# Technologies and Principles of Hot Recycling and Investigation of Preheated Reclaimed Asphalt
## 3 RAP Batching Accuracy and Precision
### Methods  
The following mixture for a road pavement surface and base courses of two types was produced in a batchAMP with preheated RAP: with 25% and 50% of RAP, AC 16 PD and AC 22 PS, respectively. The grade of AC 16 DP according to the national standard TRA ASFALTAS 09 is asphalt concrete (AC); maximum size of particles--16 mm; purpose--for pavement single ply surface course (PD). The grade of AC 22 PS is also asphalt concrete (AC); maximum size of particles--22 mm; purpose--for pavement base course (P); also, purpose--for the heavy load (S). To investigate the accuracy and precision of RAP batching, technological data about RHMA mixtures produced in 2014, which were stored in an APM handling computer, were used. AMP handling software presents rated (target) and factual data on the name and number of job-mix formula (JMF), weight, mixing time, and temperature of each RHMA mix batch. Masses of all mineral materials, bitumen, additives, and RAP weighed batches are presented as well. For statistical purposes, only the data when most of RHMA mixture was produced were used: 10-day AC 16 PD mixture production data and 12-day AC 22 PS grade hot-mix asphalt (HMA) mixture production data. Quite large sample sizes, presented in Table 1, allowed the study to obtain rather dependable investigation data. RHMA mix batches of less than 2800 kg (outliers) were eliminated from each sample size. Statistical investigation was conducted on the data of 3041 mix batches, for the production of which approximately 3400 t of RAP was used and approximately 9000 t of RHMA mixture were produced. Statistical data were calculated through the use of Statgraphics Centurion XVII software package (Statpoint Technologies, Inc., Warrenton, VA, USA) for statistical processing, which allowed to identify the accuracy and precision of RAP batching in a batch-type AMP. AMP handling computer data of each working day's lot were grouped and classified by days and grades of RHMA mixture. Total weight \(Q_{batchi}\) of RHMA mix batch and weighed RAP batch mass \(q_{RAPi}\) were calculated. RAP percentage content in each asphalt mix batch was calculated according to this data:  
\[x_{RAPi}=\frac{q_{RAPi}}{Q_{batchi}}\ \times\ 100 \tag{7}\]  
where \(x_{RAPi}\)--RAP content in \(i\) RHMA mix batch, %; \(q_{RAPi}\)--RAP batch mass, kg, \(Q_{batchi}\)--RHMA mix batch mass, kg; \(i\)--\(i\) RHMA mix batch (\(i\) = 1, 2,... \(N\), \(N\)--RHMA mix batches' number). Statistical indices of the produced RHMA mixture of both grades RAP batch mass position and variation were calculated, and diagrams and histograms were drawn (Figures 6 and 7). The accuracy of RAP batching was identified by comparing average RAP content deviation from JMF in the produced RHMA mixture:  
\[\Delta q_{RAP}=\frac{\overline{q}_{RAP}-q_{RAP,JMF}}{q_{RAP,JMF}}\ \times\ 100, \tag{8}\]  
where \(\overline{q}_{RAP}\)--average of RAP batches mass, kg; \(q_{RAP,JMF}\)--target RAP batch mass according to JMF, kg. Standard deviation was used to evaluate the precision of RAP batching (Figure 7). Normal distribution of both sample sizes of RAP batch mass was tested, which enabled the calculation of the average precision of RAP batching process. Normal distribution of experimental data was investigated by applying skewness and kurtosis. The values of the coefficient of skewness \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Type of RHMA** & **Days** & **Total Sample Size** & **Sample Size Without Outliers** \\ \hline AC 16 PD & 10 & 1424 & 1324 \\ AC 22 PS & 12 & 1617 & 1569 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Sample sizes of the data used in the investigationand coefficient of kurtosis \(ku\) calculated from data of sample size were compared with their respective standard deviations \(s_{sk}\) and \(s_{ku}\):  
\[s_{sk}=\sqrt{\frac{6n(n\,-\,1)}{(n\,-\,2)(n\,+\,1)(n\,+\,3)}}, \tag{9}\]  
\[s_{ku}=\sqrt{\frac{24n(n-1)^{2}}{(n-3)(n-2)(n+3)(n+5)}}, \tag{10}\]  
where \(n\)--the sample size (number of measurements).