 9,12 %. At the same time, expenditures of feed in the 3rd experimental group have decreased compared to the control group by 7,3 % for 10 eggs, by 9,2 % for 1 kg of egg mass. It has been found that in feeding replacement young chickens and laying hens, the most effective use of the feed additive “Toxinon” in the dosage of 0,25 % of the weight of the feed mixture (2,5 kg/ton of feed).

Rare Events via Cross-Entropy Population Monte Carlo

We present a Cross-Entropy based population Monte Carlo algorithm. This methods stands apart from previous work in that we are not optimizing a mixture distribution. Instead, we leverage deterministic mixture weights and optimize the distributions individually through a reinterpretation of the typical derivation of the cross-entropy method. Demonstrations on numerical examples show that the algorithm can outperform existing resampling population Monte Carlo methods, especially for higher-dimensional problems.

Performance evaluation of porous asphalt mixtures modified with basalt fiber

Porous pavement applications, which is environmentally friendly, especially for residential areas, allow rainwater to remain clean and to feed groundwater through infiltration. Porous asphalt pavements, in which are among the pavement types used in porous pavements systems, also reduce environmental noise pollution. On the other hand, there is a need to improve the performance of these asphalt pavement mixtures, which have a short service life due to their porous structure. It has been considered to improve the performance of the pavement mixtures by using basalt fiber without compromising the hydraulic permeability level. The waste slag material released during the ferrochrome production process was used as aggregate in the porous asphalt mixture design. Thus, it is aimed to benefit from the economic and environmental aspects with the recycling of ferrochrome slag in an area suitable for its properties. In the study, the design performances of porous asphalt mixtures were determined with tests such as volume analysis, permeability, Cantabro particle loss, indirect tensile strength, and moisture susceptibility. Basalt fiber was added at 0.2%, 0.4%, 0.6% and 0.8% of the mixture weight. It has been determined that the mixtures of basalt fibers at 0.2% significantly improve the mechanical performance.

Identifying marginal treatment effects in the presence of sample selection

This article presents identification results for the marginal treatment effect (MTE) when there is sample selection. We show that the MTE is partially identified for individuals who are always observed regardless of treatment, and derive uniformly sharp bounds on this parameter under three increasingly restrictive sets of assumptions. The first result imposes standard MTE assumptions with an unrestricted sample selection mechanism. The second set of conditions imposes monotonicity of the sample selection variable with respect to treatment, considerably shrinking the identified set. Finally, we incorporate a stochastic dominance assumption which tightens the lower bound for the MTE. Our analysis extends to discrete instruments. The results rely on a mixture reformulation of the problem where the mixture weights are identified, extending Lee’s (2009) trimming procedure to the MTE context. We propose estimators for the bounds derived and use data made available by Deb et al. (2006) to empirically illustrate the usefulness of our approach.

The role of mix design and short glass fiber content on mode-I cracking characteristics of polymer concrete

Suitable resistance against fracture and cracking is a primary requirement for using polymeric concrete materials in practical applications. The main aim of this research is to investigate the effect of mix-design on mode I cracking behavior. A total number of 72 different Polymer Concrete (PC) mix-designs made of four ingredients (epoxy resin, coarse silica aggregate, fine sand filler and chopped strand E-glass fibers) were considered for conducting fracture experiments using the Semi-Circular Bend (SCB) specimen. The weight percentages of the ingredients were varied in the following range: 17–25% resin, 75–81% fine and coarse aggregates and 0–2% glass fibers. The investigated mix-designs were categorized into six groups (ultra-high, high, medium-high, medium-low, low and ultra-low) in terms of the adhesive agent content (i.e. the ratio of resin plus fiber content to the weight of the whole mixture). The experiments showed the noticeable dependency of both fracture toughness and fracture energy values (KIf and GIf) on the PC mix-design. In addition, the effect of substituting 1 and 2% of resin content with glass fiber was investigated. It was found that adding the fiber cannot necessarily enhance the performance of PC mixture against cracking and for some mix-designs; the addition of fiber can even reduce both KIf and GIf values.

