Acceptable Error Limits Research Articles

An insight into the mechanical and morphological properties of palm oil plasticized high density polyethylene-chitosan composites

An experimental analysis of the mechanical properties of maleic anhydride compatibilized high density polyethylene-chitosan composites plasticized with palm oil were investigated. The effect of chitosan as filler (0, 2.5, 5, 7.5 and 10 wt%) on the mechanical properties of the injection moulded samples and its comparison with the corresponding palm oil plasticized with the optimised composite system has been performed. The mechanical properties of the melt mixed composites were studied and compared. An increase of 11.3 % in tensile strength, 9.4% in impact strength and 44.4 % increase in Young's modulus for 5 wt% chitosan loaded composite system was obtained when compared with the neat HDPE system. Furthermore, the addition of 5 wt% palm oil to the optimised system increased its impact strength to 102 kJ/m2 when compared to the neat high density polyethylene system without chitosan. The improved compatibility between high density polyethylene and chitosan has been further confirmed through the morphological analysis. Finite element analysis of the tensile properties showed comparable values with the experimental values within acceptable error limits. This study led to the development of a bio-based material having better mechanical performance which can be used in bone-tissue engineering applications.

Optimisation of Exhaust Emissions, Vibration, and Noise of Unmodified Diesel Engine Fuelled with Canola Biodiesel-Diesel Blends with Natural Gas Addition by Using Response Surface Methodology

The paper presents methods to determine the optimum input parameters of CNG addition, biodiesel blend ratio, and engine speed to improve engine responses in terms of exhaust emissions, vibration, and noise of CNG-biodiesel-diesel fuelled engine. Box-Behnken based on response surface methodology was used to predict and optimise input parameters. Variance analysis was applied to determine the significant relationship between the input parameters and engine responses. At optimum input parameters (CNG addition=9.24 L/min, biodiesel blend ratio=40%, engine speed=1524.24 rpm), the optimum engine responses of NOx, CO, CO2, O2, engine vibration acceleration, and noise were 93.77 ppm, 438.05 ppm, 1.47%, 18.59%, 37.17 m/s2 and 91.34 dB[A], respectively. In terms of coefficient determination of R2, the values were 99.11%, 99.22%, 99.41%, 99.70%, 98.65%, and 98.60% respectively. The correlation between the optimised result and the engine test result showed an acceptable error limit for NOx, CO, CO2, O2, engine vibration acceleration, and noise as 4.2%, 3.8%, 4.9%, 0.25%, 4.12%, and 0.17%, respectively.

Comparative performance analysis of precise point positioning technique in the UAV − based mapping

Uncrewed Aerial Vehicle (UAV) photogrammetry is a very efficient, low-cost approach for mapping small or medium-sized local areas. This approach is adequate for achieving the needed accuracy in many applications, and onboard positioning sensors have made this technique more feasible by decreasing the need for ground control stations (GCPs). When real-time positioning strategies are used, photogrammetric mapping can also be performed instantaneously in the field. This is especially crucial in applications like disaster management, where current situation must be detected rapidly. It is critical to choose a georeferencing approach in applications that is appropriate for the physical parameters of the mapping area, the intended use of the photogrammetric mapping, and the needed accuracy. In order to accurately georeference the photogrammetric outputs, this study assesses the real-time and post-processed performances of absolute and relative GNSS positioning approaches. Finally, it compares these strategies in terms of the position accuracy of the created models. In the evaluations, the 3D models of the study area were created utilizing network-based Real Time Kinematic (n-RTK), Post-Processed Kinematic (PPK) Positioning, and Precise Point Positioning (PPP) approaches, with direct georeferencing of the UAV-based photogrammetric images. These models were then compared to models developed using traditional indirect georeferencing with GCPs and aided indirect georeferencing. According to the findings, direct georeferencing using the n-RTK and PPK techniques provided a horizontal position accuracy in terms of root mean square errors (rms2D = 1.6 cm and 1.9 cm) almost equal to indirect georeferencing using GCPs (rms2D = 1.9 cm). In terms of vertical position accuracies, the n-RTK and PPK approaches in direct georeferencing (rmsh = 3.7 cm and 3.9 cm, respectively) produced rather different results than the GCPs-based conventional strategy (rmsh = 1.6 cm), although the discrepancies were within acceptable error limits. Direct georeferencing with the PPP approach produced the lowest horizontal and vertical position accuracies (rms2D = 5.9 cm, rmsh= 5.7 cm). However, this level of accuracy was deemed adequate for use in large-scale mapping in Turkey's authorized regulation.

Effect of Repeat Unit’s Composition Ratio on the Properties of a Random Copolymer: A Molecular Dynamics Simulation Study

For thermosetting resins the degree of cross-linking plays a crucial role in the dielectric properties of the resin. In our previous works we confirmed this by simulating the relationship between the dielectric properties of poly(2-(4-benzocyclobutenyl)-divinylbenzene (DVB-S-BCB)) and the degree of cross-linking. In our research described here, we constructed a novel random copolymer with all-hydrocarbon structure based on poly(DVB-S-BCB) by introducing styrene (St) as the second polymerization monomer, thus controlling the number of cross-linking sites in the polymer. The effect of changes in St monomer content (number of cross-linking points) in the polymer chains, i.e. DVB-S-BCB and St, on the dielectric properties of the cured resins was investigated by molecular dynamics simulations. The simulation results showed that increasing the St monomer content in the copolymer, decreasing the cross-linking points, led to an increase in the dielectric constant of the cured resin, in addition to which the copolymer exhibited excellent thermo-mechanical properties. We also tested resin samples prepared by the experimental method and compared them with the simulated data, confirming the reliability of the results within acceptable error limits.

Inference and visualization of nuclear magnetic moment studies with neuro-fuzzy systems

This study aims to predict the magnetic moments of nuclei with odd-A numbers in a certain region of which the magnetic moment has not yet been calculated, using the Adaptive Neuro-Fuzzy Inference System (Anfis) method. In our Anfis model the proton number (Z), neutron number (N), and spin value (I) are used as inputs for nuclei with 1 ≤ Z ≤ 88. With 652 nuclei in the dataset, consisting of the provided input data, 528 odd-A nuclei were used for training, and 124 odd-A nuclei were used for testing. The fact that the Anfis model was closer to the experimental data in the training and testing processes than the theoretical methods encouraged us to make inferences about the nuclei of which experimental nuclear magnetic moment is unknown. Motivated by the presence of odd-A nuclei exhibiting I π = 1/2±, 3/2±, and 5/2± ground-state configurations near the doubly closed-shell, within the 1 ≤ Z ≤ 28 regions, along with the limited knowledge of nuclear properties in this range. This study has conducted magnetic moment inferences for 165 nuclei lacking experimental data. Specifically, Na, F, and P isotopes have been chosen as Magnetic moment value inferences made for these isotopes using Anfis have also been compared with the theoretical results of the Quasiparticle-Phonon Nuclear Method (QPNM) and with the Shell Model calculations. There is a satisfactory agreement between our predictions and the results of these two theories. Furthermore, it is noteworthy that within the same isotope series, nuclei with identical ground-state configurations consistently yield compatible results, irrespective of the availability of experimental magnetic moments. In addition, the fact that the values obtained from test and train operations remain within acceptable error limits, with a range of approximately 0.03%–0.04%, reveals the reliability of our system. Since the Neuro-Fuzzy system will be a first in the field of nuclear technologies, we believe that the outputs of our study will be a good reference for future studies.

Development and Evaluation of Multipurpose Phantom for Delivery Quality Assurance of Intensity-modulated Radiation Therapy

Treatments demanding high accuracy, such as intensity-modulated radiation therapy (IMRT), should provide the optimal dose distribution and correct intervention. Otherwise, they may become unsafe and cause adverse effects to patients. Delivery quality assurance (DQA) for treatment verification can be performed considering the absolute dose using an ionization chamber and relative dose using a film. However, a film imposes a long waiting time for measurement and is sensitive to temperature and humidity, development conditions, and noise. We aim to evaluate the usefulness of a multipurpose phantom for fast and simple IMRT DQA. The multipurpose phantom is made of poly (methyl methacrylate)-based resin. The phantom allows the insertion of a 2D array detector and an ionization chamber. Therefore, the relative and absolute doses can be measured simultaneously. The IMRT DQA evaluation provided absolute dose of 0.35 ± 1.74% and relative dose of 99.03 ± 0.6 % in 3 mm/3% gamma evaluation for a linear accelerator. In addition, the absolute and relative doses were 1.37 ± 1.05% and 98.7 ± 0.78% in helical tomotherapy, respectively. Therefore, the dose measurements were within acceptable error limits of 3%. The results demonstrate the multipurpose capabilities of the proposed phantom for evaluating dose distribution and absolute dosimetry.

Robot vision-based control strategy to suppress residual vibration of a flexible beam for assembly

PurposeIndustrial robots are extensively used in the robotic assembly of rigid objects, whereas the assembly of flexible objects using the same robot becomes cumbersome and challenging due to transient disturbance. The transient disturbance causes vibration in the flexible object during robotic manipulation and assembly. This is an important problem as the quick suppression of undesired vibrations reduces the cycle time and increases the efficiency of the assembly process. Thus, this study aims to propose a contactless robot vision-based real-time active vibration suppression approach to handle such a scenario.Design/methodology/approachA robot-assisted camera calibration method is developed to determine the extrinsic camera parameters with respect to the robot position. Thereafter, an innovative robot vision method is proposed to identify a flexible beam grasped by the robot gripper using a virtual marker and obtain the dimension, tip deflection as well as velocity of the same. To model the dynamic behaviour of the flexible beam, finite element method (FEM) is used. The measured dimensions, tip deflection and velocity of a flexible beam are fed to the FEM model to predict the maximum deflection. The difference between the maximum deflection and static deflection of the beam is used to compute the maximum error. Subsequently, the maximum error is used in the proposed predictive maximum error-based second-stage controller to send the control signal for vibration suppression. The control signal in form of trajectory is communicated to the industrial robot controller that accommodates various types of delays present in the system.FindingsThe effectiveness and robustness of the proposed controller have been validated using simulation and experimental implementation on an Asea Brown Boveri make IRB 1410 industrial robot with a standard low frame rate camera sensor. In this experiment, two metallic flexible beams of different dimensions with the same material properties have been considered. The robot vision method measures the dimension within an acceptable error limit i.e. ±3%. The controller can suppress vibration amplitude up to approximately 97% in an average time of 4.2 s and reduces the stability time up to approximately 93% while comparing with control and without control suppression time. The vibration suppression performance is also compared with the results of classical control method and some recent results available in literature.Originality/valueThe important contributions of the current work are the following: an innovative robot-assisted camera calibration method is proposed to determine the extrinsic camera parameters that eliminate the need for any reference such as a checkerboard, robotic assembly, vibration suppression, second-stage controller, camera calibration, flexible beam and robot vision; an approach for robot vision method is developed to identify the object using a virtual marker and measure its dimension grasped by the robot gripper accommodating perspective view; the developed robot vision-based controller works along with FEM model of the flexible beam to predict the tip position and helps in handling different dimensions and material types; an approach has been proposed to handle different types of delays that are part of implementation for effective suppression of vibration; proposed method uses a low frame rate and low-cost camera for the second-stage controller and the controller does not interfere with the internal controller of the industrial robot.

Development of ICP‐OES Based Analytical Method with Prior Preferential Removal of Emission Rich Matrix by Elevated Temperature Ionic Liquid Based Extractive Mass Transfer for Determination of Metallic Constituents in U‐Mo Alloy: The Next Generation Nuclear Fuel

AbstractAn (ICP‐OES) based analytical methodology was developed for the determination of metallic constituents (Al, Ca, Co, Cr, Cu, Fe, Ga, In, Mn, Mg, Na, Ni, Si, V, W and Zn) at minor and trace level in U−Mo alloy fuel after preferential separation of emission rich major matrix using TBP‐HDBO‐NTf2 without any compromise on the determination of analytes at trace levels. Application of ionic liquid, HDBO‐NTf2 drastically reduced the time of analysis (30 min reduction per sample) and generation of toxic organic waste (20 mL per sample) containing U and Mo. The method was optimized by identification of analytical lines of the elements free from spectral interference of U and Mo, establishing the calibration curves using those lines and evaluation of analytical performances (detection limit, linear dynamic range etc.) in U−Mo matrix. The preferential separation of U and Mo were found to follow anion exchange and cation exchange mechanism involving UO2((NO)3)3.2TBP− and MoO2(NO3) TBP+ species, respectively, which differ in their conventional separation by solvation mechanism involving ML2 and ML1 neutral species, respectively. Preferential separation by HDBO‐NTf2 based system can be effectively used for determination of analytes of 10 ppm concentration at 10 % error limit. The total uncertainty in estimation of each analyte have been estimated. The real sample analyses data were compared to that obtained by n‐dodecane based ICP‐OES method and direct analysis of Energy Dispersive X‐ray Fluorescence spectroscopic (EDXRF) method. The data were found to be in good agreement with each other. The experimentally obtained results were subjected to t‐test with 95 % confidence limit and 10 degrees of freedom. The texpt was found to be less than tcrit 2.228 revealing reliability of the methods. The experimentally obtained variance values (Fexpt) were found to be less than Fcrit∼2.980 revealing the variance values are within acceptable statistical error limit.

Elastic anisotropic finite-difference full-wave modeling and imaging of 2D tilted transversely isotropic (TTI) media

Imaging below the tilted transversely isotropic (TTI) media pose serious problems and distortions of the subsurface geological targets of interest for hydrocarbon exploration, which is very common in fold-thrust belts or active tectonic areas like the Rocky Mountain foothills of the Canada or foothills of the Himalaya. To model and image below the TTI media having symmetry axis orthogonal to dipping anisotropic layers, a 2D TTI thrust sheet is considered for elastic anisotropic finite-difference full-wave modeling and generation of synthetic seismic data using the robust staggered-grid scheme of wave propagation. Free-surface boundary conditions at the top and absorbing boundary conditions for the other three sides of the model have been imposed to reduce undesirable edge effects and suppress dispersions. The synthetic seismic data generated for the 2D TTI thrust model are migrated using the anisotropic Kirchhoff pre-stack time (PSTM) and depth migration (PSDM) technique followed by the migration velocity analysis (MVA) algorithm. The traveltime computations are made using robust eikonal equations with fourth-order elastic anisotropic finite-difference solutions to handle large tilts (ν) along with anisotropic ray-tracing to image below the TTI thrust sheet. The MVA algorithm adopted also estimates the anisotropic parameters ε and δ accurately within the acceptable error limit through successive iterations of inversion and parameter update, which results in sufficient flattening of the reflection events in the common image gathers (CIGs). This is a powerful and stable methodology to handle large tilt (ν = 60°) of the steeply dipping reflectors in complex geological structure like the TTI thrust model without much distortion of CIGs for which the symmetry axis of each TTI block is set orthogonal to the bottom of the reflectors having different tilts.

Studi Pendahuluan Sistem Akuakultur Cerdas Berbasis Online Monitoring Terhadap Unjuk Kerja Kincir Aerasi

This article discusses a preliminary study of developing a paddlewheel aerator for shrimp ponds using an integrated intelligent aquaculture system to support intensification. Two paddlewheel aerators with different phases have been successfully installed. The test was carried out on two different types of motors, which were intended to comprehend the performance of every motor on a paddlewheel aerator. The ratio of the speed values for a single-phase motor was 102 rpm and for a 3-phase motor was 110.3 rpm. The data from the performance observation of the aeration wheel motor can be viewed via a smartphone using a website application. The data displayed from the observations are in the form of data on voltage, current, frequency, power, power factor, and the power generated by the pinwheel motor. The test results show the performance of the aeration wheel motor that works under normal conditions with an average measurement error of 0.23%, below the acceptable error limit of 0.5%. This research forms the basis for a smart aquaculture system that can be developed domestically to support local industries in Indonesia.

