Prediction of ground vibration due to quarry blasting based on gene expression programming: a new model for peak particle velocity prediction

Blasting is a widely used technique for rock fragmentation in opencast mines and tunneling projects. Ground vibration is one of the most environmental effects produced by blasting operation. Therefore, the proper prediction of blast-induced ground vibrations is essential to identify safety area of blasting. This paper presents a predictive model based on gene expression programming (GEP) for estimating ground vibration produced by blasting operations conducted in a granite quarry, Malaysia. To achieve this aim, a total number of 102 blasting operations were investigated and relevant blasting parameters were measured. Furthermore, the most influential parameters on ground vibration, i.e., burden-to-spacing ratio, hole depth, stemming, powder factor, maximum charge per delay, and the distance from the blast face were considered and utilized to construct the GEP model. In order to show the capability of GEP model in estimating ground vibration, nonlinear multiple regression (NLMR) technique was also performed using the same datasets. The results demonstrated that the proposed model is able to predict blast-induced ground vibration more accurately than other developed technique. Coefficient of determination values of 0.914 and 0.874 for training and testing datasets of GEP model, respectively show superiority of this model in predicting ground vibration, while these values were obtained as 0.829 and 0.790 for NLMR model.     

Integration schemes with substepping algorithms for creep analysis in geomaterials

This paper describes a robust and efficient methodology for predicting displacements, deformations, and stresses in geomaterials that are susceptible to creep. The methodology is based on two integration schemes, which consider substepping algorithms. The first scheme is used for integrating space-time relations in a global sense, whereas the second scheme is used for integrating stress-stain relations in a local sense. Different from previous studies, both integration schemes are easy to implement and general in the sense that they can be applied to any type of creep law. Through an in-house finite element simulator, several numerical tests are performed. They include triaxial and wellbore closure analyses considering soft soils and salt rocks. The results show that the combination of both schemes leads to stable and accurate solutions with reduced computational time.     

Environmental isotope investigation for the identification of source of springs observed in the hillock on the left flank of Gollaleru Earthen Dam,Andhra Pradesh,India

A hydrometric, hydrochemical and environmental isotopic study was conducted to identify the source and origin of observed springs on the foot of the hillock abutting the left flank of the Gollaleru earthen dam, Nandyal, Andhra Pradesh, India. Water samples (springs, reservoir water and groundwater) in and around the dam area were collected and analyzed for environmental isotopes (\(\updelta ^{18}\!\hbox {O}\), \(\updelta ^{2}\hbox {H}\) and \(^{3}\hbox {H}\)) and hydrochemistry. Reservoir level, spring discharges and physico-chemical parameters (temperature, electrical conductivity, pH, etc.) were monitored in-situ. Isotopic results indicated that the source of springs is from the Owk reservoir and groundwater contribution to the springs is insignificant. Based on hydrometric observations, it is inferred that the springs might be originated from the reservoir level of 209 m amsl. It is found that the lower spring discharges were derived from diffuse sources (seepage) which could be a mixture of reservoir water and the groundwater, while the relatively higher spring discharges were resulted from concentrated sources (leakage) from the reservoir. Thus, the study portraits the usefulness of isotope techniques in understanding the dam seepage/leakage related problems.     

Appraisal of soft computing techniques in prediction of total bed material load in tropical rivers

This paper evaluates the performance of three soft computing techniques, namely Gene-Expression Programming (GEP) (Zakaria et al 2010), Feed Forward Neural Networks (FFNN) (Ab Ghani et al 2011), and Adaptive Neuro-Fuzzy Inference System (ANFIS) in the prediction of total bed material load for three Malaysian rivers namely Kurau, Langat and Muda. The results of present study are very promising: FFNN (R ² = 0.958, RMSE = 0.0698), ANFIS (R ² = 0.648, RMSE = 6.654), and GEP (R ² = 0.97, RMSE = 0.057), which support the use of these intelligent techniques in the prediction of sediment loads in tropical rivers.     

