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The design of the Advanced Combat Helmet (ACH) currently in use was optimized by its designers in order to attain maximum protection against ballistic impacts (fragments, shrapnel, etc.) and hard-surface/head collisions. Since traumatic brain injury experienced by a significant fraction of the soldiers returning from the recent conflicts is associated with their exposure to blast, the ACH should be redesigned in order to provide the necessary level of protection against blast loads. The paper aims to discuss this issue.

In the present work, an augmentation of the ACH for improved blast protection is considered. This augmentation includes the use of a polyurea (a nano-segregated elastomeric copolymer) based ACH external coating. To demonstrate the efficacy of this approach, blast experiments are carried out on instrumented head-mannequins (without protection, protected using a standard ACH, and protected using an ACH augmented by a polyurea explosive-resistant coating (ERC)). These experimental efforts are complemented with the appropriate combined Eulerian/Lagrangian transient non-linear dynamics computational fluid/solid interaction finite-element analysis.

The results obtained clearly demonstrated that the use of an ERC on an ACH affects (generally in a beneficial way) head-mannequin dynamic loading and kinematic response as quantified by the intracranial pressure, impulse, acceleration and jolt.

To the authors’ knowledge, the present work is the first reported combined experimental/computational study of the blast-protection efficacy and the mild traumatic brain-injury mitigation potential of polyurea when used as an external coating on a helmet.

The purpose of this paper is to optimize the design of the advanced combat helmet (ACH) currently in use, by its designers in order to attain maximum protection against ballistic impacts (fragments, shrapnel, etc.) and hard-surface/head collisions. Since traumatic brain injury experienced by a significant fraction of the soldiers returning from the recent conflicts is associated with their exposure to blast, the ACH should be redesigned in order to provide the necessary level of protection against blast loads. In the present work, augmentations of the ACH for improved blast protections are considered. These augmentations include the use of a polyurea (a nano-segregated elastomeric copolymer)-based ACH external coating/internal lining.

To demonstrate the efficacy of this approach, instrumented (unprotected, standard-ACH-protected, and augmented-ACH-protected) head-mannequin blast experiments are carried out. These experimental efforts are complemented with the appropriate combined Eulerian/Lagrangian transient non-linear dynamics computational fluid/solid interaction analysis.

The results obtained indicated that: when the extent of peak over-pressure reduction is used as a measure of the blast-mitigation effectiveness, polyurea-based augmentations do not noticeably improve, and sometimes slightly worsen, the performance of the standard ACH; when the extent of specific impulse reduction is used as a measure of the blast-mitigation effectiveness, application of the polyurea external coating to the standard ACH improves the blast-mitigation effectiveness of the helmet, particularly at shorter values of the charge-detonation standoff distance (SOD). At longer SODs, the effects of the polyurea-based ACH augmentations on the blast-mitigation efficacy of the standard ACH are inconclusive; and the use of the standard ACH significantly lowers the accelerations experienced by the skull and the intracranial matter. As far as the polyurea-based augmentations are concerned, only the internal lining at shorter SODs appears to yield additional reductions in the head accelerations.

To the authors’ knowledge, the present work contains the first report of a combined experimental/computational study addressing the problem of blast-mitigation by polyurea-based augmentation of ACH.

This study provides an integrated risk-based cost and time estimation approach for deep excavation projects. The purpose is to identify the best practices in recent advances of excavation risk analysis (RA) and integrate them with traditional cost and time estimation methods.

The implemented best practices in this research are as follows: (1) fault-tree analysis (FTA) for risk identification (RI); (2) Bayesian belief networks (BBNs), fuzzy comprehensive analysis and Monte Carlo simulation (MCS) for risk analysis; and (3) sensitivity analysis and root-cause analysis (RCA) for risk response planning (RRP). The proposed approach is applied in an actual deep excavation project in Tehran, Iran.

The results show that the framework proposes a practical approach for integrating the risk management (RM) best practices in the domain of excavation projects with traditional cost and time estimation approaches. The proposed approach can consider the interrelationships between risk events and identify their root causes. Further, the approach engages different stakeholders in the process of RM, which is beneficial for determining risk owners and responsibilities.

This research contributes to the project management body of knowledge by integrating recent RM best practices in deep excavation projects for probabilistic estimation of project time and cost.