Indifference Computer Experiment for Mathematical Identification of Two Variables

In order to understand the two types of nonlinear differential equation problems in engineering dynamics, the author proposes a numerical analysis method for the two types of nonlinear differential equations based on computer simulation. This method establishes the MATLAB algorithm structure of the numerical solution of the fourth-order fixed-step Runge-Kutta and Lorenz models, discusses the error control in the case of variable step size, and plots the numerical solutions of the Lorenz system based on MATLAB in two-dimensional and three-dimensional space graphics. The x -direction displacement and y -direction displacement data are extracted from the Lorenz equation as iterative samples of the model, the regression curve obtained after iteration has a slope of 0.996, and the iterative regression model reflects the basic characteristics of the data well. This method presents the basic idea of numerical solution verification within acceptable error limits. For solving engineering problems with differential equations as mathematical models, an effective numerical solution method is provided, and further discussion on the numerical solutions of partial differential equations is of great significance.

Pemodelan Numerik Aliran Angin di Sekitar Gedung Tinggi Menggunakan Metode RANS Standard K-ε dengan Program OpenFOAM

Amplified wind loads around buildings could induce structural failure, thus making it important to understand the behavior of fluid flow between buildings. In this study, the analysis is performed using RANS, a computational fluid dynamics (CFD) simulation with faster computation time compared to other methods. OpenFOAM, an open-source software, is used to run the simulations. This study used a structured mesh with standard RANS k − ε turbulence model. Four symmetrical buildings with a scale of 1: 420 are used as the model of this study. Numerical modelling of different computational domain size and different degrees of fineness of the meshing is simulated to determine margin of errors. The result indicates that changes in computational domain has a significant effect on CFD analysis in lowering the error value in area with high flow speed ratio (U/U0> 1) to reach the acceptable error limit. Contrastingly, changes in the degree of fineness of the meshing do not give a significant change in error value. A relatively coarse meshing with fast computation time could give a similar result as A fine meshing model with longer computation time.

Development of a Multilayer Perceptron Neural Network for Optimal Predictive Modeling in Urban Microcellular Radio Environments

Modern cellular communication networks are already being perturbed by large and steadily increasing mobile subscribers in high demand for better service quality. To constantly and reliably deploy and optimally manage such mobile cellular networks, the radio signal attenuation loss between the path lengths of a base transmitter and the mobile station receiver must be appropriately estimated. Although many log-distance-based linear models for path loss prediction in wireless cellular networks exist, radio frequency planning requires advanced non-linear models for more accurate predictive path loss estimation, particularly for complex microcellular environments. The precision of the conventional models on path loss prediction has been reported in several works, generally ranging from 8–12 dB in terms of Root Mean Square Error (RMSE), which is too high compared to the acceptable error limit between 0 and 6 dB. Toward this end, the need for near-precise machine learning-based path loss prediction models becomes imperative. This work develops a distinctive multi-layer perception (MLP) neural network-based path loss model with well-structured implementation network architecture, empowered with the grid search-based hyperparameter tuning method. The proposed model is designed for optimal path loss approximation between mobile station and base station. The hyperparameters examined include the neuron number, learning rate and hidden layers number. In detail, the developed MLP model prediction accuracy level using different learning and training algorithms with the tuned best values of the hyperparameters have been applied for extensive path loss experimental datasets. The experimental path loss data is acquired via a field drive test conducted over an operational 4G LTE network in an urban microcellular environment. The results were assessed using several first-order statistical performance indicators. The results show that prediction errors of the proposed MLP model compared favourably with measured data and were better than those obtained using conventional log-distance-based path loss models.