A study of Brans-Dicke theory in FRW-model

In FRW space time Brans-Dicke theory is developed for two cases: (i) the vacuum and (ii) the perfect fluid model. The field equations are transformed into a much simpler form under a change of time co-ordinates and then the solutions are determined for the above cases. An equation of statep =/3 (radiation) is assumed in the case of perfect fluid.     

Integrating agriculture and energy to assess GHG emissions reduction: a methodological approach

Agriculture is responsible for approximately 25% of anthropogenic global GHG emissions. This significant share highlights the fundamental importance of the agricultural sector in the global GHG emissions reduction challenge. This article develops and tests a methodology for the integration of agricultural and energy systems modelling. The goal of the research is to extend an energy systems modelling approach to agriculture in order to provide richer insights into the dynamics and interactions between the two (e.g. in competition for land-use). We build Agri-TIMES, an agricultural systems module using the TIMES energy systems modelling framework, to model the effect of livestock emissions and explore emissions reduction options. The research focuses on Ireland, which is an interesting test case for two reasons: first, agriculture currently accounts for about 30% of Ireland's GHG emissions, significantly higher than other industrialized countries yet comparable with global levels (here including emissions associated with other land-use change and forestation); second, Ireland is both a complete and reasonably sized agricultural system to act as a test case for this new approach. This article describes the methodology used, the data requirements, and technical assumptions made to facilitate the modelling. It also presents results to illustrate the approach and provide associated initial insights.

Policy relevance

Most of the policy focus with regard to climate mitigation targets has been on reducing energy-related CO₂ emissions, which is understandable as they represent by far the largest source of emissions. Non-energy-related GHG emissions – largely from agriculture, industrial processes, and waste – have received significantly less attention in policy discourse. Going forward, however, if significant cuts are made in energy-related CO₂ emissions, the role of non-energy-related GHG emissions will grow in importance. It is therefore crucial that climate mitigation analyses and strategies are not limited to the energy system. This article shows the value of using integrated energy and agriculture techno-economic modelling techniques to draw evidence for new comprehensive climate policy strategies able to discern between the full range of technical solutions available. It enables the production of economy-wide least-cost climate mitigation pathways.     

An assessment of the creep behaviour of Brazilian salt rocks using the multi-mechanism deformation model

Salt rocks are geomaterials that exhibit several peculiarities, which require a particular approach in rock mechanics. In the field, those rocks are usually found in layered/bedded deposits and in domes or similar structures. Creep is one of the main deformation mechanisms associated with salt rocks, and this phenomenon is highly dependent on the stress state, temperature and mineralogy. Salt rock mechanics for engineering applications requires the definition of a powerful constitutive model and this is an ongoing challenge. Among the many available models, one of the most sophisticated physical constitutive models for salt rocks is the multi-mechanism deformation creep model (MD model). The main contribution of this work is to present a first effort in the use of the MD model for Brazilian salt rocks. Material-sensitive parameters have been calibrated for the Brazilian halite through two methodologies. Salt is modelled as an elasto-viscoplastic material. Numerical simulations using the finite element method have been carried out for triaxial creep tests, Pre-salt wellbore closure and mining gallery convergence in order to validate the parameter set and the methodologies. Excellent results have been observed in most of the applications for validation. Even so, validation efforts should continue to consolidate the parameters and identify possible limitations.     

Age and growth of redeye round herring Etrumeus whiteheadi off the South African coast

Ages of redeye round herring Etrumeus whiteheadi were estimated with associated errors and used to infer life-history information, such as age composition, age-at-maturity and instantaneous mortality rate. Samples were collected in November 2005 during a research survey aimed at estimating the biomass of spawning pelagic fish off South Africa’s west and south coasts. Replicate age estimates obtained from sagittal otoliths were collected with slight bias and relatively high precision. A von Bertalanffy model describing growth of the combined sexes, including juveniles, was L_t = 20.41(1 ? e^{?0.41(t ? 1.92)}). Kimura’s likelihood ratio test revealed no statistically significant differences between growth parameters of males and females. Results suggested that otolith length is a better predictor of age than otolith weight. Maturity estimates for E. whiteheadi were similar to those previously documented.