The purpose of this paper is to calculate the Hugoniot relations of polyurea; also to investigate the atomic-scale energy change, the related chain conformation evolution and the hydrogen bond dissociation of polyurea under high-speed shock.

The atomic-scale simulations are achieved by molecular dynamics (MD). Both non-equilibrium MD and multi-scale shock technique are used to simulate the high-speed shock. The energy dissipation is theoretically derived by the thermodynamic and the Hugoniot relations. The distributions of bond length, angle and dihedral angle are used to characterize the chain conformation evolution. The hydrogen bonds are determined by a geometrical criterion.

The Hugoniot relations calculated are in good agreement with the experimental data. It is found that under the same impact pressure, polyurea with lower hard segment content has higher energy dissipation during the shock-release process. The primary energy dissipation way is the heat dissipation caused by the increase of kinetic energy. Unlike tensile simulation, the molecular potential increment is mainly divided into the increments of the bond energy, angle energy and dihedral angle energy under shock loading and is mostly stored in the soft segments. The hydrogen bond potential increment only accounts for about 1% of the internal energy increment under high-speed shock.

The simulation results are meaningful for understanding and evaluating the energy dissipation mechanism of polyurea under shock loading, and could provide a reference for material design.

The purpose of this paper is to strive to develop a rock fall velocity model in C++ language and to give spatial attributes to the model using Geographic Information System (GIS) capabilities. Interaction between the parameters involved in the model is evaluated through GIS embedded techniques.

The mathematical model developed in C++ is based on the physical law of gravitation pull, adjudging the potential fall between two points at different elevation. Further, parameters influencing the velocity gradient – namely local relief, coefficient of land use friction, slope amount and slope length – are incorporated in the model. GIS is used extensively to generate the data required for the model. GIS capabilities are also explored for visualisation and interpretation of the model output. Section profiles and a co‐relation coefficient further strengthen the velocity map.

The rock fall velocity map generated using GIS shows variations in the velocity gradient at selected sections. It is concluded from analysis that friction values play a pivotal role in drastically changing the velocity gradient.

The model presented is restricted to rock fall velocity evaluation for a rectangular matrix of input data and spatial extent, rather than for specific locations. Incorporating parameters to delineate source areas and runout zones would produce a more realistic scenario. Trials along this line are in progress and are expected to be executed successfully very shortly.

The paper presents a versatile model with easily extractable parameters to compute rock fall velocity at a regional scale, conditioned for rugged terrain. The model has specific implications in infrastructure development and planning management for rocky terrain. Moreover, the model's output can be implemented effectively in preliminary investigations of the protection of forest development and erecting defensive measures in rock fall‐prone areas.

Not many models are available for rock fall velocity estimation on a regional scale. The model developed through this research work provides a platform for a regional‐scale study using parameters that can be easily derived from DEM and a land use map. It is reiterated that the model output is helpful for land planners and managers engaged in mountain development. The model is an effective tool in the strategic development of hazard management plans in slide‐prone areas.

The higher education, universities and institutions across the world have increasingly adopted information and communication technology (ICT) as a tool for curriculum development, learning and teaching, and for administrative activities. The use of technology to facilitate learning is gaining acceptance across various educational institutions. In order to use technology in the best possible manner, it becomes essential that the teacher should be willing to accept the technology and use it for the teaching activities. Thus, the purpose of this paper is to understand the teachers’ motivation toward adopting technology in the higher education.

An exploratory-descriptive approach is used in this research. The sampling frame for the study is the teachers employed in the management institutes in Bengaluru, Pune, Indore and Delhi. A simple random sampling technique is used for identifying the sample for the study. A self-administered questionnaire was employed to measure the validity of items measuring the teacher’s intention to use technology.

The results of the study confirm a significant positive impact of value beliefs (VB), social influence (SI) and perceived ease of use (PEOU) on the behavioral intention (BI) to use technology by the teachers. However, the study does not establish the relationship between self-efficacy and BI to use technology by teachers.

The use of technology will be an important area in the field of higher education where it becomes crucial to understand the motivation factors that lead to the adoption of ICT in the classroom and the curriculum. In order to successfully integrate technology into the teaching-learning process, it is concluded that the factors that positively influence the BI to use technology include the VB, PEOU and the SI.

This study contributes toward the study of teachers’ motivation in the adoption of technology in higher education in India.