A spatial upscaling method for describing the three-body potential of a diamond lattice structure

A spatial upscaling method that efficiently describes the three-body potential of diamond lattice structures is proposed in this paper. The spatial scale of the bulk single-crystal diamond can be increased without increasing the computational complexity by balancing the weighting factor with the atomic-scale Tersoff potential and the mass of its constituents. The statistical averages and fluctuations in the thermodynamic equilibrium were reproduced within acceptable error limits. The model used to represent the mechanical behavior of diamond-structured materials was further expanded to simulate polycrystalline diamond structures under mechanical deformation. An empirical scaling formula was applied to attenuate localized stresses generated at the surfaces and grain boundaries. The upscaled model successfully reproduced the deformation energy distribution under spherical indentation observed from the all-atom-based simulation model.

Data-driven modeling of multiaxial fatigue in frequency domain

A data-driven approach to modeling multiaxial fatigue in frequency domain is proposed. The paper presents a methodology through which models can be built to predict fatigue damage based on a multiaxial cycle counting method and the associated life assessment approach in frequency domain. Through apt parameterization of spectrum in conjunction with principal component analysis transformation, every biaxial stress state in frequency domain can be represented as a point on a common feature space. The proposed methodology consists of three phases: exploratory study, data generation and model development. Two structural components are used for the demonstration. The performance of the models are evaluated in comparison with time domain approaches, and results are compared. The proposed methodology is able to predict multiaxial fatigue damage in frequency domain within acceptable error limits, allowing for a fast and efficient method to tackle multiaxial fatigue analysis in frequency domain.

Accuracy of body composition measurement techniques across the age span.

This study investigated the acceptable accuracy of common body composition techniques compared with the reference 4-compartment (4C-R) model, which has not been investigated in a sample with diverse characteristics, including age and sex. Techniques included components of the 4C-R model [dual-energy X-ray absorptiometry, air displacement plethysmography, deuterium dilution (DD)] and surrogate compartment models, which utilised bioelectrical impedance spectroscopy (BIS) rather than DD. Men and women (sex = 1:1, 18-85 years, n = 90) completed body composition testing under best-practice guidance. For measurement of individuals, only the reference 3-compartment (3C-R) equation met acceptable error limits (<5% error among individuals) within the a priori cut-point (80%) for fat-free mass (FFM; CV = 0.52%) and fat mass (FM; CV = 1.61%). However, all investigated techniques reached equivalency to the 4C-R model for FFM on average (CV = 0.52-4.31%), but for FM only the 3C and 4C equations that included quantification of total body water (TBW) by DD or BIS reached equivalency overall (CV = 1.61-6.68%). Sex and age minimally influenced accuracy. Only the 3C-R or 4C-R equations are supported for acceptable individual accuracy for both FFM and FM. For group estimates any investigated technique could be used with acceptable accuracy for FFM; however, for FM, inclusion of TBW measurement within a compartment model is necessary. Novelty: Only the referent 3C and 4C models (including deuterium dilution) provide accurate body composition results that are acceptable for measurement of individuals in the general population. For group estimates of lean mass in the general population, compartments models that include TBW must be used for accurate measurement.

Alkaline phosphatase interference in immuno-enzymatic assays.

BackgroundAlkaline phosphatase (ALP) enzymes are widely used as signal amplifiers in immunoenzymatic methods. Conditions that cause ALP elevations, such as bone or liver diseases, can cause interference in immunoenzymatic methods. We aimed to examine ALP's effect on immunoenzymatic assay by adding isolated pure ALP to the prepared serum pool.MethodsWe prepared a serum pool and divided it into 4 groups. By adding isolated pure ALP at different concentrations to each group, we obtained sample groups containing ALP enzyme at concentrations of 85 U/L, 340 U/L, 870 U/L, and 1570 U/L. 20-repetition of bhCG, ferritin, FT4, TSH, troponin I, and Vit B12 tests were performed in each group. The coefficient of variation, bias, and total error was calculated. All groups were compared by using the Friedman test for paired samples.ResultsAfter ALP addition, the calculated total error values of FT4, bhCG and troponin I tests were above the acceptable error limits. There were statistically significant differences in bhCG, FT4, troponin I, and Vit B12 tests compared to the baseline ALP level (P<0.0125).ConclusionsIsolated ALP elevations can be a source of interference for immunoenzymatic methods.

