Volume Change Behaviour of Soil Influenced with Sulfuric Acid

The paper brings out the role of calcium carbonate (CaCO3) on the volume change behaviour of natural black cotton soil with 1N sulfuric acid (H2SO4) as pore fluid. Natural black cotton soil contained predominantly montmorillonite [Ca0.2(Al,Mg)2Si4 O10 (OH)2 .4H2O] along with other minerals such as amesite [(Mg Fe)2 Al (Si Al)2 O5 (OH)4], kalsilite [KAlSiO4] and quartz [SiO2]. The calcitic soil, reacted with H2SO4 during consolidation testing, showed the presence of the new mineral yavapaiite [K Fe(SO4)2]. Consequently, the carbonate soil treated with 1N H2SO4 led to higher swell at seating load and more compression upon loading than the soil with no carbonate. The swelling increased with increase in the amount of carbonate present in the soil.

Numerical modeling of the contaminant Transport through stratified soil

The transport processes of the dissolved chemicals in stratified or layered soils have been studied for several decades. In case of the solute transport through stratified layers, interface condition plays an important role in determining appropriate transport parameters. First‐ type and third‐ type interface conditions are generally used in the literature. A first‐type interface condition will result in a continuous concentration profile across the interface at the expense of solute mass balance. On the other hand, a discontinuity in concentration develops when a third‐ type interface condition is used. To overcome this problem, a combined first‐ and third‐ type condition at the interface has been widely employed which yields second‐ type condition. This results in a similar break‐through curve irrespective of the layering order, which is non‐physical. In this work, an interface condition is proposed which satisfies the mass balance implicitly and brings the distinction between the breakthrough curves for different layering sequence corroborating with the experimental observations. This is in disagreement with the earlier work by H. M. Selim and co‐workers but, well agreement with the hypothetical result by Bosma and van der Zee; and Van der Zee.

Volume Change behaviour in Calcitic Soil influenced with Sulphuric Acid using Artificial Neural Networks

This paper elucidates the methodology of applying artificial neural network model (ANNM) to predict the percent swell of calcitic soil in sulphuric acid solutions, a complex phenomenon involving many parameters. Swell data required for modelling is experimentally obtained using conventional oedometer tests under nominal surcharge. The phases in ANN include optimal design of architecture, operation and training of architecture. The designed optimal neural model (3-5-1) is a fully connected three layer feed forward network with symmetric sigmoid activation function and trained by the back propagation algorithm to minimize a quadratic error criterion.The used model requires parameters such as duration of interaction, calcite mineral content and acid concentration for prediction of swell. The observed strong correlation coefficient (R2 = 0.9979) between the values determined by the experiment and predicted using the developed model demonstrates that the network can provide answers to complex problems in geotechnical engineering.

Modeling wrap faced reinforced soil retaining walls subjected to dynamic excitation

This paper describes some of the physical and numerical model tests of reinforced soil retaining walls subjected to dynamic excitation through uni-axial shaking tests. Models of retaining walls are constructed in a perspex box with geotextile reinforcement using the wrap around technique with dry sand backfill and instrumented with displacement sensors, accelerometers and soil pressure sensors. Numerical modelling of these shaking table tests is carried using FLAC. Numerical model is validated by comparing physical model results. Responses of wrap faced walls with different number of reinforcement layers are discussed from both the physical and numerical model tests. Results showed that the displacements are decreasing with the increase in number of reinforcement layers while acceleration amplifications are not affected significantly.

Contolling Alkali Induced Heave in soil with fly ash

The properties of the soils can change drastically due to the presence of contaminants leading to several geotechnical failures founded on them. One important pollutant that can have considerable effect is the alkali released from varies industries. It is known that alkali solutions can increase the swelling of soil containing both expansive and non-expansive minerals.Many attempts to control this alkali-induced heave in soils through chemical agents were not successful. With a view to study the use of fly ash to stabilize alkali contaminated soil, the behavior of soils containing 25% and 50% of fly ash has been studied in the presence of 2N-alkali solution. Results of volume change behavior of non-expansive soil containing kaolinite clay mineral in the presence of fly ash showed that it is effective to control the alkali induced swelling in the soil. The effectiveness increases with an increase in the percentage of fly ash in soils. Detailed X-ray diffraction and SEM studies showed that the mineralogical changes that occur in soil due to alkali interaction are inhibited in the presence of fly ash.

Optimal Parameterized Policies for Resource Allocation in Communication Networks

The problem of finding optimal parameterized feedback policies for dynamic bandwidth allocation in communication networks is studied. We consider a queueing model with two queues to which traffic from different competing flows arrive. The queue length at the buffers is observed every T instants of time, on the basis of which a decision on the amount of bandwidth to be allocated to each buffer for the next T instants is made. We consider two different classes of multilevel closed-loop feedback policies for the system and use a two-timescale simultaneous perturbation stochastic approximation (SPSA) algorithm to find optimal policies within each prescribed class. We study the performance of the proposed algorithm on a numerical setting and show performance comparisons of the two optimal multilevel closedloop policies with optimal open loop policies. We observe that closed loop policies of Class B that tune parameters for both the queues and do not have the constraint that the entire bandwidth be used at each instant exhibit the best results overall as they offer greater flexibility in parameter tuning. Index Terms — Resource allocation, dynamic bandwidth allocation in communication networks, two-timescale SPSA algorithm, optimal parameterized policies. I.

Optimal maintenance policies for machines subject to deterioration and intermittent breakdowns

Optimal preventive maintenance policies, for a machine subject to deterioration with age and intermittent breakdowns and repairs, are derived using optimal control theory. The optimal policies are shown to be of bang-bang nature. The extension to the case when there are a large number of identical machines and several repairmen in the system is considered next. This model takes into account the waiting line formed at the repair facility and establishes a link between this problem and the classical ``repairmen problem.''

Optimal energy management policies for energy harvesting sensor nodes

We study a sensor node with an energy harvesting source. The generated energy can be stored in a buffer. The sensor node periodically senses a random field and generates a packet. These packets are stored in a queue and transmitted using the energy available at that time. We obtain energy management policies that are throughput optimal, i.e., the data queue stays stable for the largest possible data rate. Next we obtain energy management policies which minimize the mean delay in the queue. We also compare performance of several easily implementable sub-optimal energy management policies. A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay.