Fatemeh Molaei

Bio: Fatemeh Molaei is an academic researcher from University of Arizona. The author has contributed to research in topics: Thermal conductivity & Molecular dynamics. The author has an hindex of 6, co-authored 21 publications receiving 93 citations. Previous affiliations of Fatemeh Molaei include Stantec & New Mexico Institute of Mining and Technology.

A Comprehensive Review on Internet of Things (IoT) and its Implications in the Mining Industry

Abstract: The integration of computer-based technologies interacting with industrial machines or home appliances through an interconnected network, for teleoperation, workflow control, switching to autonomous mode, or collecting data automatically using a variety of sensors, is known as Internet of Things (IoT). When applied inside an industrial context, it is possible to immediately benefit from the analytics obtained, contributing to process optimization, machine health, the safety of workers and asset management. IoT can assist real-time platforms in remotely monitoring and operating a complex production system with minimal intervention of humans. Hence it can be beneficial for hazardous industries, such as mining, by increasing the safety of personnel and equipment while reducing operation costs. An ideal smart automated mine could potentially be achievable by gradually taking advantage of IoT. Currently, different sensors are used in mine-related activities, such as geophones in exploration and blast control, piezometers in dewatering and toxic gas detectors in working frontlines. However, a fully integrated automated system is challenging in practice due to infrastructural limitations in communication, data management and storage. Moreover, the tendency of mining companies to continue with traditional methods instead of relying on untested novel techniques decelerates this progress. In this study, the adaptability of the mining industry to IoT systems and its current development is reviewed. Significant challenges of this progress are investigated and recommendations to develop a comprehensive model suited for different mining sections such as exploration, operation and safety considering flexible technologies such as Wireless Sensor Networks and the introduction of Global Data Management.

Investigation of tetracosane thermal transport in presence of graphene and carbon nanotube fillers––A molecular dynamics study

Abstract: This paper examines the thermal properties of pure tetracosane paraffin, tetracosane-graphene, and tetracosane-carbon nanotube mixed phase change materials (PCM). The most important properties studied were thermal capacity in constant volume (Cv), mean square displacement of atoms (MSD), radial distribution function (RDF), density, phonon density of states (PDOS) and thermal conductivity (k) under different temperatures. The results show that graphene and carbon nanotube increase the thermal conductivity of the tetracosane at different temperatures, but decrease the molecular movement and its thermal capacity (except after about 360 K), and it can be said that this slightly decreases the paraffin melting temperature. It was demonstrated that carbon nanotube is more efficient than graphene to increase the thermal conductivity of the proposed PCM.

Interfacial Thermal Resistance Mechanism for the Polyaniline (C3N)–Graphene Heterostructure

Abstract: The transport properties of hybrid nanostructures formed by graphene and polyaniline (C3N) are investigated using molecular dynamics simulations. We systematically explored various possible atomic ...

Investigating the effects of adding hybrid nanoparticles, graphene and boron nitride nanosheets, to octadecane on its thermal properties

Abstract: Octadecane is an alkane that is used to store thermal energy at ambient temperature as a phase change material. A molecular dynamics study was conducted to investigate the effects of adding graphene and a boron nitride nanosheet on the thermal and structural properties of octadecane paraffin. The PCFF force field for paraffin, AIREBO potential for graphene, Tersoff potential for the boron nitride nanosheet, and Lennard-Jones potential for the van der Waals interaction between the nanoparticles and n-alkanes were used. Equilibrium and nonequilibrium molecular dynamics simulations were used to study the nano-enhanced phase change material properties. Results showed that the nanocomposite had a lower density change, more heat capacity (except at 300 K), more thermal conductivity, and a lower diffusion coefficient in comparison with pure paraffin. Additionally, the nanocomposite had a higher melting point, higher phonon density of state and radial distribution function peaks.

Fast parallel algorithms for short-range molecular dynamics

Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.

A Wireless Sensor Network.

Abstract: The Wireless sensor network play a vital role in collecting a Real – Time data, monitoring environmental conditions based on technology adoption. These sensor network is the combination of sensing, computation, and communication through a single tiny device. Here many tiny nodes assemble and configure themselves. It also controls actuators that extend control from cyberspace into the physical world. Here the sensor nodes communicate with the local peers rather than the high – power control tower or base station. Instead, of relying on a predeployed infrastructure, each individual sensor or actuator become part of the overall infrastructure. Here we have three hardware platforms that addresses the needs of wireless sensor netwoks. The operating system here uses an event based execution to support concurrency. The platform serves as a baseline and does not contain any hardware accelerators. . First platform serves as a baseline and it produces Operating system concepts for refining concurrency mechanisms. The second node validates the architectural designs and improve the communicational rates. The third node represents the full realization of the general architecture. Keywords— node, platform, concurrency.

Cobalt: Chapter F of critical mineral resources of the United States - Economic and environmental geology and prospects for future supply

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