Preoperative Ozaki technique measures on tridimensional engineered root

BackgroundThe aortic valve neocuspidalization (AVNeo) is an innovative surgical technique aiming at the reconstruction of the aortic valve using autologous pericardium. One of the main criticisms to AVNeo is the longer duration of the aortic clamping time (ACT) as compared to standard aortic valve replacement due to the sizing of the valve neocusps. MethodsWe retrospectively enrolled 30 consecutives patients underwent AVNeo. For each patient we developed a 3D aortic root model (ARM) based on CT-scan datasets. We retrospectively compared the leaflets measurements performed during surgery with those obtained on the corresponding ARMs. ResultsIn 100% of cases no difference between the in vitro and in vivo measurements exceeded the acceptable error limit of 2 ​mm. The correlation of each single in vitro versus in vivo measurements demonstrates a strong coincidence between the two different methods of sizing (r ​> ​0,9, p ​< ​.0001). By analyzing the data considering the annulus perimeter and not the single cusp size, the perfect coincidence was to be found in 89.9% with a slight acceptable discrepancy (2 ​mm on total) in the remaining 10.1%. Conclusions3D-ARMs, printed from CT-scan, represent a reproducible process to obtain overlapping cusp sizes compared to those measured in-vivo, possibly reducing the ACT.

Experimental investigation on potential use of drilling parameters to quantify rock strength

The uniaxial compressive strength (UCS) represents the strength of the rock. It frequently requires during the introductory phase of mining projects such as tunneling, rock excavation, blast hole designs, etc. Usually, the determination of UCS of rocks is carrying out in a concerned laboratory. The main drawback of determining the UCS in a laboratory requires at least five core samples of high-grade quality. Many problems and limitations are associated with removing the core, and also preparing the test specimen for UCS is tedious, time-consuming, and expensive. Therefore an attempt is made to develop an efficient indirect method to estimate the UCS of rocks without using the core samples. In this experimental investigation, the drilling response, such as thrust, is gathered by drill tool dynamometer considering the different drill operating parameters. The prediction model is developed with a regression technique using the measured thrust and calculated torque. The prediction capacity and validation of the model are carried out using the standard procedure. The experimental results show that the model could explain the variance in UCS up to 93.60%. RMSE and MAPE values in terms of percentage are 3.49% and 11.27%, respectively. Besides, the model's validation is checked for sandstone and limestone having the UCS 28 MPa and 35 MPa, respectively, and yielded the best prediction results with an error of 8.51% and 8.01% suggesting that the developed model could predict the UCS of sedimentary rock types within acceptable error limit, and reasonably. The correlation of UCS of rocks and drilling specific energy is also tested and found that linear relationship between them with an R2 value of 92.10%.

Digital Building-Height Preparation from Satellite Stereo Images

Buildings are considered prominent objects for understanding the pattern of growth in an urban setting. Remote sensing technology plays a vital role in facilitating data generation pertaining to various urban applications. Digital surface models represent the elevation of the earth surface features, and can be obtained from stereo images, radar, laser scanning, and so on. Photogrammetric techniques applied to optical stereo satellite images are economical and fast ways to generate height information of buildings. In this work, a quantitative and qualitative analysis of digital surface models generated from Cartosat-1 stereo images is compared with openly available data. The study finds that it is possible to acquire about 50 percent of building heights with acceptable error limits. The experimental results indicate that the quality of height information is suitable for applications to assess urban development at a macro scale, but not for individual building-level modeling.