Performance Characterization of Stone Mastic Asphalt using Steel Fiber

Stone Mastic Asphalt (SMA) is a gap-graded hot mixture designed to provide higher resistance towards permanent deformation and rutting potential by 30% to 40% more than dense-graded asphalt, due to its stable aggregate skeleton structure. However, compared to other types of hot mix asphalt, SMA unfortunately has some shortcomings in term of its susceptibility towards moisture-induced damage due to its structure and excessive bitumen content in the composition. This research aims to assess the performance of a SMA mixture with steel fiber by enhancing overall stability, abrasion resistance, and, most importantly, moisture susceptibility. This study involved the incorporation of various steel fiber proportions of 0%, 0.3%, 0.5% and 0.7% by the total weight of mixture. The steel fiber modified SMA was made up of 6.0% PEN 60/70 bitumen content. The performance of SMA were evaluated through Marshall stability and flow test, Cantabro loss test and indirect tensile strength test. The results obtained from the testing showed that the incorporation of steel fiber is significantly effective to enhance the resistance towards moisture damage, while increasing the stability and reducing the abrasion loss of SMA mixture, compared to conventional mixture. Overall, it can be concluded that the addition of steel fiber in asphalt mixture specifically SMA, has improved the mechanical performance in the application of asphalt pavement with the optimum steel fiber proportion of 0.3% by the weight of mixture. The developed models between the independent variables and responses demonstrated high levels of correlation. The study found that Response Surface Methodology (RSM) is an effective statistical method for providing an appropriate empirical model for relating parameters and predicting the optimum performance of an asphaltic mixture to reduce flexible pavement failure.

Pharmacognostic and antidysentery screening of mixed ethanol leaf extract of Parkia biglobosa and Acanthus montanus (50:50)

Introduction: Parkia biglobosa belong to the family mimosaceae and Acanthus montanus belong to the family acanthaceae. The plants both have a multipurpose use as herbal medicine. Aim: This work investigate the pharmacognostic standard and anti-dysentery activity of the mixed ethanol extract of both plants on E. histolytical induced dysentery. Method: The phytochemical, chemo microscopy and proximate analysis were carried out using the standard procedures. The mixed extract of ratio 50:50 was administered to different groups of rats at different doses. Loperamide was administered as standard drug. The change in faecal consistency was observed and recorded. Result: The phytochemical analysis shows the presence of alkaloids, tannins, proteins, glycosides and carbohydrates. Chemomicroscopy of both plants showed the presence of starch, calcium oxalate, lignin, cellulose. While the extractive value analysis gave 25.0% and 32.7% for water extractive value and ethanol extractive value respectively (for Acanthus montanus) and 23.0% and 30.0% for water extractive value and ethanol extractive value respectively (for Parkiabiglobosa). The absence of death at 5000mg/kg of the extract shows that the lethal dose of the ethanol extract of the plant mixture is higher than 5000mg/kg which may be an indication of safety of the mixture. The anti-dysentery activity of the mixture of both plants with different concentration of 250mg/kg, 500mg/kg, 1000mg/kg body weight of ethanol extract showed a significant change in the faecal consistency of the rats. The effect obtained on the administration of 500mg/kg body weight of the extract mixture is more comparable to the standard (loperamide). Conclusion: The synergistic use of the extract contains the secondary metabolites glycosides, alkaloids, flavonoids, which may be responsible for their anti-dysentery synergistic activity. Mixed extracts from both leaves of P. biglobosa and A. montanus can be recommended as an anti-dysentery agent.

Erlang mixture modeling for Poisson process intensities

We develop a prior probability model for temporal Poisson process intensities through structured mixtures of Erlang densities with common scale parameter, mixing on the integer shape parameters. The mixture weights are constructed through increments of a cumulative intensity function which is modeled nonparametrically with a gamma process prior. Such model specification provides a novel extension of Erlang mixtures for density estimation to the intensity estimation setting. The prior model structure supports general shapes for the point process intensity function, and it also enables effective handling of the Poisson process likelihood normalizing term resulting in efficient posterior simulation. The Erlang mixture modeling approach is further elaborated to develop an inference method for spatial Poisson processes. The methodology is examined relative to existing Bayesian nonparametric modeling approaches, including empirical comparison with Gaussian process prior based models, and is illustrated with synthetic and real data examples.

Strategies to Enhance the Performance of Gaussian Mixture Model Fitting for Uncertainty Quantification

Summary When formulating history matching within the Bayesian framework, we may quantify the uncertainty of model parameters and production forecasts using conditional realizations sampled from the posterior probability density function (PDF). It is quite challenging to sample such a posterior PDF. Some methods [e.g., Markov chain Monte Carlo (MCMC)] are very expensive, whereas other methods are cheaper but may generate biased samples. In this paper, we propose an unconstrained Gaussian mixture model (GMM) fitting method to approximate the posterior PDF and investigate new strategies to further enhance its performance. To reduce the central processing unit (CPU) time of handling bound constraints, we reformulate the GMM fitting formulation such that an unconstrained optimization algorithm can be applied to find the optimal solution of unknown GMM parameters. To obtain a sufficiently accurate GMM approximation with the lowest number of Gaussian components, we generate random initial guesses, remove components with very small or very large mixture weights after each GMM fitting iteration, and prevent their reappearance using a dedicated filter. To prevent overfitting, we add a new Gaussian component only if the quality of the GMM approximation on a (large) set of blind-test data sufficiently improves. The unconstrained GMM fitting method with the new strategies proposed in this paper is validated using nonlinear toy problems and then applied to a synthetic history-matching example. It can construct a GMM approximation of the posterior PDF that is comparable to the MCMC method, and it is significantly more efficient than the constrained GMM fitting formulation (e.g., reducing the CPU time by a factor of 800 to 7,300 for problems we tested), which makes it quite attractive for large-scale history-matching problems. NOTE: This paper is also published as part of the 2021 SPE Reservoir Simulation Conference Special Issue.

Reinforcement evaluation of different fibers on fracture resistance of asphalt mixture based on acoustic emission technique

Fibers have been proven to enhance the stability and mechanical strength of asphalt mixture, but different fibers exhibited diverse characteristics of reinforcement effect. This study is set out to investigate the fiber reinforcement effect of asphalt mixture containing glass fiber reinforced asphalt mixture (GFRAM), basalt fiber reinforced asphalt mixture (BFRAM), and steel fiber reinforced asphalt mixture (SFRAM). The control asphalt mixture (CAM) was also fabricated for comparison. The fiber content was 0.5% by weight of the asphalt mixture and the specimens were manufactured following the Marshall compaction method. Indirect tensile test (IDT) and acoustic emission (AE) test at low temperature were conducted simultaneously to characterize the fracture resistance of different types of fiber reinforced asphalt mixture (FRAM). The amplitude, count, rise angle (RA), average frequency (AF), and b-value were obtained based on AE signal analysis to evaluate FRAM's reinforcement effect. The results revealed that the addition of fibers dramatically improved the strength of CAM, and the occurrence of the main fracture in FRAM emerged later than CAM. SFRAM exhibited more favorable anti-cracking performance than GFRAM and BFRAM based on the comprehensive AE signals analysis.

On Construction and Estimation of Stationary Mixture Transition Distribution Models

Mixture transition distribution (MTD) time series models build high-order dependence through a weighted combination of first-order transition densities for each one of a specified number of lags. We present a framework to construct stationary MTD models that extend beyond linear, Gaussian dynamics. We study conditions for first-order strict stationarity which allow for different constructions with either continuous or discrete families for the first-order transition densities given a prespecified family for the marginal density, and with general forms for the resulting conditional expectations. Inference and prediction are developed under the Bayesian framework with particular emphasis on flexible, structured priors for the mixture weights. Model properties are investigated both analytically and through synthetic data examples. Finally, Poisson and Lomax examples are illustrated through real data applications. Supplementary files for this article are available online.

Evaluating the impact of fiber type and dosage rate on laboratory performance of Fiber-Reinforced asphalt mixtures

The purpose of this study was to evaluate the impact of fiber types, binder content, and their dosage rates on the volumetric properties and laboratory performance of asphalt mixtures. One asphalt mixture (control) and three fiber types (Basalt, Fiberglass, and Carbon) were used. Two different fiber dosage rates were considered 0.15% (recommended dosage rate) and 0.30% by total mixture weight. Furthermore, a novel experimental methodology was developed and implemented consisting of a volumetric mixture design and performance testing—Indirect Tensile Asphalt Cracking Test (IDEAL-CT) and Asphalt Pavement Analyzer (APA)—to isolate the effects of fiber types and dosage rates from the effect of binder content. Statistical analysis was also used to further evaluate the impact of fibers on mixture performance. Results showed that 0.15% dosage rate had little to no impact on optimum binder content, whereas 0.30% dosage rate required an increase in binder content of 0.6%, 0.6%, and 0.8% for basalt, fiberglass, and carbon fibers, respectively, to meet the volumetric requirements. This study showed that the need for additional binder content at 0.30% dosage rate could be due to an increase in specimen volume (referred to as rebounding height) that occurred after 24 h of specimen cooling at room temperature. Performance testing showed that 0.15% (regardless of fiber type) had no impact on cracking and rutting performance. At 0.30% dosage rate, only carbon fiber improved cracking performance without the use of additional binder. Overall, the study highlighted laboratory performance benefits and challenges of using fiber-reinforced reinforced asphalt mixtures.

Convex combinations in judgment aggregation

Judgments are the basis for almost all decisions. They often come from different models and multiple experts. This information is typically aggregated using simple averages, which leads to the well-known shared information problem. A weighted average of the individual judgments based on empirically estimated sophisticated weights is commonly discarded in practice, because the sophisticated weights have large estimation errors. In this paper, I explore mixture weights, which are convex combinations of sophisticated and naïve weights. I show analytically that if the data generation process is stable, there always exists a mixture weight which aggregates judgments better than the naïve weights. I thus offer a path to alleviate the shared information problem. In contrast to other proposed solutions, it does not require any control over the judgment process. I demonstrate the utility of mixture weights in numerical analyses and in two empirical applications. I also offer heuristic selection algorithms for the correct mixture weight and analyze them in my numerical and empirical settings.